Copyright Yiyuan Ben Yin 2019

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Copyright

Yiyuan Ben Yin

2019

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ABSTRACT

Sensing and Mitigating Water Contaminants with Engineered Gold-Based Nanostructures

by

Yiyuan Ben Yin

Decentralized or distributed water monitoring and treatment systems are expected to be a

fundamental tenant of the next generation of solutions aimed at addressing the global

water crisis. Within this context, emerging nanotechnology-based options provide a

promising approach to overcome many of the shortcomings associated with traditional,

centralized water treatment technologies. For example, in the realm of water monitoring,

gold-based nanostructures exhibit unique optical properties compared with bulk Au

which can be employed as more rapid and affordable options for contaminant detection

than conventional technologies (e.g., ion chromatography). However, there are still many

technological challenges that limit practical implementation. Typically, Au

nanostructures lack the sensitivity to detect contaminants at low concentration levels

relevant to drinking water standards, and/or display insufficient selectivity to find

practical use in real complex water matrices. Similarly, regarding remediation, Au-based

nanostructures display promising catalytic performance towards the degradation of

contaminants but are often negatively impacted by other co-present species in the water

matrix. This is particularly problematic in the treatment of highly complex waters such as

oil and gas hydraulic fracturing produced waters (HFPW). Here, two Au-bases

nanostructures, luminescent gold nanoclusters (Au NCs) and bimetallic palladium gold

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nanoparticles (PdAu NPs), were investigated for their ability to circumvent these

limitations for contaminant sensing and catalytic water treatment, respectively.

Hexavalent chromium (Cr(VI)) is a carcinogenic contaminant regulated by the

United States Environmental Protection Agency (US EPA) with the maximum

contaminant level (MCL) of 100 ppb in drinking water. As Cr(VI) detection probes,

novel Au nanostructures with Au NCs encapsulated in silica-coated microcapsule

structures were developed, which have a 5× luminescence enhancement compared to

traditional luminescent Au NCs, and can detect Cr(VI) at concentrations as low as 6 ppb.!

The Au microcapsules can also be successfully extended to a simple test strip system,

similar to that of a pH indicator paper.

The reuse of HFPW requires the removal of organic compounds. Bimetallic PdAu

NPs were investigated as catalysts to degrade phenol, a model organic compound, at

room temperature and atmospheric pressure via the in-situ catalytic formation of H2O2.

PdAu showed the highest rate of phenol degradation compared with pure Pd and Au in

simulated HFPW with total dissolved solid (TDS) concentration as high as ~16,000 ppm.

However, while viable, performance was still negatively impacted by neutral pH and

elevated TDS concentrations. It was further found that with a cost-effective additive,

bimetallic PdAu NPs can degrade phenol with a TDS of ~160,000 ppm even at neutral

pH. Again compared to pure Pd and Au, bimetallic PdAu NPs showed greater resistance

to high TDS and lower byproduct formation rates. As a proof of concept, a scaled-up

model of this technology was built implementing a circulating trickle bed reactor to

successfully treat model HFPW.!

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Acknowledgments

When I looked back my five-year Ph.D. research on catalysis and nanomaterials, I

surprisingly found this journey somewhat resembled a typical catalytic reaction pathway.

Looking at the reaction coordinate diagram, which shows the energy changes of a

molecule along its reaction pathway, I am thinking myself as the molecule. How similar

the energy ups and downs of the molecule is to the countless ups and downs during my

Ph.D. path. More similarly, catalysts could accelerate the reaction by reducing the energy

barrier and there are actually many excellent “catalysts” making my Ph.D. path less

struggled. Here, I would like to express my deep gratitude for these “catalysts”.

Firstly, I would like to thank my Ph.D. advisor Dr. Michael S. Wong for

providing guidance and supports along my Ph.D. journey at Rice University. I’m always

thankful for being offered by numerous opportunities from Dr. Wong. The training I

received at Wong Group significantly improved my research logics and presentation

skills, which benefited me for my time as a Ph.D. student and will be a treasure for my

future career. The high standards set by Dr. Wong seemed scary but eventually pushed

me to be a better and well-rounded person.

I appreciate Dr. Aditya Mohite, Dr. Eilaf Egap, and Dr. Michael Reynolds served

in my thesis committee and provided feedback for my research work. As a collaborator

and sponsor for parts of my research, Dr. Reynolds generously shared his knowledge

with me and continuously encouraged and helped me along my Ph.D. journey.

I am deeply gratitude for all my co-authors and collaborators contributing to my

research. I thank Dr. Z. Conrad Zhang for hosting me as a visiting scholar at Dalian

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Institute of Chemical Physics (DICP), China for our collaboration project in the summer

of 2016. Dr. Zhang’s patience, kindness, humbleness and high working efficiency always

impress and motivate me. I thank Dr. Nathan Cai and Ms. Christina Robinson for the

helpful discussion on commercialization opportunities of my sensing project. I thank

Ibrahim A. Said for the help of constructing the recirculating trickle bed reactor. I thank

all staff, faculty and members in the Nanotechnology Enabled Water Treatment (NEWT)

Center, especially the Director Dr. Pedro J. J. Alvarez, for providing a collaborative and

interactive research platform.

I would like to thank all my current and previous colleagues in the Catalysis and

Nanomaterials Laboratory for being parts of my Ph.D. journey. Specifically I thank Dr.

Li Chen for her tremendous mentorship not only for my research but also for my life. I

clearly remembered numerous late nights we worked and discussed together in the lab

and office. Your braveness always encourages me. I thank Dr. Kimberly Heck for her

huge help on revising my manuscripts and providing insights for my research. I thank Mr.

Christian Coonrod for helping edit my thesis and offer strong help for various my

projects. I thank Dr. Varun Gangoli and Mr. Yinhong Cheng for their guidance and help

for my first project at the beginning of my Ph.D. journey. I thank Dr. Ciceron Ayala for

his kind supports on transmission electron microscope imaging. I thank Ms. Sujin Guo

and Ms. Camilah Powell for their continuous encouragement and supports along the

journey. I thank Ms. Chelsea Clark for her technical supports on various instrumentation

and helpful discussions on my research. I also thank Dr. Zhun Zhao, Dr. Yu-lun Fang,

Dr. Zhen Wang, Dr. Welman Elias, Dr. Mayank Gupta, Dr. Sivaram Pradhan, Dr. Pinn-

Tsong Chiang, Ms. Yan Xu, Ms. Priscilla Dias, Mr. Jake Lobb, Ms. Samantha

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Samaniego, Mr. Hunter Jacobs, Ms. Tanya Rogers, Mr. Austin Fehr, Ms. Lijie Duan, Mr.

Bo Wang, and Ms. Xinying Luan for being together with me and helping me at the

Catalysis and Nanomaterials Laboratory.

I would like to thank my friends who have walked together with me though my

toughest five years. Especially to Dr. Jieyi Zhang, Dr. Jun Kuang, Dr. Yuchong Zhang,

Dr. Yan Yan, Mr. Leilei Zhang, Dr. Zeliang Chen, without the encouragement and

accompany from you, I could not make through my Ph.D. journey. I thank Dr. Yongchao

Zeng, Dr. Le Wang, Dr. Xiaoqun Mu and Dr. Luqing Qi for providing helpful career

advice.

Last but not least, I would like to express my deepest gratitude to my family: my

father Lixin Yin, mother Yinzhi Xu, wife YanLin Cai and daughter Lexi Yin. My parents

persuaded me to pursue my Ph.D. that was not my plan five years ago. Look back from

now, I was thankful to take their suggestion and start this incredible journey. My parents

did not understand much about my research, but they were always willing to listen and

ready to provide unconditional supports. I met my wife during the time when my projects

get stuck and I was depressed to think of quitting. The optimism, proactivity and

confidence her brought to me changed my life. The career advice from my wife pushed

me stepped of my comfort zone, which led directly to my job offer. Lexi came to my

family towards the end of my Ph.D. journey, which motivated me to take more

responsibilities as a father.

Yiyuan Ben Yin

December 2019

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Table of Contents

Acknowledgments ............................................................................................................. v!

Table of Contents ........................................................................................................... viii!

List of Figures ................................................................................................................. xiii!

List of Tables ................................................................................................................. xvii!

List of Scheme .............................................................................................................. xviii!

Chapter 1 Background and Research Overview ............................................................ 1!

1.1. Centralized versus decentralized water treatment and monitoring systems!.............!1!

1.1.1. Point of use (POU) drinking water monitoring!.................................................!4!

1.1.2. On-site hydraulic fracturing produced water treatment and reuse!.....................!5!

1.2. Nanostructures-enabled DWTM systems!.................................................................!7!

1.3. Gold nanostructures as sensing materials!.................................................................!9!

1.3.1. Luminescent gold nanoclusters!.......................................................................!10!

1.3.2. Au NCs for water contaminant sensing!...........................................................!11!

1.4. Gold-based nanostructures as catalytic materials!...................................................!11!

1.4.1. Bimetallic PdAu catalysts!................................................................................!12!

1.4.2. PdAu catalyst for water contaminant degradation!...........................................!12!

1.5. Research overview and thesis layout!.....................................................................!13!

1.6. Reference!...............................................................................................................!17!

Chapter 2 Microencapsulated Photoluminescent Gold for ppb-level Chromium(VI) Sensing ............................................................................................................................. 23!

2.1. Introduction!............................................................................................................!23!

2.2. Experimental!..........................................................................................................!26!

2.2.1. Materials!..........................................................................................................!26!

2.2.2. Synthesis of Luminescent Glutathione-capped Gold Nanoclusters (GSH-Au NCs)!..........................................................................................................................!27!

2.2.3. Synthesis of Luminescent GSH-Au NC-containing Microcapsules (Au-MCs)!...................................................................................................................................!28!

2.2.4. Characterization!...............................................................................................!28!

2.2.5. Quantum Yield (QY) Measurements!...............................................................!29!

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2.2.6. Cr(VI) Sensing Studies!....................................................................................!30!

2.2.7. Synthesis of RBITC-conjugated PAH!.............................................................!32!

2.2.8. Test Strip Study!...............................................................................................!32!

2.3. Results and Discussion!...........................................................................................!32!

2.3.1. Characterization of GSH-Au NCs!...................................................................!32!

2.3.2. Encapsulation of GSH-Au NCs!.......................................................................!33!

2.3.3. Photoluminescence enhancement of Au-MCs!.................................................!38!

2.3.4. Sensitivity of GSH-Au NCs to Different Ions!.................................................!40!

2.3.5. Sensitivity of GSH-Au NCs and Au-MCs to Cr(VI) at different concentrations!...................................................................................................................................!42!

2.3.6. Indirect evidence for low pH inside the microcapsules!...................................!46!

2.3.7. Cr(VI) strip-based sensor using Au-MCs!........................................................!47!

2.4. Conclusions!............................................................................................................!48!

2.5. Supplementary Information!...................................................................................!49!

2.5.1. Synthesis of RBITC!.........................................................................................!50!

2.5.2. Synthesis and testing of RBITC-PAH MCs!....................................................!51!

2.5.3. Characterization of GSH-Au NCs!...................................................................!52!

2.5.4. Estimating Au content of Au-MCs!..................................................................!53!

2.6. Reference!...............................................................................................................!60!

Chapter 3 Treating Water by Degrading Oxyanions Using Metallic Nanostructures........................................................................................................................................... 66!

3.1. Introduction!............................................................................................................!66!

3.1.1. Sustainability of water!.....................................................................................!66!

3.1.2. Toxic oxyanion contamination!........................................................................!67!

3.1.3. Metallic nanostructure based catalytic water treatment as a sustainable process!...................................................................................................................................!70!

3.2. Catalytic Detoxification of Oxyanions Using Metallic Nanostructures!.................!72!

3.2.1. Nitrogen oxyanions!.........................................................................................!73!

3.2.1.1. Occurrence and health effects!...................................................................!73!3.2.1.2. Current technology!....................................................................................!73!3.2.1.3. Catalytic chemistry!...................................................................................!74!3.2.1.4. Assessment of technology readiness!.........................................................!81!

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3.2.2. Chromium Oxyanions!.....................................................................................!82!

3.2.2.1. Occurrence and health effects!...................................................................!82!3.2.2.2. Current technologies!.................................................................................!82!3.2.2.3. Catalytic chemistry!...................................................................................!83!3.2.2.4. Assessment of technology readiness!.........................................................!86!

3.2.3. Halogen oxyanions!..........................................................................................!86!

3.2.3.1. Occurrence and health effects!...................................................................!86!3.2.3.2. Current technologies!.................................................................................!87!3.2.3.3. Catalytic chemistry for bromine oxyanion!................................................!88!3.2.3.4. Catalytic chemistry for chlorine oxyanions!..............................................!90!3.2.3.5. Assessment of the technology readiness!...................................................!91!

3.3. Perspective and Research Opportunities!................................................................!92!

3.3.1. Comparison of reduction catalytic activity for the different oxyanions!...........!92!

3.3.2. Applicability of catalytic remediation to other oxyanions!...............................!93!

3.3.3. Possible catalytic water treatment scenarios using metallic nanostructures!....!94!

3.3.4. Roadmap for deployment of catalysts for oxyanion treatments!.......................!95!

3.3.5. Practical implementation issues of catalytic water treatment!..........................!95!

3.4. Conclusions!............................................................................................................!97!

3.5. References!..............................................................................................................!97!

Chapter 4 PdAu-catalyzed Oxidation through in situ Generated H2O2 in Simulated Produced Water ............................................................................................................ 115!

4.1. Introduction!..........................................................................................................!115!

4.2. Experimental!........................................................................................................!118!

4.2.1. Materials!........................................................................................................!118!

4.2.2. Catalyst preparation and characterization!......................................................!119!

4.2.3. H2O2 formation and detection!........................................................................!119!

4.2.4. Detection of hydroxyl radicals!......................................................................!122!

4.2.5. Phenol degradation reaction!..........................................................................!123!

4.3. Results and discussion!.........................................................................................!124!

4.3.1. H2O2 and hydroxyl radical generation!...........................................................!124!

4.3.2. Phenol degradation!........................................................................................!130!

4.3.3. Effect of ferrous iron!.....................................................................................!134!

4.3.4. Effect of pH and salinity!................................................................................!135!

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4.4. Conclusion!...........................................................................................................!137!

4.5. Supplementary Information!.................................................................................!138!

4.6. Reference!.............................................................................................................!145!

Chapter 5 Room-temperature Catalytic Treatment of High-salinity Produced Water at Neutral pH ................................................................................................................. 150!

5.1. Introduction!..........................................................................................................!150!

5.2. Experimental!........................................................................................................!153!

5.2.1. Materials!........................................................................................................!153!


5.2.3. H2O2 formation in batch reactor!....................................................................!154!

5.2.4. Phenol degradation in batch reactor!..............................................................!156!

5.2.5. Quantification of nitrogen byproducts from HA oxidation!...........................!157!

5.2.6. Phenol degradation in recirculating trickle bed reactor (TBR)!......................!157!

5.2.7. Modeling of overall phenol degradation rate in recirculating TBR!...............!159!


5.3.1. H2O2 generation from HA oxidation in batch reactor!....................................!160!

5.3.2. Phenol degradation in batch reactor!..............................................................!163!

5.3.3. Effect of pH and salinity in batch reactor!......................................................!165!

5.3.4. HA oxidation byproduct detection!.................................................................!167!

5.3.5. Phenol degradation in circulated TBR!...........................................................!168!

5.4. Conclusion!...........................................................................................................!170!


5.6. Reference!.............................................................................................................!173!

Chapter 6 Towards Glucuronic Acid through Oxidation of Methyl-glucoside Using PdAu Catalysts .............................................................................................................. 177!

6.1. Introduction!..........................................................................................................!177!

6.2. Experimental!........................................................................................................!180!


6.2.2. Catalytic testing!.............................................................................................!180!


6.3.1. Catalyst structure!...........................................................................................!183!

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6.3.2. Effect of Pd surface coverage on catalyst activity of MG oxidation!.............!184!

6.3.3. Effect of Pd surface coverage on MGA yield from MG oxidation!................!186!

6.4. Conclusion!...........................................................................................................!189!


6.5.1. Materials!........................................................................................................!189!

6.5.2. NP Synthesis!..................................................................................................!190!

6.5.3. Carbon-supported catalyst preparation!..........................................................!192!

6.5.4. Catalyst characterization!................................................................................!193!

6.5.4.1. Transmission electron microscopy (TEM)!..............................................!193!6.5.4.2. Inductively Couples Plasma Optical Emission Spectrometer (ICP-OES)!.............................................................................................................................!193!

6.6. Reference!.............................................................................................................!196!

Chapter 7 Recommendations for Future Work ......................................................... 200!

7.1. Recommendations for future work!.......................................................................!200!

7.1.1. Simultaneous sensing multiple contaminants using luminescent Au nanostructures!..........................................................................................................!200!

7.1.2. Improving the catalyst and reactor for on-site produced water cleanup!........!203!

7.1.3. Development of the simultaneous contaminants sensing and degradation systems!....................................................................................................................!205!

7.2. Reference!.............................................................................................................!206!

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List of Figures

Figure 1.1 Global freshwater use over long run and the percentage of freshwater used in different categories. ............................................................................................................. 2

Figure 1.2 Centralized water management systems including wastewater treatment and monitoring facility and the drinking water treatment and monitoring facility. .................. 3

Figure 1.3 Example of water quality test kit for various contaminants monitoring .......... 5

Figure 1.4 Example of a mobile oil and gas wastewater treatment unit operated on the production site to treat the produced water. ........................................................................ 7

Figure 1.5 An example of modular water treatment and monitoring system using multifunctional nanostructures. ........................................................................................... 8

Figure 1.6 Examples of the most common gold nanostructures. ..................................... 10

Figure 2.1 (a) SEM image of Au-MCs (containing 4.8 wt% Au). (b) Size histogram of Au-MCs based on 200 imaged particles. TEM images of (c) an individual Au-MC and (d) shell structure of the Au-MC with SiO2 NPs circled in red. ............................................. 36

Figure 2.2 Water suspensions of MCs that (a) contain and (b) not contain GSH-Au NCs. Dried MCs (c) containing and (d) not containing GSH-Au NCs, recovered after centrifugation and vacuum drying. Upper panels: visible light illumination. Lower panels: UV light illumination (at 365 nm). ................................................................................... 37

Figure 2.3 (a) Au-MC suspensions with increasing Au loading (0, 0.125×107, 0.25×107, 0.5×107, 1×107, 2×107, 3×107 Au NCs per microcapsule) (upper: visible light; (lower: UV illumination) MC concentration of ~108 capsules/mL. (b) Luminescence peak intensity (at 600 nm; excitation wavelength of 365 nm) as function of Au content. (c) Brightfield and confocal microscope images of Au-MCs (4.8 wt% Au). ........................................... 38

Figure 2.4 (a) Suspensions of GSH-Au NCs and Au-MCs under UV illumination (365 nm), and corresponding (b) photoemission (365 nm excitation) and (c) absorbance/photoextinction spectra. (overall Au concentration in vial for both suspensions = 0.03 mM on Au atom basis). ..................................................................... 39

Figure 2.5 Relative luminescence intensity (F/F0 at 600 nm, where F and F0 are the corresponding luminescence intensities at 600 nm with and without 20 µM tested ion) of the GSH-Au NCs (a) in acidified DI water (pH 1) and (b) in DI water (pH 7), and of (c) the Au-MCs in DI water (pH 7). Final Au atom concentration of 0.003 mM. ................. 40

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Figure 2.6 Luminescence ratio (F/F0) of (a) GSH-Au NCs and (b) Au-MCs versus Cr(VI) concentration, where F0 and F are the corresponding luminescence intensities at 600 nm (365 nm excitation) in the absence and presence of Cr(VI), respectively. Solution pH = 1 or 7 (or 7.5), Gold content = 3 µmol-Au atom per 1 L solution). ..................................... 43

Figure 2.7 Peak wavelength of UV-vis absorbance of RBITC-PAH (a) inside the MCs, and (b-d) in bulk solution at pH values of (b) 1-2, (c) pH 2-3, and (d) pH 3-9. ............... 47

Figure 2.8 Image of paper test strips with Au-MCs (0.19 µg Au per strip) (a) under visible light as it fabricated, and (b) under 365 nm UV illustration after dipping into simulated drinking water with different Cr(VI) concentrations and plot of the relative color intensity (I/I0) versus Cr(VI) concentration ............................................................. 48

Figure 3.1 Periodic table showing the most common oxyanion and cation species (marked by color) under drinking water conditions (pH 6.5~8.5, Eh 0.1~0.4 V). Thermodynamically stable oxyanions are peach-colored, kinetically stable oxyanions are in red, and cationic elements are in blue. .......................................................................... 68

Figure 3.2 Pourbaix diagram of (a) sulfur (modified from Vermeulen et al.[13]), (b) chlorine (modified from Radepont et al.[16]), and (c) iron (modified from Tolouei et al.[17]). The blue dashed lines indicate the water electrochemical potential window. .... 69

Figure 4.1 (a-c) TEM image (scale bar =50 nm) and (d-f) size distribution of alumina supported PdAu (a, d), Pd (b, e) and Au (c, f) NPs catalysts. Each bar represents percentage of NPs in the diameter range 0.5 nm. ........................................................... 125

Figure 4.2 Time profiles for (a) H2O2 concentrations, (b) H2O2 formation rates, and (c) formic acid conversion using PdAu, Pd, and Au catalysts. (d) H2O2 selectivity-formic acid conversion plot. Reaction conditions: 20 mg PdAu/Al2O3 or 20 mg Pd/Al2O3 or 200 mg Au/Al2O3, 23 °C, 100 mL, 0.2 M formic acid, 50 mL min-1 O2, and initial pH = 2. 126

Figure 4.3 (a, c, e) Phenol and catechol concentration profiles using (a) PdAu, (c) Pd and (e) Au catalysts; (b, d, f) formic acid and H2O2 concentration profiles using (b) PdAu, (d) Pd and (f) Au catalysts. Reaction conditions: 50 mg PdAu/Al2O3, or 50 mg Pd/Al2O3 or 200 mg PdAu/Al2O3, 23 °C, 100 mL, 0.2 M formic acid, 100 ppm phenol, 50 mL min-1 O2, and initial pH = 2. ..................................................................................................... 131

Figure 4.4 Phenol degradation reaction constant (on a g-metal basis) in PdAu, Pd, and Au catalytic systems with the presence of different concentration of ferrous iron. Reaction conditions: 20 mg PdAu/Al2O3 or 20 mg Pd/Al2O3 or 200 mg Au/Al2O3, 23 °C, 100 mL, 0.2 M formic acid, 100 ppm phenol, 0-10 ppm Fe(II), 50 mL min-1 O2, and initial pH = 2. .................................................................................................................. 135

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Figure 4.5 Initial phenol degradation reaction rate constant on a g-metal basis (kcat) in water ([TDS]~0 mg/L) (a) at different pH and (b) with different TDS concentrations (corresponding to 1×, 10×, 102×, 103×, 104×, 105×, and 106× dilutions of simulated HF-PW stock solution). Reaction conditions: 20 mg PdAu/Al2O3 or 20 mg Pd/Al2O3 or 200 mg Au/Al2O3, 23 °C, 100 mL, 0.2 M formic acid, 100 ppm phenol, 5 ppm Fe(II), 50 mL min-1 O2. .......................................................................................................................... 136

Figure 5.1 Time profiles for (a) H2O2 and (b) HA concentrations, and (c) H2O2 selectivity-HA conversion plots for PdAu, Pd, and Au catalysts. Reaction conditions: 20 mg PdAu/Al2O3 or 20 mg Pd/Al2O3 or 200 mg Au/Al2O3, 23 °C, 100 mL, 10 mM HA, 50 mL min-1 O2, and initial pH = 9.0. .................................................................................. 161

Figure 5.2 Time profiles for (a) phenol (solid lines) and TOC (dashed lines), (b) HA, and (c) H2O2 concentration using PdAu, Pd, and Au catalysts. Reaction conditions: 20 mg PdAu/Al2O3, or 20 mg Pd/Al2O3 or 200 mg PdAu/Al2O3, 23 °C, 100 mL, 10 mM HA, 100 ppm phenol (~1.06 mM), 50 mL min-1 O2, and initial pH = 9. ................................ 163

Figure 5.3 Initial phenol degradation reaction rate constant on a g-metal basis (kcat) (a) in DI water ([Cl-] ~ 0 mg/L) at pH 5-8 buffered by phosphate, and (b) in water with chloride concentrations of 0, 3, 30, 300, 3000 mM (or 0, 100, 1000, 10000, 100000 ppm) buffered at pH 7. Reaction conditions: 20 mg PdAu/Al2O3 or 20 mg Pd/Al2O3 or 200 mg Au/Al2O3, 23 °C, 100 mL, 10 mM HA, 100 ppm phenol, 8 mM phosphate, 50 mL min-1 O2. ................................................................................................................................... 166

Figure 5.4 HA, NO2- and NO3

- concentration profiles using (a) PdAu, (b) Pd and (c) Au catalysts during phenol oxidation. Reaction conditions: 20 mg PdAu/Al2O3 or 20 mg Pd/Al2O3 or 200 mg Au/Al2O3, 23 °C, 100 mL, 10 mM HA, 100 ppm phenol, 8 mM phosphate, 50 mL min-1 O2, and pH ~ 7. ........................................................................ 167

Figure 5.5 Experimental (dots) and modeled (curves) phenol degradation profiles in recirculating TBR in DI water and simulated HFPW. Solid curve and dash curve indicate semi-batch reactor model without (Eqn 1) and with (Eqn 2) considering performance decay, respectively. Reaction condition: 250 g Pd/Al2O3, 23 °C, 100 ppm phenol, 8 mM phosphate, pH~7, 12 L min-1 air. .................................................................................... 169

Figure 6.1 (a) Concentration-time profiles for 0, 30, 50 and 80 sc% Pd-on-Au/C catalysts and (b) concentration-time profiles for 80, 100, 150, 300 sc% Pd-on-Au/C and Pd/C (both synthesized and purchased) catalysts. Reaction conditions: 50 °C, 50 mL, 0.1 M MG, 0.4 M NaOH, pH = 13, and 100 mL min-1 O2. ..................................................................... 185

Figure 6.2 Plot of initial TOF with Pd surface coverage. Reaction conditions: 50 °C, 50 mL, 0.1 M MG, 0.4 M NaOH, pH = 13, and 100 mL min-1 O2. ..................................... 186

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Figure 6.3 Reaction products and carbon balance of MG oxidation using 80 sc% Pd-on-Au/C catalyst. Reaction conditions: 50 °C, 50 mL, 0.1 M MG, 0.4 M NaOH, pH = 13, and 100 mL min-1 O2. ...................................................................................................... 187

Figure 6.4 Plot of MGA yields (at the end of the 8-hr reaction) with Pd surface coverage (black squares). Glucuronic acid yield from glucose oxidation using 80 sc% Pd-on-Au NPs (blue cross). Reaction conditions: 50 °C, 50 mL, 0.1 M MG (or glucose), 0.4 M NaOH, pH =13, and 100 mL min-1 O2. ........................................................................... 188

Figure 7.1 (a) Fluorescence intensity spectra of BSA-Au NCs for different concentrations of Pb2+ at pH ~7. (b) Fluorescence quenching as a function of Pb2+ concentration in water at pH ~7. F denotes the fluorescence intensity at a certain amount of Pb2+ present, while F0 represents the original fluorescence of BSA-Au NCs with no Pb in the water sample. ........................................................................................................ 202

Figure 7.2 Effect of 10 !M of chloride metals on the fluorescence of 2 !M of BSA-AuNCs at a neutral pH. ................................................................................................... 202

Figure 7.3 Plot of initial H2O2 productivity with Pd surface coverage. Reaction conditions: 23 °C, 50 mL, 10 mM hydroxylamine, pH = 9, and 50 mL min-1 O2. ......... 204

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List of Tables

Table 2.1 Comparison of KSV and LOD for GSH-Au NCs and Au-MCs. ....................... 43

Table 3.1 Concentration level and health effect of common toxic oxyanions ................. 71

Table 3.2 Performance of metallic nanostructures in the catalytic reduction of nitrite ... 77

Table 3.3 Performance of metallic nanostructures in the catalytic reduction of nitrate ... 80

Table 3.4 Performance of metallic nanostructures in the catalytic reduction of chromate........................................................................................................................................... 85

Table 3.5 Performance of metallic nanostructures in the catalytic reduction of bromate 89

Table 3.6 Performance of metallic nanostructures in the catalytic reduction of perchlorate........................................................................................................................................... 90

Table 4.1 Initial H2O2 formation rate, initial formic acid reaction constant and zero-conversion H2O2 selectivity of PdAu, Pd, and Au catalysts. .......................................... 127

Table 4.2 Initial phenol degradation reaction constant, initial formic acid decomposition reaction constant and formic acid utilization efficiency of PdAu, Pd, and Au catalysts. 133

Table 5.1 Catalyst pellet characteristics ......................................................................... 158

Table 5.2 Initial H2O2 formation rate, initial HA reaction constant and zero-conversion H2O2 selectivity for PdAu, Pd, and Au catalysts. ........................................................... 161

Table 5.3 Initial phenol degradation reaction constant, initial HA reaction constant and zero-conversion H2O2 selectivity for PdAu, Pd, and Au catalysts. ................................ 164

Table 5.4 NO2-/NO3

- byproduct selectivity from HA oxidation in phenol degradation experiments at different Cl- concentrations of 0, 3, 30, and 300, mM (or 0, 10, 100, 1000 ppm). ............................................................................................................................... 168

Table 5.5 Fitted phenol degradation reaction rate constants at DI water and simulated HFPW conditions using semi-batch reactor model ........................................................ 170

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List of Scheme

Scheme 2.1 Formation of charged-assembled microcapsules (MCs) that (a) contain and (b) not contain the luminescent GSH-Au NCs. ................................................................ 35

Scheme 3.1 Reduction reaction of nitrite and nitrate, to nitrogen gas and ammonia with corresponding standard Gibbs free energy values (25 °C, 1 atm, 1 M reactant concentrations, pH 0) ........................................................................................................ 75

Scheme 3.2 Nitrite catalytic reduction pathway on Pd surface with hydrogen gas as a reducing agent (modified from Martínez et al.[68]). The DFT calculated pathway is kinetically unlikely to occur. ............................................................................................. 76

Scheme 3.3 Nitrate catalytic reaction pathway to nitrite on Pd surface with M (Cu, Sn, or In) as a secondary metal promoter and hydrogen gas as a reducing agent (modified from Guo et al.[36]) ................................................................................................................... 79

Scheme 3.4 Formic acid (HCOOH) decomposition to hydrogen and carbon dioxide, reduction reaction of chromium oxyanion, and formation of chromium hydroxide with their corresponding standard Gibbs free energy values (25 °C, 1 atm, 1 M reactant concentrations, pH 0) ........................................................................................................ 83

Scheme 3.5 Reduction reactions of bromate, chlorite, chlorate and perchlorate with the corresponding standard Gibbs free energy values (25 °C, 1 atm, 1 M reactant concentrations, pH 0) ........................................................................................................ 88

Scheme 3.6 Reduction reaction of arsenate/arsenite to arsenic metal, and selenate to selenium metal with corresponding standard Gibbs free energy values (25 °C, 1 atm, 1 M reactant concentrations, pH 0) .......................................................................................... 93

Scheme 3.7 Technology readiness level (TRL) for catalytic reduction of oxyanion contaminants. The colored boxes represent current and past activities in research and development. ..................................................................................................................... 95

Scheme 4.1 Proposed reaction mechanism of formic acid decomposition, surface •OH radical and H2O2 formation PdAu catalyst surfaces ....................................................... 130

Scheme 5.1 (a) Schematic of TBR operating in recirculating mode, and (b) corresponding semi-batch reactor model to account for phenol concentration changes in reservoir tank.......................................................................................................................................... 158

xix!!

Scheme 6.1 Direct synthesis of glucuronic acid via biocatalyzed glucose oxidation (red path), and indirect synthesis of glucuronic acid via metal-catalyzed MG oxidation (blue path). ............................................................................................................................... 180

Scheme 7.1 Example of paper-based multiple contaminants test strip. Different colors indicate different contaminants sensing areas with different Au NCs ............................ 201

!

!

Chapter 1

Background and Research Overview

1.1. Centralized versus decentralized water treatment and monitoring

systems

Fresh water is essential for human activities including household use, irrigation

for food production, industrial use, and for energy production. Currently around four

trillion cubic meter of water is consumed globally every year, among which 70% is for

agricultural use, 22% is for industrial use, 6% is for household use and 2% is as drinking

water. (Fig. 1.1) However, readily available fresh water only accounts for ~1% of the

total water on earth.[1] Ensuring a safe and sustainable water supply is critical for the

continuous and stable development of human society.

2!!

Figure 1.1 Global freshwater use over long run and the percentage of freshwater used in different categories. (Figure adapted from https://ourworldindata.org/water-use-stress)

Towards this goal, considerable effort has been put towards developing

technologies for water treatment and quality monitoring which can function at high

throughput. Modern examples include Centralized Water Treatment and Monitoring

(CWTM) facilities (Fig. 1.2), which are typically used to service urban areas.[2] CWTM

facilities treat and monitor millions of cubic meter water every day, providing clean water

for millions of people.

3!!

!

Figure 1.2 Centralized water management systems including wastewater treatment and monitoring facility and the drinking water treatment and monitoring facility. (Figure adapted from https://www.epa.ie/pubs/reports/water/wastewater/).

However, CWTM facilities have several key disadvantages.[3] CWTM facilities

are large, centralized treatment plants and thus are often unable to address the supply

needs for the people living in rural areas and/or developing regions. More than 800

million people live without the access to safe drinking water, and two million children

under the age of five die each year due to the lack of safe drinking water.[4] Similarly,

the prohibitively expensive infrastructure (e.g., piping, pumping) required to transport

wastewaters generated far from CWTM facilities also implies that out-of-network regions

not only have freshwater supply issues, but limited means of removing generated

wastewater. Third, CWTM facilities cannot be easily or affordably upgraded to increase

capacity or capabilities, thus CWTM facilities are unable to treat emerging classes of

wastewater, such as the produced water generated from hydraulic fracturing sites.[5]

4!!These limitations highlight the need for decentralized (distributed) water

treatment and/or monitoring (DWTM) systems, which can complement the disadvantages

of the centralized system. Two examples of the DWTM systems, point of use (POU)

drinking water monitoring and on-site hydraulic fracturing produced water treatment, are

highlighted below.

1.1.1. Point of use (POU) drinking water monitoring

Although water quality is carefully monitored at CWTM facilities, the water

quality at the residence of many users may change as a result of transportation through

the pipelines. Corrosion, bacteria contamination, or metal leaching from the pipeline can

contaminate water making it unsafe to use.[6] In a tragic recent example, lead leached

from water pipes into drinking water, exposed over 100,000 residents to elevated lead

levels in the city of Flint, MI in 2014.[7]

Water obtained from CWTM facilities is also greatly affected by the weather

conditions. Extreme weather conditions, such as hurricanes, may lower the treatment

capacity, which results in the poor household water quality.[8] In 2017, Hurricane

Harvey made landfall in southeast Texas, disrupting power and causing at least 45

CWTM facilities to shut down. This left hundreds of communities in southeast Texas

without safe drinking water.[9]

In the rural areas of some developing countries (e.g., Zambian, Bangladesh)

where CWTM facilities are not available, fresh water is primarily obtained from wells

and surface water.[10] The quality of these waters is often unknown and may have

negative impacts on human health.

5!!POU household water quality monitoring devices (e.g. test kits), an example of a

DWTM system, is a solution to ensure the household drinking water quality (Fig. 1.3).

Though there are several commercialized household devices available in the market, they

are often costly and have low sensitivity to contaminants. There is a global need for a

low-cost, sensitive and user-friendly portable device for water monitoring.[11] The

potential market in developing countries exceeds $20 million annually.[11]

!

Figure 1.3 Example of water quality test kit for various contaminants monitoring (Figure adapted from https://www.homedepot.com/p/Protect-Plus-Complete-Water-Analysis-Kit-13-Conditions-WFTST013/207134932)

1.1.2. On-site hydraulic fracturing produced water treatment and reuse

Oil and gas production using hydraulic fracturing requires the use of 2-6 million gallons

of fresh water per well and generates 0.5-4 million gallons of wastewater (i.e., produced

water) per well.[12,13] Since hydraulic fracturing sites are usually located in isolated

areas, the accessibility to CWTM facilities is often limited, and the cost of transportation

6!!

of produced water to a CWTM facility is often too high to be economical. [14]

Additionally, CWTM facilities are usually designed to treat far less contaminated

municipal wastewater [15] implying that traditional CWTM facilities may not have the

capacity to treat produced water effectively; the introduction of produced water may

overload the facilities and affect normal operations.

Therefore, there is a need for DWTM units that can be operated at oil and gas

production sites (Fig. 1.4). After on-site treatment, produced water can be reused for

other hydraulic fracturing operations, which may be both more economical and

sustainable.[16] Though there are some commercialized on-site treatment options such as

ozonation[17] and filtration[18], more effective technologies with lower operating cost

are desired. An ideal DWTM unit should be small-sized, effective, low-cost and generate

no additional waste streams.

7!!

!

Figure 1.4 Example of a mobile oil and gas wastewater treatment unit operated on the production site to treat the produced water. (Figure adapted from http://www.okcrich.com/contents.php?contents=m_mobilewater)

1.2. Nanostructures-enabled DWTM systems

Nanomaterials are promising candidates for the design of DWTM systems.[19] As the

name suggests, the size of a nanomaterial is small enough to enable a miniature DWTM

system. Nanomaterials with specific sizes and structures can exhibit various properties

(e.g., optical, catalytic, magnetic, electrochemical) that may be useful for DWTM

systems. For example, the optical property of some nanostructures may change when

interacting with contaminants in water.[20] These nanostructures can therefore be

implemented as sensors to detect the presence of certain contaminants. Their catalytic

properties accelerates chemical reactions occurring on the nanostructure surface, which

can convert harmful contaminants to non-toxic species.[21] Nanostructures may also

achieve better performance while using less material. A modular water treatment and

monitoring system using multifunctional nanostructures was proposed by National

8!!

Science Foundation (NSF) funded Nanosystems Engineering Research Center for

Nanotechnology-Enabled Water Treatment (NEWT) (Fig. 1.5).[22]

!

Figure 1.5 An example of modular water treatment and monitoring system using multifunctional nanostructures. (Scheme adapted from reference [22])

Sensors are a key component for DWTM systems. A sensor usually consists of

two parts: a receptor and a transducer.[11] The receptor is a material that changes its

property (e.g., optical, electrochemical, magnetic) when interacting with a specific

analyte. Transducers transform the property change into a quantifiable signal, which is

usually electrically processable for ease of measurement. Nanomaterials (e.g., noble

metallic nanostructures[23], quantum dots[24], carbon-based nanomaterial[25]) are good

candidates as sensing receptors due to their structures allowing interaction with specific

contaminants to generate signals. Nanostructure-enabled sensors have been studied to

detect a variety of contaminants including inorganics (oxyanions[26], heavy metals[27]),

organics (pesticides[28], personal care products) and pathogens (bacterial, viruses)[29].

Indeed, nanomaterials provide opportunities to design sensors for detecting and

quantifying water contaminants with low cost, high sensitivity and high specificity.

9!!Nanostructures are also promising for their ability to remove contaminants from

water.[30] Nanostructures with large surface area to volume ratio (e.g. nano-magnetite)

can be used as adsorbents for trapping and separating contaminants. Some nanostructures

with catalytic and/or photocatalytic properties (e.g. nano-sized titania, noble metallic

nanoparticles, nanoscale zero-valent iron) can be used for oxidative or reductive

degradation of various contaminants including organic and inorganic compounds.

Gold-based nanostructures are one of the most investigated nanomaterials since

they are easy to synthesize, biocompatible, have functionalizable surfaces, and have

distinct structure-dependent physiochemical properties. The gold nanostructures used as

sensing and catalytic materials for contaminant monitoring and degradation is discussed

in detail in the following sections.

1.3. Gold nanostructures as sensing materials

Gold nanostructures refer to gold materials with nanometer-scale sizes and with well-

defined morphology, composition and surface structures.[31] Some common examples

are gold nanoparticles (Au NPs), gold nanoclusters (Au NCs), gold nanorods (Au NRs),

and gold nanoshells (Au NSs) (Fig. 1.6).[32] Gold nanostructures usually exhibit unique

optical, electrochemical and catalytic properties, which strongly depend on their physical

structures and can be changed by altering their structures. This distinct feature makes

gold nanostructures a promising material as a sensing element. Extensive research on

using gold nanostructures for sensing chemical and biological species such as metal ions,

small organics, proteins, cells and microorganisms has been conducted for over twenty

years, which has been highlighted by several review articles.[33–37]

10!!

!

Figure 1.6 Examples of the most common gold nanostructures. (Scheme adapted from reference [32])

1.3.1. Luminescent gold nanoclusters

Gold nanostructures with particle sizes smaller than two nanometers are typically called

gold nanoclusters (Au NCs).[38] The number of gold atoms in one Au NC varies from a

few atoms to ~100 atoms. Since Au NCs are usually stabilized by encapsulation in

polymer matrix (e.g. dendrimers) or by surface ligands (e.g. thiolates or proteins), the

terminology of “Au NCs” refers to the entire ensemble consisting of gold atoms and

stabilizers. The Au NCs exhibit different properties compared with Au NPs larger than 2

nm due to their small size and special structures. Rather than having surface plasmon

resonance (SPR), the Au NCs exhibit photoluminescent properties, which are attributed

to a combination of quantum confinement effect[39] and the electron transfer between

gold and the surface ligands.[40] Luminescence will disappear (or “quench”) if either the

structure of the Au NC or the ligands is damaged. This “luminescence quenching”

phenomenon of Au NCs can therefore be used for sensing.

11!!

1.3.2. Au NCs for water contaminant sensing

One popular application using luminescent Au NC is environmental analysis.[41]

Luminescent Au NCs provide highly sensitive and specific responses to detect water

contaminants at low concentrations (several ppb or ppm level) and in complex water

matrices.[42] By far, luminescent Au NCs research has been focused on heavy metals

(e.g., Cu2+, Hg+, Cd2+) and inorganic anions (e.g., NO3-, NO2-, CN-). Sensing organics

(organohalides, pesticides, personal care products) and organisms (e.g., bacteria, viruses)

water contaminants using Au NCs are relative less explored. [43,44] Multiple review

articles have summarized recent developments on luminescent Au NCs for sensing

applications.[41,45] However, low luminescence intensity limits the practical

applications of Au NCs.[46] There is a need to enhance the luminescence and improve

the sensitivity for contaminants at low concentration, especially as environmental

regulations are getting stricter. Engineered Au NCs with improved sensitivity are thus

desired to design an effective point-of-use water quality monitoring system as a part of a

DWTM system.

1.4. Gold-based nanostructures as catalytic materials

Although the use of gold materials for decorative purpose can be dated back to the fourth

century A.D., the use of gold for catalytic applications is much more recent.[47] Gold

was believed to be catalytically inactive due to its non-oxidizable appearance in bulk

phase. In the late 1980s, the findings of gold catalysis for CO oxidation by Haruta[48]

and ethylene hydrochlorination by Hutchings[49] precipitated extensive research on gold

12!!

as a catalytic material for different chemical reactions, such as alcohol oxidation to

acids[50] and direct formation of hydrogen peroxide from H2 and O2.[51]

Gold can also be added to other metallic materials (e.g., Pd, Pt, Ru) to form a

bimetallic structure. Bimetallic structures can be core-shell, segregated, or mixed, which

depends on the physical properties of the two metals and the preparation methods.

Compared with the monometallic structures, the bimetallic structures typically showed

enhanced catalytic activity, selectivity to desired products, and/or higher stability due to

synergistic effects such as geometric effect, electronic effect and bifunctional effect.

1.4.1. Bimetallic PdAu catalysts

PdAu bimetallic nanoparticles are among the most investigated Au-based bimetallic

nanostructures. One reason is that PdAu usually show superior catalytic performance than

monometallic Pd or Au catalysts. Another reason is that Au is miscible with Pd at all

compositions, which allowing the design of PdAu with different structures to investigate

the structure-performance relationship. Though the nature of synergistic effect of PdAu is

still under debate, in most common cases, Au can increases deactivation resistance of Pd

by electronic effect, dilute the Pd atoms to create single Pd atom active site,[52,53] or

provide bifunctional sites for bonding of reactants to the surface.[54] PdAu bimetallic

catalysts for different reactions are summarized by Prati and co-workers.[55]

1.4.2. PdAu catalyst for water contaminant degradation

Though PdAu catalysts have been applied to various reactions for chemical synthesis

including the commercialized process for production of vinyl acetate monomer (VAM),

13!!

its application to water remediation is still emerging.[56] Most water remediation

reactions using PdAu catalysts are based on a reductive mechanism. For example, the

reduction of halogenated hydrocarbons (e.g. trichloroethylene[57,58],

perchloroethylene[59]), oxyanions (nitrite[60,61], nitrate[62]), and nitroarenes[63]. In

most cases, the Au behaves as a catalytic support with the active sites being the Pd

ensembles deposited on Au. Bimetallic PdAu showed significantly enhanced (>10 times)

catalytic activity in contaminant degradation reactions compared with pure Pd and Au.

PdAu was also found to be more resistant to catalyst poisoning agents such as chloride.

These findings suggested PdAu nanostructures can provide an effective and economical

approach for the design of DWTM systems. PdAu's use as a catalyst in oxidative

treatment of water contaminants is less explored, which presents opportunities for

researchers.

1.5. Research overview and thesis layout

The overall goal of this thesis is to address the challenges in the design of DTWM

systems. On the contaminant sensing side, luminescent Au NCs are promising materials

for POU household contaminant sensors. However, the challenge remains to improve the

sensitivity to detect trace amounts of contaminants. One of the contributions of this thesis

is that a novel Au material called luminescent Au microcapsules (Au MCs) were

engineered with enhanced sensitivity to a toxic water contaminant, hexavalent chromium

(Cr(VI)).

On the contaminant mitigation side, Au-based nanostructures as catalysts can be

used to design a mobile catalytic converter unit, which enables on-site cleanup of

14!!

produced water. The challenge is to find a robust and low-cost catalytic process that

remains effective in high salinity conditions. In this thesis, bimetallic PdAu nanoparticles

were found to be a robust catalyst that can degrade organics in produced water and is

resistant to high salinity compared with monometallic Pd and Au. The catalytic unit

based on PdAu catalyst, air, and/or cheap additive can potentially be a cost-effective

approach for on-site produced water treatment.

Chapter 2 discusses the development of novel Au-based composite materials,

named luminescent Au microcapsules (Au MCs), as ultra sensitive probe for contaminant

detection and quantification, and served as a platform to design an affordable and

effective POU contaminant sensor. Au microcapsules were synthesized by inducing

glutathione-capped Au NCs to aggregate within silica-coated microcapsule structures via

polymer–salt aggregate self-assembly chemistry. The Au MCs have a 5× luminescence

enhancement compared to free Au NCs and can detect Cr(VI) at concentrations as low as

6 ppb through luminescence quenching, compared to free Au NCs which have a limit of

detection (LOD) of 52 ppb. The LOD is 16× lower than the United States Environmental

Protection Agency maximum contaminant level of 100 ppb for total chromium in

drinking water. The luminescent microcapsule material can sense Cr(VI) in simulated

drinking water with a ∼20–30 ppb LOD, serving as a possible basis for a practical Cr(VI)

sensor. This work has been published as: Y.B. Yin, C.L. Coonrod, K.N. Heck, and M.S.

Wong, “Microencapsulated Photoluminescent Gold for ppb-level Chromium(VI)

Sensing”, ACS Applied Material & Interface, 2019, 11, 19, 17491-17500.[64]

Chapter 3 describes the recent progresses in the usage of noble metallic

nanostructures (e.g. Au, Pd, Pt) for contaminant cleanup of drinking water sources. Toxic

15!!

oxyanions of nitrogen (NO2-, NO3

-), chromium (CrO42-), chlorine (ClO2

-, ClO3-, ClO4

-),

and bromine (BrO3-) were used as contaminant examples. An assessment of practical

implementation issues, and additional opportunities for metal nanostructures to contribute

to improved quality and sustainability of water resources were provided.!This work has

been published as: Y.B. Yin, S. Guo, K.N. Heck, C.A. Clark, C.L. Coonrod, and M.S.

Wong, “Treating Water by Degrading Oxyanions Using Metallic Nanostructures”, ACS

Sustainable Chemistry & Engineering, 2018, 6, 9, 11160-11175.[26]

Chapter 4 studied the ability of alumina-supported bimetallic PdAu to degrade

organic compounds at room temperature and atmospheric pressure via the catalytic

formation of H2O2. PdAu catalyst produced H2O2 and hydroxyl radicals in the presence

of oxygen and formic acid. The bimetallic catalyst was the most active in terms of initial

•OH formation rate, and when phenol was present, PdAu showed the highest rate of

phenol degradation. We assessed the promotional and inhibitory effects of other species

present in produced water including ferrous ion concentration, pH, and salt concentration

on catalytic phenol oxidation. PdAu was catalytically active for phenol degradation in

simulated produced water at salinities as high as ~0.3"M (~16,000"ppm). The combination

of air-formic acid-bimetallic catalyst is an intriguing approach for the degradation of

organics in contaminated water at low pH and moderate salinity. This work has been

published as: Y.B. Yin, K.N. Heck, C.L. Coonrod, C.D. Powell, S. Guo, M.A. Reynolds,

and M.S. Wong, “In-situ PdAu Catalytic Oxidation of Organic Compounds in Simulated

Produced Water”, Catalysis Today, 2020, 339, 362-370.[65]

Chapter 5 reports an approach to overcome the limitations of the previous study

that was restricted to acidic pH conditions and intolerant to high concentrations of total

16!!

dissolved solids (TDS). The new approach generated H2O2 in-situ through the oxidation

of a low-cost additive, hydroxylamine, over PdAu catalyst. This improved system

successfully degraded a model organic compound (phenol) in simulated HFPW with a

TDS of ~149,000 ppm at neutral pH. Furthermore, the bimetallic PdAu catalyst

demonstrated superior activity in high TDS (>100,000 ppm) waters and a lower

formation rate of undesired byproducts (e.g., NO2- and NO3

-) compared to monometallic

Pd and Au. As proof of concept, a circulating trickle bed reactor (TBR) was constructed

which could reduce the organic load of model HFPW by ~50% in 48 hrs.

Chapter 6 highlights the work done at the beginning of my graduate research,

which is not as relevant to the field of water monitoring and remediation but is just as

important in advancing science. This work investigated the structure and performance of

the bimetallic PdAu catalyst using a biomass oxidation model reaction, which provided a

way to optimize the structure of PdAu catalysts used in the produced water treatment

study. We studied the oxidation of methoxy-protected glucose (MG) using Pd-on-Au

nanoparticle model catalysts to generate methoxy-protected glucuronic acid (MGA), a

precursor to glucuronic acid. Pd-on-Au showed volcano-shape activity dependence on

calculated Pd surface coverage (sc). The 80 sc% Pd-on-Au catalyst composition showed

maximum initial turnover frequency (413 mol-MG mol-surface-atom-1 h-1) that was 5×

higher than that of Au/C, while Pd/C was inactive. This Pd-on-Au composition gave the

highest MGA yield (46%), supporting a bimetallic approach to glucuronic acid

production. This work has been submitted as: Y.B. Yin, L. Chen, K.N. Heck, Z.C. Zhang,

and M.S. Wong, “Indirect Oxidation of Glucose to Glucuronic Acid Using Pd-decorated

Au Catalysts”, Catalysis Communication, 2019, in revision.

17!!Chapter 7 proposes several directions for future work. The selective sensing of

other contaminants using luminescent Au-based nanostructures will provide a way to

design a sensor with the capacity to detect multiple contaminants simultaneously. The

continued investigations to tune the structure of PdAu to find better PdAu catalysts for

produced water on-site treatment are noted. Other non-metal nanostructures can also be a

direction to find the cost-effective method for design of DWTM system.

1.6. Reference

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23!!

Chapter 2

Microencapsulated Photoluminescent Gold for ppb-level Chromium(VI) Sensing

2.1. Introduction

Luminescent gold nanoclusters (Au NCs) have emerged as a promising material for

sensing due to their inherent luminescent properties, ultrafine size (< 2 nm), high

photostability, good biocompatibility, and ease of synthesis[1–3]. They have been

investigated as a probe for the detection of hazardous heavy metal ions such as

mercury[4], copper[5] and hexavalent chromium[6].

Although it is commonly used in metallurgy, pigment manufacturing and wood

treatment processes[7], hexavalent chromium has cytotoxic and carcinogenic

properties.[8] The United States Environmental Protection Agency (US EPA) set the

maximum contaminant level (MCL) of total chromium (= Cr(III) + Cr(VI)) to 100 ppb

for drinking water. Certain U.S. states have more stringent regulations; California, for

24!!

example, has a MCL of 50 ppb for total chromium.[9,10] The World Health Organization

(WHO) provides a drinking water guideline value of 50 ppb for Cr(VI).[11] The Ministry

of Environmental Protection in China set the legal limit of Cr(VI) in drinking water to 50

ppb,[12] and the industrial waste water discharge limit to 100 ppb[13]

The US EPA provides two protocols for Cr(VI) detection in drinking water,

groundwater, and wastewater. Methods 218.6 and 218.7 have respective limits of

detection (LOD) of 0.3 ppb and 0.0044 ppb, with the latter one most recently published in

2011. For both protocols, an aqueous sample containing Cr(VI) is filtered (0.45 µm),

treated with a base, and then passed through an ion chromatography column. The

recovered Cr(VI) is reacted with diphenylcarbazide to form a pink colored complex,

which can be detected using a UV detector (at 530 nm). These methods are highly

sensitive and accurate, but are not appropriate for household use; they involve the use of

expensive instrumentation, chemical treatment steps, and a basic competency with

advanced chemical techniques. A portable test kit for Cr(VI) based on diphenylcarbazide

chemistry is commercially available,[14] but it has a LOD of 100 ppb, which is

inconveniently close to the 100-ppb MCL for total Cr. A rapid, easy-to-use, sensitive

(<100 ppb), and inexpensive method for selective Cr(VI) detection is highly desired for

household use.

Luminescent Au NCs could be the basis of such a method, but practical

implementation has not been demonstrated yet. Sun et al. reported the synthesis of 11-

mercaptoundecanoic acid-capped gold nanoclusters (MUA-Au NCs) with a QY of 2.4%.

Finding that Cr(III), but not Cr(VI), quenched the luminescence at pH 7, they chemically

reduced Cr(VI) using ascorbic acid to Cr(III), for quantification; a Cr(VI) LOD was not

25!!

reported.[6] Zhang et al. reported the synthesis of glutathione-capped gold nanoclusters

(GSH-Au NCs) with a QY of 1.5%. Under acidic conditions, they reported a LOD value

of 0.5 ppb (0.0096 µM as CrO42-).[15] Guo et al. reported the synthesis of bovine serum

albumin-capped gold nanoclusters (BSA-Au NCs) that had a LOD value of 0.03 ppb (0.6

nM as CrO42-) at pH 1.[16] Low pH values are necessary for Cr(VI)-induced

luminescence quenching. Selectivity for Cr(VI) can be introduced into the system by

using ethylenediaminetetraacetic acid as a masking agent to sequester other metal

ions.[15]

The photoluminescence of Au NCs can come from fluorescence or

phosphorescence depending on the composition.[17] The origin of Au NC fluorescence is

generally attributed to the quantum confinement of the metallic core or/and the charge

transfer of the surface ligands.[18–20] The fluorescence of Au NC is generally too low

(QY<1%) to be practically used. Xie and coworkers reported one Au NC composition

with to be phosphorescent based on lifetime measurements (with a QY OF 15%).[21]

They attributed the luminescence to aggregation-induced emission (AIE): non-

luminescent Au(I)-thiolate complexes, when localized into a shell around a Au(0) metal

core, became luminescent as a result of increased inter-Au(I) interactions.[22] Yahia-

Ammar et al. showed that Au NC luminescence could be increased by aggregating Au

NCs within a poly(allylamine hydrochloride) gel network, with the QY reportedly

increasing from 7% to 25%.[23]

In this study, we synthesized luminescent glutathione-capped gold nanoclusters

(GSH-Au NCs) and entrapped them inside micron-sized capsules (Au-MCs). The capsule

formation process is based on polymer-salt assembly (PSA), in which polyamines and

26!!

polyvalent anions combine to form polymer-salt aggregates around which charged

nanoparticles deposit to form a multilayer-thick, semipermeable shell.[24–28] The

encapsulation step occurs when the cargo is introduced to the polymer-salt aggregates

and before shell formation is initiated. We hypothesized that confining the GSH-Au NCs

within a polymer-salt matrix would increase luminescence, and that a shell of SiO2

nanoparticles would allow Cr(VI) to diffuse through and interact with the encapsulated

GSH-Au NCs. We indeed found the Au MCs were more luminescent than GSH-Au NCs,

due to light scattering of the emitted color caused by the microcapsular particles (0.9±0.2

µm). We quantified the Cr(VI) LOD in deionized water and in simulated drinking water

to be less than 100-ppb MCL for total Cr. We found that Cr(VI) in neutral-pH water

surprisingly induced luminescence quenching, suggesting the capsule interior contains a

low-pH environment, which we confirmed by synthesizing pH-sensitive MCs. Finally,

we demonstrated a user-friendly Cr(VI) strip test with ppb sensitivity, using Au MCs

deposited onto paper.

2.2. Experimental

2.2.1. Materials

Reduced L-glutathione ("GSH", molecular weight of 307 g/mol), hydrogen

tetrachloroaurate trihydrate (HAuCl4•3H2O), LiCl, NaCl, KCl, MgCl2, CaCl2, BaCl2,

CrCl3, MnCl2, FeCl2, FeCl3, CoCl2, NiCl2, CuCl2, ZnCl2, AlCl3, CdCl2, PbCl2, K2CrO4,

K2MnO4, Na2SO4, NaNO3, NaNO2, Na2CO3 and NaHCO3 were purchased from Sigma-

Aldrich. Poly(allylamine hydrochloride) ("PAH", ~70,000 g/mol) was purchased from

Alfa Aesar. Polyethyleneimine (PEI, ~750,000 g/mol) was purchased as a 50 w/v%

27!!

solution from Sigma. Disodium hydrogen phosphate heptahydrate (Na2HPO4·7H2O), and

disodium citrate dihydrate (Na2CIT•2H2O) were purchased from EMD Chemicals. Stock

solutions of all polymer and sodium salts were prepared using deionized water (Milli-Q)

with a resistivity of 18.2 MΩ, and stored at 4 °C before use. Silicon oxide NPs (~13 nm)

were available as an aqueous colloidal suspension (20.5 wt%, pH = 3.4, Snowtex-ST-O,

Nissan Chemicals). All purchased chemicals in this study were used without further

purification. Filter media (Disruptor, Grade 4601) comprised of a blend of alumina (in

the form of pseudoboehmite or AlO(OH)), glass fiber, and cellulose was provided by

Ahlstrom Corporation. For the conjugation of PAH to a dye compound, rhodamine B

isothiocyanate (RBITC) was purchased from Sigma-Aldrich.

2.2.2. Synthesis of Luminescent Glutathione-capped Gold Nanoclusters (GSH-Au

NCs)

An aqueous solution of HAuCl4 (20 mM, 5 mL) was added into 43.5 mL of deionized

water in a 100 mL single neck round bottom flask and stirred with magnetic stirring at

room temperature (~23 °C). GSH solution (100 mM, 1.5 mL) was then added into the

solution.[21] The flask with the reaction mixture was sealed with a glass stopper and

heated in a 70 °C oil bath under gentle stirring (~500 rpm) for 24 h. The synthesized

product was loaded into a dialysis bag (molecular weight cut-off of 3.5 kDa) and placed

in 2 L deionized water for 24 h to remove any unreacted precursors. The GSH-Au NC sol

(2 mM on gold atom basis and 0.056 mM on Au36SG32 particle basis) was stored in a

Duran laboratory bottle at 4 °C until use. The bottle was covered in aluminum foil to

shield the sample from ambient light.

28!!

2.2.3. Synthesis of Luminescent GSH-Au NC-containing Microcapsules (Au-MCs)

Luminescent GSH-Au NCs were encapsulated using polyamine-salt aggregate (PSA)

assembly chemistry.[27,28] A volume (0.5 mL) of cooled PAH solution (4 °C, 2 mg/mL,

pH = 4.3) was combined with 3-mL of cooled Na2HPO4 solution (4 °C, 0.01 M, pH =

7.4) for 10 s with a vortex mixer (speed 5 from 1-10), and the resulting suspension was

aged at 4 °C for 10 min. The ratio of total negative charge of added Na2HPO4 to the total

positive charge of the PAH, or the R ratio, was controlled as 6. The NC sol (0.5 mL) at a

given gold concentration (up to 2 mM on a Au atom basis) was then added, vortex mixed

for 10 s, and aged for an additional 10 min at 4 °C. Finally, a SiO2 NP sol (diluted to 7 wt

%, 1.5 mL) was added and vortex-mixed for 10 s. The synthesis of Au-MCs using two

different polymer types (PAH or PEI), two salt linkers (Na2HPO4 or Na2CIT) and R

ratios (3 or 6) were also investigated.

The resulting material (herein termed "Au-MCs" for gold-containing

microcapsules) was aged for an additional 2 h at 4 °C, washed twice with a deionized

water rinse and centrifugation (3000 rpm for 20 min), redispersed in deionized water

(final volume of 5.5 mL), and stored in the dark at 4 °C until use. The luminescence of

the supernatant was analyzed after centrifugation of the Au-MCs to ensure that all the

GSH-Au NCs were encapsulated. As a control sample, MCs without GSH-Au NCs were

synthesized using 0.5 mL DI water (instead of 0.5 mL of the Au NC sol).

2.2.4. Characterization

UV-vis absorbance spectra (or extinction spectra, for Au MC suspensions) were recorded

on a Shimadzu UV 2401 spectrophotometer. Photoluminescence (PL) spectra were

29!!

recorded on a Jobin-Yvon-Horiba photoluminescence spectrometer (FluoroMax 3). Zeta

potential values were measured through phase analysis light scattering (PALS) with a

Brookhaven ZetaPALS instrument. A dip-in electrode system with a 4-mL polystyrene

cuvette was used, and measurements were taken at 25 °C. Transmission electron

microscopy (TEM) images were taken using a JEOL JEM 2010 microscope with an

operating voltage of 200 kV. Scanning electron microscopy (SEM) images were

performed with FEI Helios SEM operating at 10 kV with a working distance of 10.0 mm.

The MCs were loaded on a SEM specimen stub, and dried under air overnight before

SEM imaging. Laser-scanning confocal microscopy was performed on a Carl Zeiss LSM

710 microscope (laser excitation of 405 nm). Samples were mounted on a glass slide and

sealed under a cover slip to prevent drying.

2.2.5. Quantum Yield (QY) Measurements

The QY of GSH-Au NCs was calculated, following International Union of Pure and

Applied Chemistry (IUPAC) methodology.[29] Fluorescein dissolved in 0.1 M NaOH

aqueous solution (QY = 95%) was used as a reference sample. For both GSH-Au NC and

reference samples at different concentrations, the absorbance at 365 nm and the

corresponding PL spectra (excitation wavelength of 365 nm) were recorded. The

absorbance was kept below 0.1 at the 365 nm excitation wavelength. The integrated

luminescence intensity versus absorbance was linearly fitted. The fitted gradients (slope

of luminescence intensity-absorbance line) of GSH-Au NCs sample and reference sample

were recorded. The QY of the test sample was determined with the formula below:

30!!

!" = !"!"#×!"#$!"#$!"#

× !!!"#

!

where the Grad is the gradient and η = the refractive index of the solvent.

The QY of Au MCs was determined using a method that accounted for light

scattering effects on UV-vis extinction spectra.[30] The experimental procedure was the

same as described above, except fluorescein combined with Au-MCs (at the same

suspension concentration as the Au-MCs) was used as the reference.

2.2.6. Cr(VI) Sensing Studies

Two stock solutions of Cr(VI) (0.01"M) were prepared by dissolving 19.4 mg K2CrO4 in

10 mL of either DI water or simulated drinking water. The simulated drinking water (pH

~ 7.5) comprises sodium (Na+, 3.86 mM) calcium (Ca2+, 1.0 mM) magnesium (Mg2+, 0.5

mM), bicarbonate (HCO3-, 3 mM), chloride (Cl-, 2 mM), sulfate (SO4

2-, 0.5 mM), nitrate

(NO3-, 0.14 mM), fluoride (F-, 0.053 mM), phosphate (PO4

3-, 0.0013 mM), and silica

(SiO2, 0.33 mM) (Table S2.1). This composition is used in the NSF/ANSI Standard 53

for water treatment system certification.[31] Cr(VI) solutions with various concentrations

were obtained by serial dilution of the stock solution.

A series of solutions with different Cr(VI) concentrations (up to 3120 ppb-Cr, or

60 µM-CrO42-) were prepared in separate vials. In testing GSH-Au NCs for Cr(VI)

sensitivity, the photoluminescence spectra of each sample solution (3 mL) were recorded

after addition of GSH-Au NC sol (5 µL), with and without 1 M HCl solution (to lower

pH to 1). In testing Au-MCs, spectra of each sample (3 mL) were similarly collected after

31!!

the addition of Au-MC suspension (50 µL), with and without 1 M HCl solution (to lower

pH to 1). To adjust pH of deionized water to 7, 1 M NaOH solution was used.

The effect of other cations and anions that may be present in natural water on the

sensing performance was evaluated as follows. Separate vials of a 20-µM solution

containing one of 24 common ions were prepared in DI water (i.e., one ion type per vial)

and acidified to pH 1 by adding 1 M HCl. PL spectra of each sample solution (3 mL)

were recorded after the addition of 5 µL of GSH-Au NCs sol (2 mM, Au atom basis).

These screening tests included 17 cations (Li+, Na+, K+, Mg2+, Ca2+, Ba2+, Cr3+, Mn2+,

Fe2+, Fe3+, Co2+, Ni2+, Cu2+, Zn2+, Al3+, Cd2+ and Pb2+, with Cl- as the counter-ion) and 6

anions (Cl-, SO42-, NO3

-, NO2-, CO3

2- and HCO3-, with Na+ as the counter-ion). The

luminescence intensity at 600 nm of the ion-spiked solutions (F) and the intensity of the

solution without additional ions (F0) was used to calculate the relative luminescent

intensity, F/F0.

The limit of detection (LOD), calculated using IUPAC protocol,[32] is the lowest

concentration of analyte that can be detected with a statistically significant signal change

from an analyzer. The LOD for Cr(VI) was determined by finding the lowest Cr(VI)

concentration that induces a luminescence decrease change (F0-F) that is equal to three

times of the luminescence background signal (3×N). F0 is the mean value of the

luminescence intensity measurements of the NCs (or MCs) in absence of Cr(VI), and F is

the luminescent intensity measured after addition of Cr(VI).

32!!

2.2.7. Synthesis of RBITC-conjugated PAH

RBITC-conjugated PAH (RBITC-PAH) was synthesized and used to prepared MCs to

assess the pH environment within the capsules. The synthesis route of the RBITC-PAH

was adapted from Begum et al.[33] (Supplementary Information).

2.2.8. Test Strip Study

To prepare the paper test strip containing Au-MCs, 50 µL Au-MCs solution was

dispersed onto a 2 cm × 0.5 cm (1 cm2) piece of filter paper (Ahlstrom Disruptor, Grade

4601) with the same Au metal loading (0.19 µg per strip), and dried at room temperature

overnight. To test the sensitivity of the method, the test strip was immersed in a 10 mL

solution with Cr(VI) for 10 min. The test strip was removed from solution and placed

under the UV illumination (365 nm, UVP UVLMS-38 EL Series UV Lamp, illumination

distance of 20 cm). Images of the test strips were recorded with a handheld camera device

(Apple iPhone 8), and analysis using ImageJ software for color intensities. The total

analysis time of each test is roughly 20 min (10 min for test strip immersion and 10 min

for imaging and analysis). The test strip can be stored at atmospheric condition for at

least three months and used with stable luminescence and sensing performance.

2.3. Results and Discussion

2.3.1. Characterization of GSH-Au NCs

The GSH-Au NCs were successfully synthesized, with properties consistent with

previous reports (Supplementary Information, Fig. S2.1). An aqueous GSH-Au NC

33!!

suspension luminesced with a yellow-orange color in the 500-800 nm range, with a QY

of 15%. Photoluminescence lifetime measurements indicated light emission was due to

phosphorescence. The particles had an average TEM-based diameter of 1.6 nm, and a

zeta potential of -11.2±1.3 mV.

These GSH-Au NCs have a core-shell structure with a Au(0) cluster as the core

and GSH as part of the shell, specifically as GS-Au(I)-SG groups surrounding the Au(0)

core.[21] The probable molecular formulae of the GSH-Au NCs are Au29SG27, Au30SG28,

Au36SG32, Au39SG35, and Au43SG37, based on polyacrylamide gel electrophoresis and

electrospray ionization mass spectrometry analyses.[34] For the purpose of calculating

Au content in this work, we assumed the synthesized GSH-Au NCs are Au36SG32, i.e., 32

deprotonated glutathione ligands, and 36 atoms of Au (of which 32 are Au(I) and 4 are

Au(0)). A gold concentration of 2 mM on Au atom basis is equivalent to 3.4 × 1016

particles/mL (0.056 mM) on a Au36SG32 basis.

2.3.2. Encapsulation of GSH-Au NCs

The characterizations of the luminescent GSH-Au NCs including the photographs of an

aqueous sol of GSH-Au NCs (Fig. S2.1a), PL spectra (Fig. S2.1b), quantum yield,

luminescence lifetime (Fig. S2.1c), TEM image (Fig. S2.1d), particle size distribution

(Fig. S2.1e), and zeta potential were detailed in Supporting Information.

Photoluminescence lifetime measurements indicated light emission was due to

phosphorescence.

Scheme 2.1 depicts the encapsulation of luminescent GSH-Au NCs and formation

of the resulting Au-MC, via the well-established PSA charge-assembly chemistry.[28,35]

34!!

In step #1, polymer-salt aggregates (PSA) form instantaneously upon mixing of the

polymer and salt solutions, which is driven by electrostatic interactions between the PAH

amine groups and phosphate anions. In step #2a, the GSH-Au NC sol is added to the

suspension. The NCs have a net negative surface charge, allowing them to incorporate

within the crosslinked network structure of the PSAs. To this Au-PSA suspension, a SiO2

NP sol (13 nm) is added in step #3a, and these NPs (negatively charged at neutral

pH)[36] diffuse and deposit within the outer portion of the Au-PSA to form the shell. The

SiO2 shell, held together by the polymer, is structurally robust, allowing the MCs to

undergo typical powder processing.

35!!

!

Scheme 2.1 Formation of charged-assembled microcapsules (MCs) that (a) contain and (b) not contain the luminescent GSH-Au NCs.

The SEM image showed that the Au-MCs retained their spherical shape after

centrifugation and drying at room temperature and under the vacuum conditions of

microscopy imaging (Fig. 2.1a). The Au-MCs ranged from 0.4 to 1.5 µm in size, with an

average diameter of 0.9 µm and standard deviation of 0.2 µm (Fig. 2.1b). The shell

thickness was estimated to be 0.1 µm (Fig. 2.1c and 2.1d).[37] SiO2 NPs (~12 nm) that

comprise the shell are identifiable through TEM imaging (Fig. 2.1d).

36!!

Figure 2.1 (a) SEM image of Au-MCs (containing 4.8 wt% Au). (b) Size histogram of Au-MCs based on 200 imaged particles. TEM images of (c) an individual Au-MC and (d) shell structure of the Au-MC with SiO2 NPs circled in red.

The Au-MC suspension was slightly yellow and cloudy under visible light,

displaying a yellow-orange emission under UV illumination (Fig. 2.2a). For comparison,

the "empty" MCs (without the Au NCs) formed a white, turbid suspension under visible

light and show no luminescence under UV illumination (Fig. 2.2b). The Au-MC and MC

suspensions settled after ~2 h, and were readily suspended upon agitation. Light yellow

and white powders were respectively obtained after centrifugation, decanting the

37!!

supernatant, and drying the solids under vacuum at room temperature for 24 h (Fig. 2.2c-

d).

Figure 2.2 Water suspensions of MCs that (a) contain and (b) not contain GSH-Au NCs. Dried MCs (c) containing and (d) not containing GSH-Au NCs, recovered after centrifugation and vacuum drying. Upper panels: visible light illumination. Lower panels: UV light illumination (at 365 nm).

The luminescence intensity of the Au-MCs varied proportionally with

encapsulated GSH-Au NC amount, up to ~5 wt% Au (Fig. 2.3a-b). Gold mass balance

calculations indicated that each microcapsule contained up to ~3×107 GSH-Au NCs

(Table S2.2). The Au NCs are distributed uniformly throughout the Au-MC interior (Fig.

2.3c).

38!!

Figure 2.3 (a) Au-MC suspensions with increasing Au loading (0, 0.125×107, 0.25×107, 0.5×107, 1×107, 2×107, 3×107 Au NCs per microcapsule) (upper: visible light; (lower: UV illumination) MC concentration of ~108 capsules/mL. (b) Luminescence peak intensity (at 600 nm; excitation wavelength of 365 nm) as function of Au content. (c) Brightfield and confocal microscope images of Au-MCs (4.8 wt% Au).

The PSA charge-assembly chemistry can be carried out using different cationic

polymers, anionic linkers and charge ratios.[24] We found that maximum luminescence

intensity was achieved using PAH as the cationic polymer, phosphate as the salt linker,

and 6 as the charge ratio (Fig. S2.2).

2.3.3. Photoluminescence enhancement of Au-MCs

The encapsulation of GSH-Au NCs in the MCs had a strong effect on the luminescence

properties (Fig. 2.4a). GSH-Au NCs and Au-MCs were both luminescent with the same

color, with a broad orange emission peak centered at 600 nm, but the latter material was

39!!

5× brighter, i.e., showed 5× greater luminescence intensity (Fig. 2.4b). The comparison

of luminescence intensity between Au-PSAs and Au-MCs (Fig. S2.3) indicated Au-PSA

is the major contribution for the luminescence increase while SiO2 had little effect. We

initially thought that the luminescence enhancement was due to QY increase, since

Yahia-Ammar et al. observed a 4-fold luminescence enhancement and concluded that the

QY increased from 7% to 25%, after aggregating the GSH-Au NCs using PAH.[23]

In our case, the absorbance spectra of Au-MCs (Fig. 2.4c) showed non-zero

"absorbance" throughout the UV-vis range, which is due to significant light (Mie)

scattering within the suspension of the micron-sized capsules. By accounting for this

scattering,[30] we calculated the Au-MCs to have a QY of 13%, slightly lower than the

15% QY for the unencapsulated GSH-Au NCs. The Au MCs are more luminescent than

GSH-Au NCs because of light scattering by the submicron-sized capsule particles and not

because of QY differences.

Figure 2.4 (a) Suspensions of GSH-Au NCs and Au-MCs under UV illumination (365 nm), and corresponding (b) photoemission (365 nm excitation) and (c) absorbance/photoextinction spectra. (overall Au concentration in vial for both suspensions = 0.03 mM on Au atom basis).

40!!

2.3.4. Sensitivity of GSH-Au NCs to Different Ions

Luminescent GSH-Au NCs have been previously reported to function as a "turn-off"

probe to sense Cr(VI) in solution exclusively under acidic conditions.[15] We confirmed

the luminescence sensitivity of the unencapsulated GSH-Au NCs for Cr(VI) at pH 1. As

shown in Fig. 2.5, only Cr(VI) induced a significant decrease (~60%) in the

luminescence intensity at 600 nm, whereas less obvious luminescence changes (< ~5%)

were observed in the presence of other ions.[15]

Figure 2.5 Relative luminescence intensity (F/F0 at 600 nm, where F and F0 are the corresponding luminescence intensities at 600 nm with and without 20 µM tested ion) of

41!!

the GSH-Au NCs (a) in acidified DI water (pH 1) and (b) in DI water (pH 7), and of (c) the Au-MCs in DI water (pH 7). Final Au atom concentration of 0.003 mM.

Zhang et al. proposed that the Cr(VI) sensing ability of GSH-Au NCs is

associated with the reduction of Cr(VI) under acidic conditions (Cr2O72– + 14 H+ + 6 e–

! 2 Cr3+ + 7 H2O, Eo = +1.33 V vs. SHE at pH 0 and 25 °C). We carried out one control

experiment by mixing a solution of GSH (1 mM) and Cr(VI) (0.5 mM) at pH 1. Cr(VI)

concentration rapidly decreased to zero within 5 min as monitored using UV-vis

spectroscopy,[38] which is consistent with previously observed Cr(VI) reduction by

GSH.[39] Our own observation suggests that the GSH ligands behave as a reducing

agent, and that the turn-off effect comes from the disruption of the inter-Au(I)

interactions responsible for AIE. Nano/microscopic structural changes of GSH-Au NCs

after Cr(VI) exposure were not observed through TEM imaging (Fig. S2.4).

The same test for different ions was carried out again with GSH-Au NCs but at

neutral condition (pH~7) (Fig. 2.5b). In this case, Cr(VI) induced a small luminescence

decrease. Most of the tested alkali metal and alkaline earth metal cations increased the

luminescence slightly; Na+ increased the luminescence by 3%. Most of the transition

metal cations induced significant luminescence decrease, but the tested post-transition

(Group 13 and 14) metal showed significant luminescence increase. The anions showed

negligible effect on luminescence, as seen by others.[5,40,41]

The effect of different ions on the luminescence intensity of Au-MCs was also

carried out at neutral condition (pH~7). The Au-MCs presented luminescence behavior

nearly identical to GSH-Au NCs at pH 1 condition (Fig. 2.5c). Significant luminescence

decrease (~98%) was induced by Cr(VI), and minor luminescence changes were observed

42!!

in the presence of other ions. Nano/microscopic structural changes of Au- MCs after

Cr(VI) exposure were not significant based on SEM imaging (Fig. S2.5). Intriguingly,

low pH was not needed for Au-MCs to show Cr(VI) sensitivity. Low-pH testing of Au-

MCs was not performed for comparison, because acidic conditions damaged the capsule

structure (see next section).

2.3.5. Sensitivity of GSH-Au NCs and Au-MCs to Cr(VI) at different concentrations

We next assessed the luminescence sensitivity of GSH-Au NCs and Au-MCs towards

Cr(VI) at different concentrations. A series of solutions with different Cr(VI)

concentrations (up to 1040 ppb-Cr or 20 µM) were prepared in DI water and acidified to

pH 1. PL spectra of each sample solution were recorded after the addition of 5 µL of

GSH-Au NCs stock solution (Fig. S2.6a). Quenching was correlated to Cr(VI)

concentration added (Fig. 2.6a).

Quenching efficiency was quantified using the Stern-Volmer equation, F0/(F0-

F)=1/f+1/(fKSV[Q]), where F0 and F are the luminescence intensity in the absence and

presence of Cr(VI), respectively. f is fraction of Au NCs that are accessible to the

quencher, [Q] is the concentration of analyte quencher, and KSV is the Stern-Volmer

quenching constant.[42,43] A higher KSV value indicates a more sensitive system. The

Stern-Volmer plot (F0/(F0-F) vs. 1/[Q]) for Au NCs (Fig. S2.6b) indicated f = 1,

consistent with the idea that all the freely suspended, unencapsulated Au NCs can come

into contact with Cr(VI) oxyanions (Table 2.1).

43!!

Figure 2.6 Luminescence ratio (F/F0) of (a) GSH-Au NCs and (b) Au-MCs versus Cr(VI) concentration, where F0 and F are the corresponding luminescence intensities at 600 nm (365 nm excitation) in the absence and presence of Cr(VI), respectively. Solution pH = 1 or 7 (or 7.5), Gold content = 3 µmol-Au atom per 1 L solution).

The GSH-Au NCs were less sensitive for Cr(VI) at pH 7 (Fig. 2.6a), with the KSV

value decreasing from 1.44 ppm-1 to 0.14 ppm-1 (Table 2.1). Luminescence quenching of

GSH-Au NCs at neutral condition is much weaker than that under acidic condition, which

can be explained by the lower redox potential at pH 7 than that at pH 1 (0.41 V vs. 1.24 V

for 10 µM Cr(VI)) calculated using the Nernst equation. The lower redox potential

indicates a lower thermodynamic tendency of Cr(VI) to undergo reduction.

Table 2.1 Comparison of KSV and LOD for GSH-Au NCs and Au-MCs.

Sample Water type pH KSV (ppm-1) f Cr(VI) LOD (ppb)

GSH-Au NCs DI water 1 1.30 1 52

GSH-Au NCs DI water 7 0.14 1 700

Au-MCs DI water 1 1.10 0.93 50

Au-MCs DI water 7 13.28 0.93 6

44!!

Au-MCs DI water 7.5 6.75 0.93 8

Au-MCs Simulated drinking water 7.5 3.58 0.93 21

Cr(VI) sensing using Au-MCs was carried out following the same procedure

except that 50 µL of Au-MCs suspension with same Au content was used. With an

increase in Cr(VI) concentration, the luminescence intensity of Au-MCs gradually

decreased (Fig. 2.6b). A linear decrease in luminescence intensity was observed with

increasing Cr(VI) concentration up to 0.05 ppm. Different from the free Au NCs, the

fraction of Au NCs within the microcapsule accessible to Cr(VI) (f) was 0.93, according

to the Stern-Volmer plot (Fig. S2.7). A small portion (7%) of the encapsulated Au NCs is

not accessible to Cr(VI), and do not quench. KSV of Au-MCs at pH 1 and 7 were 1.30

ppm-1 and 13.28 ppm−1, respectively (Table 2.1). The KSV of Au-MCs and GSH-Au NCs

were essentially the same at pH 1(Table 2.1), which we attributed to the breakdown of

the former into their polymer and nanoparticle constituents at the low pH. The Au-MCs

were not found anywhere on the TEM grid, but instead individual silica nanoparticles

were found, consistent with structural breakdown and dis-assembly at pH 1 (Fig.

S2.8).[28] The Au-MCs were very sensitive to Cr(VI) at pH 7, which was >90× higher

than that of the free GSH-Au NCs at the same pH.

The Cr(VI) limit of detection (LOD) for GSH-Au NCs was 52 ppb and 700 ppb at

pH 1 and pH 7, respectively (Table 2.1). The higher LOD is a direct consequence of the

NC's lower sensitivity at pH 7. The LOD of 52 ppb at pH 1 is lower than the 100 ppb of

U.S. EPA MCL for total chromium, but practical use dictates that no pH adjustment is

needed and that NCs not be used in sol form.

45!!The Cr(VI) LOD for Au-MCs was 50 ppb and 6 ppb at pH 1 and pH 7,

respectively (Table 2.1). While LOD at pH 1 is also lower than the total chromium MCL,

the low pH condition is not appropriate for Au-MC use. The LOD at pH 7 is 15× lower

than the MCL which is one important attribute towards implementation. This much lower

LOD stems from the higher sensitivity (large KSV value) resulting from the higher

luminescence intensity of the Au-MCs (Fig. 2.4).

We next tested Au-MCs for Cr(VI) sensitivity in simulated drinking water.

Compared to deionized water at pH 7, the simulated drinking water (pH 7.5) lowered the

sensitivity and raised the detection limit of Au-MCs toward Cr(VI). The KSV value was

3.58 ppm-1, roughly 4× lower than the DI water case (Table 2.1, Fig. S2.9). The Cr(VI)

LOD increased from 6 to 21 ppb in the simulated drinking water, which was calculated

based on a modified calibration curve that corrected the effects of interference (Fig.

S2.10). This LOD was still lower than 100 ppb (total chromium MCL). There were two

possible effects causing the lowered sensitivity and the raised detection limit: the pH

difference and the presence of additional ions (e.g., HCO3-, SO4

2-, Cl-, Na+, Ca2+, Mg2+).

As a control, only raising the pH of DI water from 7 to 7.5 caused KSV to decrease from

13.28 to 6.75 ppm-1 (Fig. S2.7b) and Cr(VI) LOD to increase from 6 to 8 ppb. The

Cr(VI) sensitivity is lower because the Au-MC became less luminescent at pH values

above 7 (Fig. S2.11). In comparing the simulated drinking water (pH 7.5) to DI water at

pH 7.5, the KSV further decreased to 3.58 ppm-1 and LOD increased to 21 ppb. The

differences in KSV and LOD are possibly due to the additional ions, which could have

also contributed to some subtle change to the materials structure.

46!!

2.3.6. Indirect evidence for low pH inside the microcapsules

One of the most interesting observations of the Au-MC system is no acidification of the

sample was needed, implying the capsule interior provides the acidic environment

required for de-luminescence. Within the Au-MCs, the effective proton concentration can

be thought to be higher than bulk concentration due to the high density of PAH (carrying

protonated amine functional groups) distributed throughout the capsule wall and interior

(Scheme 2.1). To test this possibility, we synthesized PAH conjugated to a pH-sensitive

dye molecule (rhodamine B isothiocyanate, RBITC) and used it in the preparation of

MCs containing no Au NCs (Supplementary Information).

The resulting RBITC-PAH MCs, suspended in a DI water solution with a bulk pH

of ~7, showed a peak absorbance at 566 nm, identical to that shown by a RBITC-PAH

solution at pH 2 and below (Fig. 2.7). RBITC-PAH solution at higher pH values showed

a ~10-nm UV-vis absorbance blue shift (Fig. S2.12). Similar local acidic environments

was observed inside dendrimer structures[44] that have a high volume density of protons

associated with the amine groups in the interior.[45]

552

554

556

558

560

562

564

566

568

Inside MCs

pH 1-2 pH 2-3 pH 3-10

Peak

wav

elen

gth

(nm

)

a b c d

47!!

Figure 2.7 Peak wavelength of UV-vis absorbance of RBITC-PAH (a) inside the MCs, and (b-d) in bulk solution at pH values of (b) 1-2, (c) pH 2-3, and (d) pH 3-9.

2.3.7. Cr(VI) strip-based sensor using Au-MCs

This method can also be successfully extended to a simple test strip system, similar to

that of pH indicator paper. The Au-MCs immobilized on paper showed similar Cr(VI)

induced luminescence quenching behavior as if they were in suspension. The test strips

exhibited a gradual decrease in luminescence intensity after they were dipped in

simulated drinking water (pH~7.5) with Cr(VI) of increasing concentrations (Fig. 2.8).

The LOD for the Au-MC-containing test strip was estimated to be 30 ppb, which

is 3× lower than the 100 ppb MCL. The LOD for the Au-MC-containing test strip is

slightly higher than 21 ppb, the LOD for non-immobilized Au-MCs (Table 2.1), which

we attribute to the camera being less sensitive than the photoluminescence spectrometer.

In comparison, unencapsulated Au NCs were dispersed on paper with the same Au

loading, and tested in the same manner. These test strips showed negligible luminescence

decrease with increasing Cr(VI) concentration increased, showing the importance of

encapsulation (Fig. S2.13). The test strip is one-time use due to the irreversible

fluorescence quenching of the Au-MCs.

We also tested the reproducibility of the paper-based sensor in detecting Cr(VI)

by preparing 10 test strips and evaluating the luminescence response of each. The average

signal remained consistent after reaction with 0.5 ppm Cr(VI) (Table S2.3), with a

relative standard deviation (RSD) of 2.9%, indicating high reproducibility.

48!!

Figure 2.8 Image of paper test strips with Au-MCs (0.19 µg Au per strip) (a) under visible light as it fabricated, and (b) under 365 nm UV illustration after dipping into simulated drinking water with different Cr(VI) concentrations and plot of the relative color intensity (I/I0) versus Cr(VI) concentration

2.4. Conclusions

Luminescent glutathione-capped gold nanoclusters (GSH-Au NCs) were synthesized and

incorporated into 0.9 µm-sized capsular particles through polymer-salt assembly (PSA)

chemistry. These microcapsules (MCs) were five times more luminescent than the free

Au NCs at the same Au content. The enhanced luminescence comes from Mie scattering

introduced by the capsule structure. Cr(VI) sensitivity consequently increases, allowing

the LOD of 52 ppb (for free GSH-Au NCs) to improve to 6 ppb after encapsulation. The

amine polymer-containing capsule interior likely provides a low-pH environment for the

NCs to de-luminescense in the presence of Cr(VI), allowing the MCs to be used without

the need for pH adjustment. Cr(VI) was detected in simulated drinking water at

49!!

concentrations 3× below the 100 ppb MCL for total chromium, using a test strip contain

these MCs and a cell phone camera.

2.5. Supplementary Information

Table S2.1 Simulated drinking water composition

General Parameters Specification

Water Source De-ionized water (conductivity < 1 µS/cm)

pH adjusted with HCl 7.5±0.25

Temperature 20±2.5 C

Constituents Concentration (mg/L) Concentration (mM)

Bicarbonate (HCO3-, initial) 183 3.0

Calcium (Ca2+) 40 1.0

Chloride (Cl-) 71 2.0

Fluoride (F-) 1.0 0.053

Magnesium (Mg2+) 12 0.50

Nitrate (NO3-) 8.9 (2.0 as N) 0.14

Phosphate (PO43-) 0.12 (0.04 as P) 0.0013

Silica (SiO2) 20 as SiO2 0.33

Sodium (Na+) 89 3.86

Sulfate (SO42-) 48 0.50

Total Diss. Solids (TDS) 478 -

Ionic Strength - 8.5

The concentrations above are achieved by adding the following to DI water:

50!!

A. 252 mg/L NaHCO3

B. 147 mg/L CaCl2-2H2O

C. 124 mg/L MgSO4-7H2O

D. 95 mg/L Na2SiO3-9H2O

E. 12 mg/L NaNO3

F. 2.2 mg/L NaF

G. 0.18 mg/L NaH2PO4-H2O

After adjusting the pH down to 7.5 with HCl, the solution is expected to have an

alkalinity of approximately 2.8 meq/L.

2.5.1. Synthesis of RBITC

Briefly, 4.2 mg of rhodamine B isothiocyanate (RBITC) was dissolved in 1 mL of

dimethylsulfoxide (DMSO). This solution was sonicated for 10 min before being cooled

to 4 °C. The PAH solution was prepared by dissolving PAH (305.9 mg) in a sodium

hydroxide solution (1.0 mL of 0.1 N sodium hydroxide diluted in 4.0 mL of deionized

water). This second solution was also sonicated for 10 min and allowed to cool to 4 °C.

Once both solutions cooled to 4 °C, the PAH solution was poured into the RBITC

solution and vortex mixed for 10 sec. The 15-mL plastic vial was then covered in

aluminum foil and placed on a shake table for 48 h.

This solution was then placed within a 3.5-kDa MWCO dialysis bag submerged

in 1.0 L of DI water. Dialysis was performed for 90 min under slow stirring until the bulk

dialysis solution had turned a light red under visible light. The content of the dialysis bag

was transferred to a 50-mL plastic vial which was then centrifuged for 20 min at 10,000

RPM. The supernatant was decanted and the final product was re-suspended in 30 mL of

51!!

DI water and sonicated for 10 min. This vial was covered in aluminum foil and stored

under refrigeration (4 °C) until use.

2.5.2. Synthesis and testing of RBITC-PAH MCs

The synthesis route of the RBITC-conjugated PAH MCs was analogous to normal MCs.

In a typical synthesis, cooled RBITC-PAH solution (4 °C, 10 mg/mL, 0.2 mL) was added

into cooled Na2HPO4 solution (4 °C, 0.03 M, 3 mL) in a 15 mL plastic centrifuge tube

(VWR, SuperClear) at room temperature. PAH/Phosphate aggregates readily formed

upon mixing as evidence by the rapid change from a clear, colorless solution to a slight-

pink, turbid suspension. The resulting suspension was vortex-mixed at a high speed (8

speed on a 1-10 scale, Fisher Scientific Mini Vortex Mixer) for 10 seconds and then aged

for 10 min at 4 °C. SiO2 solution (diluted to 7 wt %, 3.0 mL) was then added into the

suspension to initiate MC formation. This solution was aged for 24 h at 4 °C then washed

twice with deionized water through centrifugation (3500 rpm for 20 min), and re-

dispersed in the 3.0 mL of deionized water.

The RBITC-PAH was suspended in solutions with different pH values ranging

from pH 1~9. UV-Vis absorbance was measured at each condition and it was observed

that the spectra could be categorized by three transitions. Unique spectra were acquired

(Fig. S2.12) at pH 1-2, pH 2-3, and pH 3-9. The wavelength of maximum absorbance

corresponds to 566 nm for pH 1-2, 562 nm for pH 2-3, and 557 nm for pH 3-9 (Fig. 2.7).

52!!

2.5.3. Characterization of GSH-Au NCs

The as-synthesized GSH-Au NCs sol appears bright yellow under visible light and emits

a yellow-orange color under 365 nm irradiation (Fig. S2.1a). The UV-vis absorption

spectrum do not exhibit the surface plasmon resonance absorption peak (~520 nm)

associated with a particle diameter greater than ~2 nm. The GSH-Au NCs show a broad

excitation spectrum (250-500 nm), a large Stokes shift of >200 nm, and a broad emission

spectrum (500-800 nm) with the peak centered at 600 nm (Fig. S2.1b). The typical

lifetime for fluorescence ranges from femtoseconds to nanoseconds while for

phosphorescence it ranges from microseconds to seconds.[17] The microsecond-scale

lifetime [3.27 µs (41%), 0.91µs (46%), and 0.18 µs (13%)] of the luminescent Au

NCs (Fig. S2.1c) suggests that the emission was mainly phosphorescence. Luo et al.

measured the luminescence lifetime of the Au NCs synthesized using the same procedure

to be on the order of microsecond, which was consistent with our results.[46]

53!!

Figure S2.1 (a) Photographs of an aqueous sol of GSH-Au NCs (2 mM on Au atom basis) under visible light (left) and 365 nm UV illumination (right). (b) UV-vis absorption (green line), photoexcitation (red line, emission wavelength of 600 nm) and photoemission (blue line, excitation wavelength of 365 nm) spectra of GSH-Au NCs. (c) Photoluminescence decay profile of GSH-Au NCs (d) TEM image of GSH-Au NCs. (e) Size histogram of GSH-Au NCs based on 200 imaged particles.

The QY was measured to be 15% in aqueous solution (pH ~ 7).[21] The purified

GSH-Au NC sol was stable under storage for at least one month, based on a periodic

luminescence measurements. The zeta potential of the GSH-Au NCs sol was -12.4±1.5

mV, due to the negative charge of deprotonated carboxylate groups of GSH at neutral pH.

The zeta potential measured after two months (-13.5±1.6 mV) was consistent with the

fresh-prepared GSH-Au NCs. Though, the zeta potential was not in the commonly stable

range of nanoparticles (<-30 mV or >30 mV)[47], the steric effects of the surface ligand

GSH can stabilize the Au NCs. Before each experiment, Au NCs solution was sonicated

for 10 min to ensure homogeneous dispersion.

Transmission electron microscopy showed the spherical shape of the GSH-Au

NCs (Fig. S2.1d). The particles are unimodal in size, with an average diameter of 1.6 nm

(Fig. S2.1e). At this length scale though, the standard deviation (0.4 nm) reflects image

resolution limitations more than true particle size distribution.[48]

2.5.4. Estimating Au content of Au-MCs

The amount of GSH-Au NCs per microcapsule was calculated by assuming

monodisperse microcapsules of 1 µm and same loading of GSH-Au NCs in each

microcapsule. The average concentration of typical as-synthesized MCs was previously

reported as ~108 capsules/mL through Coulter counter measurements.[25] The average

yield of dried Au-MCs per batch synthesis is 4.1 mg. Based on these values and

54!!

assumptions, Au mass balance calculation indicates that each microcapsule was

comprised up to ~3×107 GSH-Au NCs (Table S2.2).

Table S2.2 MC formulation showing the GSH-Au NCs per MC and GSH-Au NCs (wt%) and Au content (wt%) normalized to dried microcapsule weight.

GSH-Au NCs per MC (×107) GSH-Au NCs per MC (wt%) Au content per MC (wt%)

0 0 0

0.125 0.5 0.2

0.25 1.0 0.4

0.5 1.9 0.8

1 3.8 1.6

2 7.7 3.2

3 11.5 4.8

Figure S2.2 Photoemission spectra of seven types of Au-MCs made from different cationic polymers (PAH or PEI), anionic salt linkers (Na2HPO4 or Na2CIT) and charge ratios (R=3 or 6) in water (overall Au concentration in vial for both suspensions = 0.03 mM on Au atom basis).

55!!

Figure S2.3 (a) Photoemission (365 nm excitation) and (b) photoextinction spectra of GSH-Au NCs, Au-MCs and Au-PSAs. (overall Au concentration in vial for both suspensions = 0.03 mM on Au atom basis).

Figure S2.4 (a) TEM image of GSH-Au NCs after Cr(VI) exposure. (b) Size histogram of GSH-Au NCs based on 200 imaged particles.

56!!

Figure S2.5 SEM image of Au-MCs after Cr(VI) exposure (pH~7)

Figure S2.6 (a) Photoemission spectra of 5 µL GSH-Au NCs in acidified DI water (3 mL, pH=1, 3 µM Au atom) with different concentration (0 – 1.04 ppm) of Cr(VI) at the excitation wavelength of 365 nm; (b) Stern–Volmer Plot of the luminescence ratio (F0/(F0-F)) of GSH-Au NCs versus the reverse of Cr(VI) concentration with a linear correlation range of 0.05 to 0.52 ppm of Cr(VI), where F0 and F are the corresponding luminescence intensities at 600 nm in the absence and presence of Cr(VI), respectively.

57!!

Figure S2.7 (a) Photoemission spectra of 50 µL Au MCs in DI water (3 mL, pH=7, 3 µM Au atom) with different concentration (0 – 0.52 ppm) of Cr(VI) at the excitation wavelength of 365 nm; (b) Stern–Volmer Plot of the luminescence ratio (F0/(F0-F)) of Au MCs versus the reverse of Cr(VI) concentration with a linear correlation of 0.05 to 0.52 ppm of Cr(VI) at pH=7, pH=1 and pH=7.5, where F0 and F are the corresponding luminescence intensities at 600 nm in the absence and presence of Cr(VI), respectively.

Figure S2.8 TEM image of individual SiO2 nanoparticles indicating Au-MCs broke down at pH 1.

58!!

Figure S2.9 (a) Photoemission spectra of 50 µL Au MCs in simulated drinking water (3 mL, pH=7.5, 3 µM Au atom) with different concentration (0 – 3.12 ppm) of Cr(VI) at the excitation wavelength of 365 nm; (b) Stern–Volmer Plot of the luminescence ratio (F0/(F0-F)) of Au MCs versus the reverse of Cr(VI) concentration with a linear detection range of 0.05 to 0.52 ppm of Cr(VI), where F0 and F are the corresponding luminescence intensities at 600 nm in the absence and presence of Cr(VI), respectively.

Figure S2.10 Luminescence ratio (F/F0) of Au-MCs versus Cr(VI) concentration at simulated drinking water condition, where F0 and F are the corresponding luminescence intensities at 600 nm (365 nm excitation) in the absence and presence of Cr(VI), respectively. Solution pH = 7.5, Gold content = 3 µmol-Au atom per 1 L solution).

59!!

Figure S2.11 Luminescence intensity (at 600 nm) of Au-MC at different pH condition.

Figure S2.12 UV-Vis absorbance of RBITC-PAH inside the empty MC and in bulk solution at given pH (pH 1-2, pH 2-3, and pH 3-9).

0

0.2

0.4

0.6

0.8

1

1.2

0 2 4 6 8 10 12 14 Fl

uore

scen

ce in

tens

ity

pH

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

450 500 550 600 650

Abs

orba

nce

(a.u

.)

Wavelength (nm)

pH 3-9

pH 2-3

pH 1-2

Inside MCs

60!!

Figure S2.13 Image of paper test strips with unencapulated GSH-Au NCs (0.19 µg Au per strip) under 365 nm UV illustration after dipping into simulated drinking water (pH 7.5) with different Cr(VI) concentrations and plot of the relative color intensity (I/I0) versus Cr(VI) concentration

Table S2.3 The reproducibility of the paper-based sensor in analyzing Cr(VI) in 10

batches

Test# 1 2 3 4 5 6 7 8 9 10

I/I0 0.56 0.57 0.56 0.58 0.55 0.53 0.56 0.59 0.55 0.56

2.6. Reference

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!

! !

66!!

Chapter 3

Treating Water by Degrading Oxyanions Using Metallic Nanostructures

3.1. Introduction

3.1.1. Sustainability of water

Fresh water is essential for life and is a key element of food and energy production, yet it

makes up for only 3% of all earthly water.[1] Roughly ~30% of fresh water is readily

usable, with the rest locked in ice caps and glaciers.[2] In 2014, an estimated 346 billion

gallons per day of fresh surface and groundwater were consumed in the U.S. for energy

production, agriculture, and other needs.[3] As a consequence of anthropogenic activities,

millions of tons of toxic chemicals are unfortunately released into the water supply every

year, negatively impacting water quality.[4] Clean fresh water is critical to both human

health and industrial development, and proper management is required for its sustainable

use.[5]

67!!

3.1.2. Toxic oxyanion contamination

When in the water environment, many elements speciate into oxyanions depending on pH

and electrochemical potential.[6,7] Their molecular formulae can be generalized as

AxOyz, where A represents a chemical element, O represents oxygen, and z is the overall

charge of the ion.[8,9] Oxyanions are highly soluble and mobile in water, and are

widespread in drinking water sources such as surface and groundwater.[8]

Fig. 3.1 shows elements that commonly form thermodynamically and/or

kinetically stable oxyanions at pH 6.5~8.5 and at electrochemical potential (Eh) values of

0.1~0.4, which are the conditions commonly found in drinking water system.[10] An

oxyanion of a given element is considered thermodynamically stable if it is the lowest

free energy state compared with other species of the element.[11] Pourbaix diagrams map

the most thermodynamically stable species for a given element as a function of pH and

electrochemical potential.[12] The sulfate (SO42-) anion, for example, is the

thermodynamically stable species of sulfur at pH 6.5~8.5 and Eh 0.1~0.4 V as shown in

the Fig. 3.2a.[13]

68!!

!Figure 3.1 Periodic table showing the most common oxyanion and cation species (marked by color) under drinking water conditions (pH 6.5~8.5, Eh 0.1~0.4 V). Thermodynamically stable oxyanions are peach-colored, kinetically stable oxyanions are in red, and cationic elements are in blue.

!

Oxyanions that exist in the environment but are not at the lowest energy state of

the element are kinetically stable.[14] Their conversion to a lower free energy state

requires additional energy to overcome an activation barrier.[15] For example,

perchlorate (ClO4-) is an environmentally stable oxyanion of chlorine in water, but

chloride is the lowest energy form of chlorine. Chloride (Cl-), and not perchlorate, is

shown within the water stability range in the Pourbaix diagram for chlorine (Fig.

3.2b).[16] While most non-metal elements can form common oxyanions in water at pH

6.5~8.5 and Eh 0.1~0.4 V, metal elements tend to form cations instead of oxyanions, or

they precipitate as insoluble oxides. For example, iron forms ferrous cation (Fe2+) in

water at pH ~6.5 and Eh~0.1 V (Fig. 3.2c).[17]

H He

Li Be B (BO3

3-) C

(CO32-)

N (NO3

-) O F Ne

Na (Na+)

Mg (Mg+)

Al Si (SiO3

2-) P

(PO43-)

S (SO4

2-) Cl

(ClO2-)

Ar

K Ca Sc Ti V Cr (CrO4

2-) Mn

(MnO4-)

Fe (Fe3+)

Co Ni Cu (Cu2+)

Zn (Fe3+)

Ga Ge As (AsO4

3-) Se

(SeO42-)

Br (BrO3

-) Kr

Rb Sr Y Zr Nb Mo Tc Ru Rh Pd Ag Cd In Sn Sb (Sb(OH)6

-) Te

(TeO4-)

I (IO3

-) Xe

Cs Ba La-Lu Hf Ta W Re Os Ir Pt Au Hg Tl Pb (Pb2+) Bi Po At Rn

Fr Ra Ac-Lr Rf Db Sg Bh Hs Mt Ds Rg Cn Nh Fl Mc Lv Ts Og

La Ce Pr Nd Pm Sm Eu Gd Tb Dy Ho Er Tm Yb Lu

Ac Th Pa U Np Pu Am Cm Bk Cf Es Fm Md No Lr

69!!

Figure 3.2 Pourbaix diagram of (a) sulfur (modified from Vermeulen et al.[13]), (b) chlorine (modified from Radepont et al.[16]), and (c) iron (modified from Tolouei et al.[17]). The blue dashed lines indicate the water electrochemical potential window.

Some oxyanions (e.g. carbonate CO32-) and cations (e.g. sodium Na+) are benign

to the environment and human health, and are not subject to guidelines or regulations at

either the federal or state level. However, other oxyanions and cations are toxic and can

cause severe health problems.[18] Nitrogen (e.g. NO3-/NO2

-), chromium (e.g. CrO42-),

bromine (e.g. BrO3-), and chlorine (e.g. ClO2

-) oxyanions as well as certain cations (e.g.

Cu2+, Cd2+, Pb2+ and Hg2+) are regulated by the National Primary Drinking Water

Regulations (NPDWRs) with a maximum contaminant level (MCL) as set by the US

Environment Protection Agency (EPA).[19] U.S. states often have stricter regulations.

For example, the state of California has an MCL of 6 ppb for perchlorate (ClO4-) in

drinking water, but there is not yet a federal MCL.[20]

Many technologies have been developed for the removal of oxyanions from water

including adsorption,[21] ion exchange (IX),[22] and reverse osmosis (RO).[23]

However, these methods and processes do not degrade the compounds, but instead

transfer the contaminant into a secondary waste stream requiring disposal. Biological[24]

and chemical[25] treatments of contaminants can be used to transform the contaminants

O2

H2

H2S

S

SO42-

HSO4-

HS-

H2O

2 4 6 8

1.2

0.8

0.4

0.0

-0.4

Eh (V

)

pH 2 4 6 8

pH 10 12 14

ClO- HClO Cl2

Cl-

O2

H2O

H2 -0.8

-0.4

0.0

0.4

0

0.8

1.2

1.6

2.0

Eh (V

)

Fe2+

Fe3+

Fe2O3

Fe

Fe3O4

Fe(OH)2

FeO42-

O2

H2O

H2

2 4 6 8

pH 10 12 14 0

Eh (V

)

-1.2

-0.8

-0.4

-0.0

0.4

0.8

1.2

1.6

2.0 (a) (b) (c)

70!!

to inert products. Biological processes are sensitive to operational conditions (e.g. pH and

salinity) and require long startup times though, and chemical treatments often require an

excess of chemical reagents and can generate toxic byproducts.

3.1.3. Metallic nanostructure based catalytic water treatment as a sustainable

process

Commonly used water treatment technologies based on IX and reverse osmosis not only

generate concentrated waste streams but they also require large energy input.[26]

Catalysis offers the desirable advantages of less energy usage and no waste generation,

though it is not yet a common treatment approach. As one of the principles of green

chemistry in reducing and eliminating the formation of hazardous compounds,[27]

catalysis can also play an enabling role in their degradation and removal from the water

environment, once formed. Any chemicals needed for catalysis should also be sustainably

produced. For reduction reactions, for example, hydrogen gas can be obtained through

water electrolysis (with electricity generated from solar panels or wind turbines) and

formic acid can be obtained from biomass conversion.[28,29]

The most studied materials are metal-based catalysts due to their outstanding

catalytic properties, with regard to activity, selectivity, and/or stability.[30,31] Metallic

nanostructures are defined as metallic objects with at least one dimension in the range of

one to a few hundred of nanometers, for example, spherical nanoparticles, nanorods,

nanosheets, and nanocubes.[32,33] The occupancy of d-bands of metal atoms allows

reversible bonding to reactants via electron transfer, initiating surface reactions and

affording them their catalytic activity.[32] Metal catalysts generally contain nanoparticles

71!!

(zero-dimensional metallic nanostructures) attached to a porous support, and have been

used for both oxidative and reductive catalytic processes to convert contaminants in water

to environmentally inert compounds.[34] Oxyanions (e.g. nitrite,[35] nitrate,[36]

bromate, [37] and perchlorate3,5) and organohalides (e.g. trichloroethene[39] and

chloroform[40]) have been widely studied as target contaminants for catalytic reduction.

A 2012 review by Werth and coworkers assessed the state of knowledge

concerning palladium-based catalysts for water remediation[34] of several contaminants

(halogen and nitrogen containing organic compounds), and briefly addressed the catalytic

reduction of oxyanions. In this contribution, we focus on oxyanions (Table 3.1) and the

current state of understanding of their catalytic chemistry and prospects of catalytic water

treatment.

Table 3.1 Concentration level and health effect of common toxic oxyanions

Contaminant Regulated concentration level (ppm)

Potential health effects

Nitrate 10 (measured as nitrogen, US EPA)

Infant methemoglobinemia (blue-baby syndrome); probable carcinogen

Nitrite 1 (measured as nitrogen, US EPA)

Infant methemoglobinemia (blue-baby syndrome), probable carcinogen

Chromium(VI) 0.1 (measured as total chromium, US EPA)

Probable carcinogen

Bromate 0.01 (measured as bromate, US EPA)

Probable carcinogen

Chlorite 1 (measured as chlorite, US EPA)

Anemia; nervous system effects

[Chlorate] [Not regulated] Thyroid disfunction

72!!

Perchlorate 0.002 (measured as perchlorate, Massachusetts state level) 0.006 (measured as perchlorate, California state level)

Thyroid disfunction

Arsenic (as arsenate and arsenite)

0.01 (measured as total arsenic, US EPA)

Probable carcinogen

Selenium (as selenate and

selenite)

0.05 (measured as total selenium, US EPA)

Circulatory system disfunction

3.2. Catalytic Detoxification of Oxyanions Using Metallic

Nanostructures

Monometallic nanostructures can function as a materials platform for catalytic reduction

to 1) adsorb and dissociate reducing agents (e.g. H2 to surface adsorbed hydrogen atom),

2) adsorb oxyanion contaminants on the surface of catalyst, 3) abstract oxygen from

oxyanions by reacting with hydrogen adatoms, and 4) desorb the deoxygenated products

from the surface of catalyst.[34] Monometallic compositions are sufficient to convert

nitrite,[41] bromate,[42] and chromate[43] to inert species. However, some oxyanions

like nitrate[44] and perchlorate[45] require a second metal as a promoter. The promoter

metals are typically more oxophilic and can more efficiently abstract oxygen from

oxyanion contaminants.[46] The promoter metal would then be re-reduced by hydrogen

adatoms generated on the primary metal.[36]

73!!

3.2.1. Nitrogen oxyanions

3.2.1.1. Occurrence and health effects

Nitrogen oxyanions like nitrate (NO3-) and nitrite (NO2

-) are widespread contaminants of

surface water and groundwater.[47,48] The sources of these nitrogen oxyanions mainly

come from chemical fertilizers and industrial waste.[49] A number of medical issues are

associated with NO3-/NO2

- intake, such as damage to the nervous system, spleen, and

kidneys. Evidence is building that nitrogen oxyanions are carcinogenic and that they have

a strong correlation with high cancer levels.[50] Nitrogen oxyanions can cause the in-situ

formation of cancerous nitrosoamines in the body, and ingestion of nitrates during

pregnancy can also cause infant methemoglobinemia (i.e. “blue baby syndrome”).[51]

The US EPA has placed a MCL of 10 ppm and 1 ppm (measured as nitrogen) in drinking

water for NO3- and NO2

-, respectively.[19]

3.2.1.2. Current technology

Ion exchange (IX), reverse osmosis (RO), and electrodialysis reversal (EDR) are the only

methods accepted by the US EPA for NO3-/NO2

- removal from water.[52–54] IX is the

most widespread technology used in for removing NO3-/NO2

- from drinking water

sources, and has proven very effective in small to medium sized treatment plants, while

RO is the second most common NO3-/NO2

- treatment alternative.[55] The most

significant drawback of IX is the cost for disposal of the brine waste (which contains

concentrated NO3-/NO2

- after IX regeneration), especially for inland communities.[56]

For RO, key drawbacks include pretreatment requirements, power consumption, the

management of waste concentrate, and higher electricity costs relative to IX.[57] The use

74!!

of EDR in potable water treatment has increased in recent years, offering the potential for

lower residual volumes through improved water recovery, the ability to selectively

remove nitrate ions, and the minimization of chemical and energy requirements.[58]

3.2.1.3. Catalytic chemistry

Catalytic nitrate/nitrite reduction using metallic nanostructures is a promising method for

direct drinking water treatment and IX waste brine treatment. Scheme 3.1 shows the

Gibbs free energy (∆G) values for nitrate/nitrite reduction to dinitrogen and ammonia

using hydrogen at standard conditions are -229 kJ/mol and -530 kJ/mol, respectively.[59]

For nitrate reduction to dinitrogen and ammonia, the free energy values are -835 and -733

kJ/mol, respectively.[59] Under laboratory conditions (1 mM nitrate ~ 14 ppm-N, pH 7,

25 °C, 1 atm), the calculated corresponding free energy values decrease to -778 and -653

kJ/mol. Since ∆G is negative (exergonic reaction), the reduction of nitrate (and nitrite) to

the two end-products is thermodynamically favorable at room temperature. These

reactions do not proceed without catalysts that lower the activation barriers for the

respective reactions.

75!!

Scheme 3.1 Reduction reaction of nitrite and nitrate, to nitrogen gas and ammonia with corresponding standard Gibbs free energy values (25 °C, 1 atm, 1 M reactant concentrations, pH 0)

!

Generally, noble metallic nanostructures (i.e. Pd, Pt) adsorb and dissociate

reducing agents (e.g. H2) into reactive species (e.g. surface-adsorbed hydrogen atoms),

and also adsorb NO2- onto the surface. Oxygen is then abstracted from the NO2

-, and the

formed N-species further react together to form dinitrogen gas, or hydrogenate

completely to form ammonium species. Pd is the most studied monometallic catalytic

nanostructure for nitrite reduction,[60–64] ever since the initial metal screening work of

Vorlop and co-workers. They showed Pd to be the most active towards dinitrogen,

compared to Pt, Rh and other metals.[65,66]

The most commonly accepted catalytic reduction pathway of nitrite on the Pd

surface is illustrated in Scheme 3.2. The surface adsorbed hydrogen atoms can go on to

react with co-adsorbed nitrite to form NO(ads) on the surface. NO(ads) is a key intermediate

in the nitrite reduction pathway which can lead to both dinitrogen and ammonia.[41,67]

76!!

Scheme 3.2 Nitrite catalytic reduction pathway on Pd surface with hydrogen gas as a reducing agent (modified from Martínez et al.[68]). The DFT calculated pathway is kinetically unlikely to occur.

In the formation of dinitrogen, NO(ads) can dissociate to allow for dinitrogen

formation through the direct coupling of N(ads) species.[41] Dinitrogen can also be formed

through a mechanism where NO(ads) is converted through the intermediate N2O. In the

formation of ammonia, NO(ads) can lead to NH4+ through the stepwise hydrogenation of a

presumed N(ads) species. Werth and coworkers showed, using isotopically labeled N

species that N2O forms N2 exclusively, while NO forms both N2 and ammonium.[67]

Direct NO(ads) hydrogenation has been proposed for NH4+ formation via HNO(ads),

H2NO(ads), and H2NOH(ads) intermediates,[68] though we are doubtful of this pathway.

While NO(ads) hydrogenation has been demonstrated experimentally over Pt, this pathway

was ruled out experimentally for Pd, and was determined computationally to be more

unlikely to occur compared to N(ads) formation and hydrogenation.[41,60]

Improving the activity of Pd-based catalysts has been a main focus of many

studies (Table 3.2). Various catalyst structures, support and compositions with addition

of secondary metal have been studied in catalytic nitrite reduction.[61,69,70] Seraj et al.

synthesized Pd-Au alloy catalysts and found that the addition of Au improves the nitrite

NO2- (aq) NO2

- (ads) NO (ads)

N2O (ads) N2 (g)

N2 (g)

NH (ads) NH2 (ads)

HNO (ads) H2NO (ads) H2NO (ads)

NH4+ (ads)

NH4+ (aq)

Pd

Pd Pd

Pd

Pd

Pd Pd

Pd Pd

Pd

Pd

DFT calculated pathway

77!!

reduction activity, and the alloy structure showed reduced loss of catalytic activity in

sulfide fouling tests.[71] Their DFT (density functional theory) calculations indicated that

Au enhanced the activity of Pd through electronic effects, and reduced sulfur poisoning

by weakening the sulfide bonding at the Pd-Au surface. Wong and coworkers synthesized

Au nanoparticles (NPs) covered with submonolayer amounts of Pd, and observed

improved nitrite reduction activity by an order of magnitude.[35] The enhancement effect

of Au on Pd catalysis of nitrite reduction was attributed to the creation of zerovalent two-

dimensional Pd ensembles and high Pd dispersion.

Table 3.2 Performance of metallic nanostructures in the catalytic reduction of nitrite

* Re-calculated kcat normalized by total metal amount based on the published data.

Researchers have also focused on enhancing the nitrite reduction selectivity to

nontoxic N2. Higher N2 selectivity was found to relate to large catalyst particle sizes,[64]

specific shapes (e.g. Pd rods and cubes),[31] type of stabilizing surfactants,[73] and

Catalyst kcat*

(L/ g metal/min) Hydrogen donor Initial pH Reaction temperature Ref.

5wt% Pd/Al2O3 5wt% Pt/Al2O3

- - H2 5.2 Room temperature [60]

Pd80Cu20/PVP 1.67 H2 5.5-7.5 Room temperature [46] 5wt%Pd/Al2O3

5%Pd 0.5%In/Al2O3 4

6.9 H2 5 Room temperature [70]

5.42%Pd 0.86%In/Al2O3 17.43 H2 7 Room temperature [67]

2.8nmPd/PVP 3.2nmPd/PVA

1.53 1.47 H2 8.5 Room temperature [62]

1wt%Pd/Al2O3 Pd NPs

Pd-on-Au NPs

76 40

576 H2 5-7 Room temperature [35]

1wt% Pt/Al2O3 1wt% Pt Cu/Al2O3

0.6 0.7 H2 5.5 10 °C [72]

0.25wt%Pd/ACC 7.06 H2 4.5 25 °C [69]

5wt%Pd/CNF 2.44 H2 5 21 °C [64]

PdAu alloy 5 H2 6.4 22 °C [71]

78!!

especially reaction conditions. An increase in pH generally decreased both the activity of

nitrogen oxyanion reduction and the selectivity to N2, though the mechanistic reason is

still not completely understood.[44] Lefferts and co-workers reported surface coverage

changes of the reaction intermediates at different pH values using attenuated total

reflectance infrared spectroscopy, which could be the source of reactivity and selectivity

differences.[60] Reactant concentration has little effect on the normalized activity (in unit

of liter per gram-catalyst per min) if the reaction is in the kinetically-controlled region,

while it has strong effect on the selectivity of nitrogen oxyanion reduction. Shin et al.

showed that an increased initial nitrite concentration or lower H2 flow rate both enhanced

N2 selectivity, and concluded that surface adsorbed nitrogen reacts with NO2- in solution

to form dinitrogen.[41]

While effective for nitrite, monometallic Pd (or Pt) nanostructures show little

activity for nitrate reduction,[74] and require a secondary promoter metal, such as copper

(Cu), tin (Sn), or indium (In) (Table 3.3).[75–78] The secondary metal is thought to be

oxidized after abstracting the oxygen from nitrate, and converting it to nitrite. The

oxidized secondary metal is then re-reduced by hydrogen atoms adsorbed on the Pd or Pt

surface. The nitrate-to-nitrite catalytic cycle is shown in the Scheme 3.3. The nitrite

presumably reduces to dinitrogen or ammonia via Scheme 3.2.

79!!

Scheme 3.3 Nitrate catalytic reaction pathway to nitrite on Pd surface with M (Cu, Sn, or In) as a secondary metal promoter and hydrogen gas as a reducing agent (modified from Guo et al.[36])

Among the Pd-based bimetallic catalysts, Pd-Cu is the most studied, even though

Cu is not the best promoter choice. Vorlop and coworkers originally reported that Pd-Sn

and Pd-In catalysts were more active for nitrate reduction and more N2 selective than Pd-

Cu.[79] Chaplin and coworkers reported Pd-In was more stable than Pd-Cu with regard to

metal leaching during catalyst regeneration.[80] When sulfide-poisoned Pd-Cu and Pd-In

catalysts were treated with a dilute bleach solution, 11% of the total Cu leached into

solution while no In leaching was detected. Thus, In is more appropriate for water

treatment.

Recently, Wong and coworkers studied the role of In using In-on-Pd nanoparticle

catalysts in kinetic testing, in-situ x-ray absorption spectroscopy, and DFT

simulations.[36] They experimentally observed the in situ oxidation of In upon exposure

to NO3- solution, providing experimental evidence for In as a redox site for the nitrate-to-

nitrate step (Scheme 3.3). The material exhibited nitrate reduction volcano dependence

NO3$ NO2

$

In3+In0

H+ H*

H2 2H*Pd0

Pd0

H*

N2

a

b

c

d

H2H2O$ H2$

N2/NH4+$

M0$ Mn+$

NO3-$ NO2

-$

80!!

on In surface coverage, with 40% Pd surface coverage (40 sc%) by In that was 50%

higher than that of a sequentially impregnated InPd/Al2O3 catalyst (with >95% selectivity

to dinitrogen).[36] DFT calculations indicated In ensembles containing 4 to 6 atoms

provide the strongest binding sites for nitrate oxyanions and lead to smaller activation

barriers for the nitrate-to-nitrite step.[36] Lumped kinetic modeling implicated both

factors for the observed volcano peak near 40 sc%.

Table 3.3 Performance of metallic nanostructures in the catalytic reduction of nitrate

Catalyst kcat*

(L/ g metal/min) Hydrogen donor Initial pH Reaction temperature Ref.

1.6% Pd/CeO2 2.06 H2 - 25 °C [74]

40 sc% In-on-Pd NPs 2.15 H2 5.5 Room temperature [36] 5%Pd 5%In/Al2O3

5%Pd 1.25%In/Al2O3 5%Pd 0.625%In/Al2O3

2.23

3.86

2.02

H2 H2 H2

5 Room temperature [81]

5%Pd 1%In/Al2O3 0.084

0.012 H2

HCOOH 6 Room temperature [79]

5%Pd 2%In/Al2O3 5%Pd 4%Sn/Sty-DVB 5%Pd 4%In/Sty-DVB

0.0628 0.51 0.19

H2 5 25 °C [82]

2%Pd 0.5%Cu/Al2O3 0.59 H2 5 Room temperature [83]

1%Pd 0.25%In/SiO2 1%Pd 0.25%In/Al2O3

0.65

2.8 H2 H2


5%Pd 2%In/ SiO2 5%Pd 2%In/ Al2O3 5%Pd 2%In/ TiO2

0.57

0.214

0.236

H2 H2 H2


5%Pd 1.25% In/AC 6.08 H2 5 Room temperature [85]

1.6%Pd 2.2%Sn/ZSM-5 1.73 H2 5 Room temperature [77] 0.1%Pd 0.01%In/Al2O3 0.12 H2 5 Room temperature [86] 1.6%Pd 2.2%Cu/NBeta 1.6%Pd 2.2%Sn/NBeta 1.6%Pd 2.2%In/NBeta

0.33 2.8

0.42

H2 H2 H2

4.5-5 Room temperature [87]

5%Pd 1.5%Cu/Al2O3 3.88 H2 5 Room temperature [88]

2.5%Pd 0.25%In/C 0.0088 H2 5 Room temperature [89]

1%Pd 0.25%In/Al2O3 3.1 H2 5 Room temperature [90] 1%Pd 0.25%In/Al2O3

1%Pd 1%In/SiO2 1%Pt 0.25%In/Al2O3

1%Pt 1.2%In/SiO2

5.16 0.3

2.02 0.24

H2 H2 H2 H2


0.92%Pd 0.32%In/Al2O3 0.049 H2 6 Room temperature [92]

81!!

*Re-calculated kcat normalized by total metal amount based on the published data.

3.2.1.4. Assessment of technology readiness

Attempts have been made to scale-up the catalytic reduction process for nitrate

treatment.[69,100,102,103] For example, a company has developed a catalytic unit based

on Pd-Cu supported on activated carbon cloth, and is conducting pilot tests with the

Southern Nevada Water Authority to treat 90-ppm nitrate-containing water at a

throughput of 2-8 m3/h.[102]

Werth and co-workers have worked on developing Pd-In catalyst-based trickle-

bed flow reactors (TBR) for nitrate treatment of drinking water and IX waste

brine.[86,89,104] Gas and liquid flow rates, catalyst metal loading, and catalyst pellet

size were varied to optimize TBR performance. Catalytic activity in the flow reactor was

~18% that of the same catalyst tested in batch mode, which was attributed to H2 mass

transfer limitations. Catalytic activity was lower by ~50% in the IX waste brine treatment

0.75%Pt 0.25%Cu/Al2O3 1.1 H2 6.5 10 °C [93]

4.7%Pd 1.5%Sn/Al2O3 0.3 HCOOH 5 Room temperature [94] 1.6%Pt 0.8%Cu/Al2O3 1.6%Pd 0.5%Cu/Al2O3 1.6%Pt 0.8%Ag/Al2O3 1.6%Pd 0.8%Ag/Al2O3

0.5 0.39 0.39 0.44

H2 H2 H2 H2

- 10 °C [95]

1.5%Pd 0.5%Cu/Al2O3 1.5%Pd 0.5%Co/Al2O3 1.5%Pd 0.9%In/Al2O3

0.28 0.048 0.12

H2 H2 H2

5 - [96]

2%Pd 0.6%Cu/ACC 0.08 H2 5.5 25 °C [97]

5%Pd 0.5%Sn/PPy 1.7 H2 3.5 25 °C [98]

Pd60Cu40/PVP 0.08 H2 5.5-7.5 Room temperature [46]

0.75%Pt 0.25%Cu/Al2O3 1.1 H2 5.5 10 °C [72]

5%Pd 0.86Cu/ASA 1.09 H2 5.4 25 °C [99]

0.13%Pd 0.03%Cu/GFC 0.96 H2 5.1 25 °C [100]

5%Pd 1.5%Cu/SnO2 4.9%Pd 1.5%Cu/ZrO2

0.089 3.92 H2 4 25 °C [101]

82!!

compared to drinking water treatment, which was caused by competitive adsorption

between the chloride and sulfate anions with the nitrate reactant.

3.2.2. Chromium Oxyanions


In the US, chromium is the second most common inorganic contaminant, after

lead.[105,106] The most common forms of chromium are trivalent chromium (Cr(III))

and hexavalent chromium ("chromium-6", Cr(VI)). Chromium oxyanions (e.g. chromate

CrO42-) are frequently used in metallurgy, pigment manufacturing, and wood treatment

processes.[107] Inappropriate disposal of industrial wastewaster results in chromium

contamination. Chromium oxyanions have cytotoxic and carcinogenic properties.[108]

The US EPA set a MCL of total chromium (Cr(III) + Cr(VI)) to 0.1 ppm for drinking

water.[19] California has a more restrictive MCL of 0.05 ppm for total

chromium.[109,110] The World Health Organization (WHO) provides a drinking water

guideline value of 0.05 ppm for Cr(VI).[111]

3.2.2.2. Current technologies

Numerous removal methods, including chemical reduction,[112] IX,[113]

adsorption,[114] biodegradation,[115] and membrane filtration[116] have been studied

for Cr(VI) (in the form of CrO42-). Barrera-Díaz and coworkers reviewed chemical,

electrochemical and biological methods for aqueous chromate reduction.[117] Some of

the most common remediation strategies use redox reactions to convert chromate to a

chromium oxide solid by adding Fe(II) as the electron donor (6 Fe2+(aq) + 2 CrO4

2–(aq) + 13

83!!

H2O ! 6 Fe(OH)3 (s) + Cr2O3 (s) + 8 H+).[118] IX is used on a large scale to remove

chromate (e.g., Cal Water in California).

3.2.2.3. Catalytic chemistry

While Cr(VI) is highly toxic and carcinogenic, Cr(III) is non-toxic and an essential trace

element for humans.[119] Cr(III) is in a soluble cation form (Cr3+) under acidic

conditions and readily precipitates as a Cr(OH)3 solid at neutral pH condition. The

catalysis strategy is to 1) reduce CrO42- to Cr3+ under acidic conditions, and 2) raise the

pH to convert Cr3+ to insoluble Cr(OH)3. Formic acid is widely used as a reducing agent

because it also provides the low pH condition. Reduction of chromate using hydrogen

generated from the decomposition of formic acid[120] and the formation of Cr(OH)3

precipitate[121] are thermodynamically favorable (Scheme 3.4).

Scheme 3.4 Formic acid (HCOOH) decomposition to hydrogen and carbon dioxide, reduction reaction of chromium oxyanion, and formation of chromium hydroxide with their corresponding standard Gibbs free energy values (25 °C, 1 atm, 1 M reactant concentrations, pH 0)

The Cr(VI) reduction reaction is slow and requires a catalyst, but the formed

Cr(III) rapidly forms Cr(OH)3 without one. Noble metallic nanostructures (e.g. Pd, Pt,

Au, Ag) have been investigated for the former reaction.

84!!Sadik's group first reported the reduction of chromate to Cr3+ over colloidal Pd

NP catalysts using formic acid.[43] The reaction likely follows a Langmuir-Hinshelwood

surface reaction mechanism, involving H adatom formed from the dehydrogenation of

formic acid on the metal surface.[122] Surface adsorbed hydrogen then reduce the co-

adsorbed chromate/dichromate to Cr3+ via a hydrogen transfer pathway.[122] Although

formic acid has been the most commonly studied, other reducing agents, such as

hydrogen gas,[43,123] sulfur,[124] and poly(amic acids)[125] have also been studied.

Other noble metallic nanostructures, such as Pt,[126–128] Ag102,103 and

Au[126,129], as well as their bimetallic forms, such as PdAu and AuAg[129,131] have

also been investigated for chromate reduction (Table 3.4). Yadav et al. compared Pt, Pd,

and Au nanoparticles immobilized in a metal-organic framework, and found that Pt was

the most active while Au was inactive.[126] The reason for Pt as the most active catalyst

is not clear. Bimetallic NPs (e.g. AuAg and PdAu) were found to have enhanced catalytic

activities compared with their monometallic forms in the chromate reduction

reactions.[129] The relative importance of electronic, geometric and bifunctional effects

on Cr(VI) reduction using bimetallic nanostructures is not known at this point.

To understand the structure-property relationships of monometallic catalysts, Pd-

based materials with different shapes were synthesized and studied for catalytic chromate

reduction (Table 3.4). Zhang et al. found Pd icosahedron-shaped NPs to be the most

active among other shaped studed (spheres, rods, spindles, cubes and wires).[132] They

attributed its reduction ability to the icosahedron having a greater fraction of surface Pd

atoms exposed on {111} facets. We recommend normalizing measured reaction rate

85!!

constants to surface Pd atoms (calculated or experimentally titrated) as a more

quantitative way to compare shape effects. [133]

Support effects are have been studied extensively also (Table 3.4).[134–136] The

metal-normalized reaction rate constants (re-calculated from published values) span two

orders of magnitude. This wide activity range suggests the presence of intraparticle mass

transfer effects on observed reaction rates, interfering with any potential compositional

effect of the support on Cr(VI) reduction. Mass transfer effects can be assessed (and

corrected for) if rigorous experimentation is carried out.[137]

Table 3.4 Performance of metallic nanostructures in the catalytic reduction of chromate

Catalyst kcat*

(L/ g metal/min)

Hydrogen donor

Initial pH

Temperature Ref

Pd colloid 28.97 HCOOH 2 45 °C [43] Pd tetrapod 0.14 HCOOH - 50 °C [138] Pd nanowire 0.07 HCOOH - Room

temperature [135]

Urchin-like Pd 0.01 HCOOH - Room temperature

[139]

Pd icosahedron 0.03 HCOOH 1.5 Room temperature

[132]

AuPd@Pd 24.04 HCOOH - 50 °C [131] 2.93% Pd/TiO2 nanotube 62.23 H2 2 25 °C [140]

Pd/γ-Al2O3 film - HCOOH - 30 °C [141] 13.1% Pd/PEI/PVA nanofibers 65.07 HCOOH - 50 °C [134]

1.13% Pd/Fe3O4 - HCOOH 4 45 °C [142] 1.2% Pd/Amine-functionalized SiO2 14.14 HCOOH - 25 °C [143]

22.4% Pd/ZIF-67 8.47 HCOOH - - [144] 2% Pd/MIL-101 0.15 HCOOH - 50 °C [126]

5.66% Pd/Eggshell membrane 1.85 HCOOH - 43 °C [127] Pd/Tobacco mosaic virus 345.88 HCOOH 3 Room

temperature [145]

2% Pt/MIL-101 0.56 HCOOH - 50 °C [126] 5.91% Pt/Eggshell membrane 2.61 HCOOH - 43 °C [127]

10.38% Pt/Magnetic mesoporous silica

20.00 HCOOH - 25 °C [128]

2.7% Ag/Biochar 5.54 HCOOH - 50 °C [130] 3.05% AgAu/Ruduced graphene

oxide 253.70 HCOOH - Room

temperature [129]

86!!2% Au/MIL-101 0 HCOOH - 50 °C [126]


3.2.2.4. Assessment of technology readiness

Currently, all studies on chromate reduction have been conducted in batch reactors. We

are not aware of any pilot-scale catalytic systems to treat Cr(VI). Most batch studies

assessed catalyst performance based on Cr(VI) disappearance; they did not quantify the

chromium end-products of the reaction. The Cr(OH)3 precipitate would likely foul any

catalyst during flow operation if low pH is not maintained, which would be problematic

for long-term performance and regeneration. Further, the performance of these catalysts

in the presence of real waters (i.e. in the presence of other ions and chemical species

present in complex water matrices) has not been studied.

3.2.3. Halogen oxyanions

Of the six halogen elements (e.g. F, Cl, Br, I, At and Ts) in the periodic table, the

oxyanions of chlorine, bromine and iodine are the most common. Different anionic

species can exist depending on halogen oxidation state.[146] For example, chlorine can

exist as hypochlorite (ClO-, Cl oxidation state of +1), chlorite (ClO2-, +3), chlorate (ClO3

-

, +5) and perchlorate (ClO4-, +7) anions.[146] Chlorite (ClO2

-), perchlorate (ClO4-), as

well as bromate (BrO3-), are regulated drinking water contaminants.


In drinking water treatment plants, bromate (BrO3-) can be found as a disinfection by-

product (DBP) arising from the ozonation of bromide-containing source waters (O3 + Br-

87!!

� O2 + BrO-; 2 O3 + BrO- � 2 O2 + BrO3-).[147] A suspected carcinogen, the US EPA

has set a MCL of 0.01 ppm for bromate in drinking water.[19]

Chlorite (ClO2-) and chlorate (ClO3

-) are also DBPs in drinking water caused by

the decomposition of chlorine dioxide, another strong oxidizing agent used in water

treatment.[148] Chlorite can cause anemia and affect the human nervous system; it has a

MCL of 1 ppm.[19] Chlorate was evaluated under the US EPA 2012-2016 Unregulated

Contaminant Monitoring Rule (UCMR-3) and is on the 2016 Contaminant Candidate List

(CCL-4), indicating it can potentially be regulated in the future.[149]

Perchlorate (ClO4-) occurs naturally in arid regions and in potash ore.[150] It also

used in the manufacture of rocket propellant, explosives, and fireworks, and

contamination of water resources arises from improper disposal of these

materials.[20,151] Perchlorate can cause dysfunction of the human thyroid, leading to

metabolic problems, such as heart rate, blood pressure and body temperature

regulation.[151] It was evaluated under the US EPA 2001-2005 Unregulated

Contaminant Monitoring Rule (UCMR-1) and is on the 2009 Contaminant Candidate List

(CCL-3), suggesting a federally mandated MCL is possible. Several states have set

drinking water standards for perchlorate, e.g. Massachusetts has an MCL of 0.002 ppm

and California an MCL of 0.006 ppm.[152]

3.2.3.2. Current technologies

Numerous treatment methods have been explored to remove bromate in water, including

IX, activated carbon adsorption, membrane filtration, biodegradation, chemical reduction,

and photocatalysis.[153–157] Although many of these technologies are still in the

88!!

laboratory evaluation and development stages, some have been tested in the pilot

scale.[158] Perchlorate can be removed from contaminated water through similar

means.[152] A full-scale IX treatment system was successfully operated in California to

lower perchlorate concentration from 10-200 ppb to <4 ppb.[159] The disposal of the IX

waste brine is a costly concern. Chlorite removal is comparatively less studied, and done

only at the laboratory scale.[160][161]

3.2.3.3. Catalytic chemistry for bromine oxyanion

Thermodynamically, the reduction of bromate (BrO3-), chlorite (ClO2

-), chlorate (ClO3-),

and perchlorate (ClO4-) are energetically favorable (Scheme 3.5), but the kinetics for

these transformations are slow.

Scheme 3.5 Reduction reactions of bromate, chlorite, chlorate and perchlorate with the corresponding standard Gibbs free energy values (25 °C, 1 atm, 1 M reactant concentrations, pH 0)

Chen et al. reported that bromate (BrO3-) could be directly reduced over Pd and Pt

catalysts using hydrogen.[37] The role of metallic nanostructures (e.g. Pd, Pt) is to adsorb

and dissociate hydrogen which subsequently reacts with adsorbed BrO3-.[42] This

reaction leads to the formation of the reduced product Br- and water. The oxidized metal

89!!

is then reduced by hydrogen, thus closing the catalytic cycle.[42] Subsequent studies

focused on improving the catalytic activity of monometallic nanoparticles, in particular

Pd, as well as catalyst stability by using different supports including metal

oxides,[37,162–164] silica,[37,165] carbon based materials,[37,42,163,166–171] and

zeolites (Table 3.5).[172,173]

Table 3.5 Performance of metallic nanostructures in the catalytic reduction of bromate

Catalyst

kcat*

(L/ g metal/min) Hydrogen

donor Initial

pH Temperature

(°C) Ref.

1.93% Pd/Al2O3 0.69 H2 5.6 Room temperature

[37]

2% Pd/SiO2 0.004 H2 5.6 Room temperature

[37]

2% Pd/Activated carbon 0.04 H2 5.6 Room temperature

[37]

2% Pt/Al2O3 0.27 H2 5.6 Room temperature

[37]

0.3% Pd/5% CNF/SMF 0.15 H2 6.5 25 °C [166] 2.2% Pd/Mesoporous carbon nitride 4.07 H2 5.6 25 °C [168]

0.1% Pd/Fe3O4 0.69 H2 6 27 °C [174] 2% Pd/Magnetic MCM-41 0.55 H2 5.6 25 °C [175] 1.3% Pd/Core-shell silica 1.1 H2 7 20 °C [165]

0.86% Pd/Ce1-xZrxO2 4.16 H2 5.6 25 °C [162] 1.5% Pd/ZSM-5 0.10 H2 - 25 °C [172]

1.4% Pd 1% Cu/ZSM-5 0.92 H2 - 25 °C [172] 0.92% Pd/Faujasite zeolite Y 0.07 H2 - Room

temperature [173]

1.6% Pd 0.84% Cu/Faujasite zeolite Y 0.92 H2 - Room temperature

[173]


The support composition significantly increases reduction activity, which appears

to relate to the isoelectric point (IEP) of support.[37] It was explained that Pd/Al2O3 (IEP

~8.0) is more active than the Pd/SiO2 (IEP ~2.0) and Pd/C (IEP <2.0), because the Al2O3

is positively charged at the reaction pH of 5.6, thereby electrostatically increasing the

local oxyanion concentration near the Pd domains.[37] Incorporating a second metal,

90!!

such as Cu, appears to increase bromate reduction activity.[171,173] The catalytic

behavior of bimetallic nanostructures for this reaction may be similar to that for other

oxyanions, but this has not been established yet.

3.2.3.4. Catalytic chemistry for chlorine oxyanions

Few have studied chlorite and chlorate reduction. As early as 1995, patent literature

disclosed the use of monometallic Pd and other precious metals for the catalytic reduction

of chlorite/chlorate, as well as bromate anions.[176] Perchlorate catalytic reduction is

difficult to achieve using monometallic Pd, requiring a second metal (in this case,

rhenium, Table 3.6).[45,177–180] Pd adsorbs and dissociates hydrogen to reactive

species (e.g. surface-adsorbed hydrogen atoms) which go on to reduce the oxidized

Re.[178] The role of Re, an oxophilic metal, is to adsorb chlorine oxyanions and abstract

an oxygen atom from perchlorate to form chlorate.[181] Chlorate can undergo the same

process to be reduced to lower-valent chlorine oxyanion. The reaction pathway follows

ClO4- ! ClO3

- ! ClO2- ! Cl-.[45] Using ex-situ X-ray photoelectron spectroscopy

(XPS), Choe et al. concluded that Re likely cycled between a higher oxidation state (+7)

and lower oxidation states (+5/+4 and +1) during perchlorate reduction.[178]

Table 3.6 Performance of metallic nanostructures in the catalytic reduction of perchlorate

Catalyst kcat*

(L/ g metal/min) Hydrogen donor Initial pH Temperature Ref.

5%Re 5%Pd/C 1%Re 5%Pd/C

0.03 0.04 H2 2.9 25 °C [180]

13%Re 4.71%Pd/C 9.4%Re 5%Pd/C 2.9%Re 5%Pd/C

0.04 0.034 0.007

H2 3 23 °C [45]

5%Pd 5.5%Re 0.24 0.098 H2

2.7 3.8 23 °C [179]

91!!


3.2.3.5. Assessment of the technology readiness

Continuous-flow fixed-bed reactors have been studied for the reduction of halogen

oxyanions under simulated conditions.[163,164,166,167,169,170] A life cycle assessment

(LCA) was performed by Yaseneva et al. to assess the potential application of a carbon

nanofiber supported Pd catalyst for bromate removal from industrial wastewater and

natural waters in a plug flow reactor (5 mL water/min).[170] The bromate reduction

activity in industrial wastewater samples was lower than that in the natural water sample

due to the presence of other anions (e.g. Cl-, SO42- and dissolved organic compounds)

which competed for the active sites on the catalyst surface. The treatment process using

carbon nanofiber supported Pd catalyst was more efficient in terms of activity and less

costly and environmentally impactful, compared with the process based on a

conventional Pd/Al2O3 catalyst.

Liu et al. investigated the impact of water composition on the activity of

perchlorate reduction using Re-Pd/C.[180] The perchlorate reduction activity was higher

in simulated brine than that in real IX waste brine. Nitrate in the IX waste brine was

found to deactivate the Re-Pd/C, but the deactivation mechanism is not known.[180]

Choe et al. assessed the environmental sustainability of perchlorate treatment

technologies including IX, bioremediation, and catalytic reduction.[183] They found the

environmental impact of catalytic treatments to be 0.9~30x higher compared to

12%Re 5%Pd/C 0.009 H2 2.7 21°C [178]

7%Re 5%Pd/C 0.3 H2 3 Room temperature [182]

10%Pd/C 0.012 H2 7 20°C [177]

92!!

conventional IX, which could be mitigated with increased catalytic activity and increased

H2 mass transfer.[183] To date, there is no published work on catalytic treatment of

chlorite/chlorate oxyanions at the testbed level.

3.3. Perspective and Research Opportunities

3.3.1. Comparison of reduction catalytic activity for the different oxyanions

Based on the re-calculated values compiled in Tables 3.2-3.6, we found that the reaction

rate constants for NO2-, NO3

-, CrO42-, BrO3

-, and ClO4- reduction using monometallic Pd

catalyst were roughly 1, 0, 10, 0.1 and 0.01 liter per gram metal per min, respectively. In

terms of their reactivity on Pd, the oxyanions were ordered in the following way: CrO42-

> NO2- > BrO3

- >> ClO4- > NO3

-. These oxyanions are broadly less reactive compared to

halogenated organic compounds like trichloroethene, due to the latter's ability to bind

more readily to metal surfaces.[39]

Chaplin et al. compared rate constants for several oxyanion contaminants over

mono- and bi-metallic Pd catalysts and suggested that the X-O bond strength was one

factor in determining reaction rates.[34] Another factor is molecular geometry, which can

can affect the adsorption and activation of the oxyanion to the catalyst surface. NO2- has a

bent shape, different from the trigonal planar shape of NO3-. CrO4

- and ClO4- are

tetrahedral in shape, and BrO3- is trigonal pyramidal. Tetrahedral molecules tend to be

more stable and are more difficult to adsorb, which could be a reason for the low

reactivity of ClO4- compared with BrO3

-, even though the Cl-O bond (197 kJ/mol) is

weaker than the Br-O bond (242 kJ/mol). Considering CrO4- and ClO4

- have the same

93!!

geometry, their bond strengths appear correlated to their relative reactivity. DFT

calculations can provide insights to the effects of bond strength, molecular shape, and

metal-adsorbate interactions on oxyanion reactivity differences.

3.3.2. Applicability of catalytic remediation to other oxyanions

The soluble forms of As (arsenate and arsenite) and Se (selenite and selenite) are

toxic,[184] making the metal form desirable as the reduced end-product. The reduction of

As and Se oxyanions can be achieved using bacteria,[185,186] but this has not been

reported using heterogeneous catalysts. Thermodynamically, it is favorable to reduce

arsenate (AsO43-) to arsenite (AsO3

3-) to elemental arsenic using hydrogen as a reducing

agent (Scheme 3.6).[120] The reduction of selenate (SeO42-) to elemental selenium using

hydrogen is also thermodynamically favored. Catalytic reduction is possible, but fouling

due to solids formation would make this approach problematic with regard to long-term

performance stability and regeneration.

Scheme 3.6 Reduction reaction of arsenate/arsenite to arsenic metal, and selenate to selenium metal with corresponding standard Gibbs free energy values (25 °C, 1 atm, 1 M reactant concentrations, pH 0)

AsO43- + 2.5 H2 + 3 H+ → As (s) + 4 H2O ΔG = -386 kJ/mol AsO4

3-

SeO42- + 3 H2 + 2 H+ → Se (s) + 4 H2O ΔG = -1094 kJ/mol SeO4

2-

AsO43- + H2 → AsO3

3- + H2O ΔG = -112 kJ/mol AsO43-

94!!

3.3.3. Possible catalytic water treatment scenarios using metallic nanostructures

We highlight several opportunities for the use of metallic nanostructure enabled catalytic

systems. A passive in-situ groundwater treatment could be envisioned using permeable

reactive barriers or horizontal-flow treatment wells filled with catalytic material and

supplied with reductant (e.g. formic acid).[187] Pilot scale tests have been carried out in

both US and Europe.[188,189] Although the studies focused on halogenated organic

compounds, the approach and associated reactor design can be applied to treat oxyanion

contaminants as well. For the latter, bench scale and pilot scale studies have been carried

out successfully for nitrate and perchlorate.[89,104,180]

Catalysis is an exciting concept to address the issue of spent IX brine, especially

if the metal catalysts can be designed to be more active in high-salinity water.[104]

Researchers have shown that nitrate brine treatment is feasible using a combined IX-

catalytic treatment system, and can have a lower environmental impact than IX alone.[89]

Current technical challenges of this system include the depressed activity of the catalyst

(due to the high concentrations of salt species), and possible, unquantified metal loss

during operation. Metal nanostructures that can operate at high-salinity conditions

durably are desired.

Catalytic processes could also potentially be used at a consumer, point-of-use

level. A major concern would be the safe use and storage of hydrogen. Alternative safe

and inexpensive reductants (e.g. formic acid) could be used instead of hydrogen gas; a

water electrolysis (as part of an under-the-sink treatment unit) could be used to produce

the required amounts of hydrogen on-demand. Catalysis could also be useful in the

95!!

treatment of decentralized water supplies at the community level, if hydrogen can be

sustainably supplied on a larger scale, e.g., using wind energy[190] or photovoltaics.

3.3.4. Roadmap for deployment of catalysts for oxyanion treatments

The progress of technology of catalytic reduction of oxyanions can be roughly assessed

using technology readiness level (TRL) values, as introduced by the National Aeronautics

and Space Administration (NASA) in the 1970s (Scheme 3.7).[191] Most academic

laboratory studies are at the TRL 1 (e.g. batch reactors), with fewer at TRL 2 (e.g, flow

reactors, LCA and techno-economic analysis, TEA). Of the oxyanions, nitrate treatment

by catalysis is the furthest along with respect to technology development. IX-brine and

fresh water treatments described in previous sections can be characterized to be at least at

TRL 4. There is much room to develop catalyst technologies for the other oxyanions,

which can be enabled by university-industry partnerships.[192]

!

Scheme 3.7 Technology readiness level (TRL) for catalytic reduction of oxyanion contaminants. The colored boxes represent current and past activities in research and development.

3.3.5. Practical implementation issues of catalytic water treatment

Strong progress has been made in developing new catalysts and catalytic reduction

processes for oxyanions in drinking water and waste brine treatment. However, practical

0 1" 2" 3" 4" 5" 6" 7" 8" Ideation Batch

tests Continuous

tests Test bed" Integrated

system Integrated

system Prototype

system Prototype

system Actual system

9"Commercialization

TRL Levels

96!!

application requires the sufficient and low-cost supply of reducing agents, usually

hydrogen. As mentioned earlier, catalytic treatment unit using stored H2 gas will likely

not be adopted for home use, but its electrolytic production is appropriate. The estimated

amount of H2 needed to treat one cubic meter of nitrate-contaminated water (from 100 to

9 mg-N/L) is 0.33 kg H2, assuming 100% selectivity to dinitrogen and 10% H2 utilization

efficiency. Its production would cost ~$1.65 based on electricity priced at

~$0.08/kWh.[193] In comparison, a small IX system (serving a community of <500

people) would cost ~$2.70 to treat the same water to the same treatment goal.[52] The H2

production cost is lower than the IX cost, indicating the margin for cost competitiveness

for a catalytic water treatment, which would need to accommodate other operations and

maintenance costs and capital costs. To further reduce the hydrogen cost, future research

should focus on ways to increase hydrogen utilization efficiency, for example, improving

hydrogen mass transfer.

The high per-mass cost of the precious metals used in the catalyst material could

be of some concern. However, the catalyst itself accounts for only a small fraction of the

overall capital cost. A study by Reinhard and co-workers found that the catalyst was

~10% of the total cost of a treatment unit they designed and constructed, which was

designed to remove trichloroethene from groundwater using Pd/Al2O3.[189] Lowering

the metal content or replacing with an earth-abundant catalyst are helpful, though not

critical, research goals. Instead, the more important opportunity is to design metal

catalysts that perform stably under realistic water conditions and that require less

downtime for regeneration. Long-term studies on the operation and effective regeneration

of the catalyst are lacking.

97!!To make more informed decisions on whether catalysis could be competitive

against the available technologies, catalytic treatment approaches need to incorporate a

technoeconomic analysis of capital and operational costs, and a LCA to address their

environmental footprint. The LCA work on the combined IX-catalyst nitrate system[89]

and a catalytic perchlorate system[183] are a promising start.

3.4. Conclusions

Metal nanostructures can degrade toxic water-borne oxyanions at ambient conditions in

the form of supported precious metal reduction catalysts. The hydrogenation of

oxyanions (nitrite/nitrate, chromate, bromate, chlorite and perchlorate) is exergonic (∆G

< 0), but the reaction can be slow without combining the primary metal with a second

one. An understanding of the surface reaction mechanisms continues to be needed,

especially in water systems (e.g., a drinking water source or spent IX brine) that contain

other chemical species besides the target oxyanion. It can lead to more active, selective,

and durable catalysts (e.g., what are the appropriate metal particle size and shape, and

support composition). Scale-up of catalytic systems will require attention to mass transfer

effects associated with the imposition of intraparticle and interparticle transport rules, and

engineering and reactor design issues associated with hydrogen gas as the reducing agent.

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115!!

Chapter 4

PdAu-catalyzed Oxidation through in situ Generated H2O2 in Simulated Produced

Water

4.1. Introduction

Oil and gas (O&G) production from hydraulic fracturing accounts for more than 50% of

total oil production and 70% of the total gas production in the United States since

2016.[1] One of the critical steps in hydraulic fracturing is to pump a large amount of

fracturing fluid and proppant into the wellbore at high pressure to fracture the shale

formation, and release the oil and gas.[2] Fresh water is the predominant component of

the fracturing fluid, but also contains a mixture of chemical additives used to improve

performance of the hydraulic fracturing process.[3] During production, the fracturing

fluid, formation water, crude oil and/or natural gas are produced back to surface where

they are separated and recovered.

116!!All waters that are recovered from an O&G well are termed "produced water"

with produced water from hydraulic fracturing wells (HF-PW) being especially

problematic due to the number of different contaminants. The composition of HF-PW can

include total organic content (TOC) in a variety of organic compounds, concentrated,

multivalent inorganic salts, naturally occurring radioactive materials (NORM), suspended

solids and bacteria. The complicated compositions make the treatment of produced water

a great challenge for O&G operators.[4,5] Currently, the most common way to manage

HF-PW is to inject it into a disposal well.[6] However, because of the concern of possible

water and soil contamination, the limited availability of disposal wells, and the cost of

transporting water to wells, there is a desire to treat and reuse HF-PW.[7][8]

Many technologies have been proposed and investigated for the treatment of

conventional produced water.[9–11] Ion exchange, reverse osmosis, membrane

distillation and evaporative crystallization have been studied to reduce the total dissolved

solids (TDS) in produced water.[9] Organic compounds, which can contaminate

groundwater and facilitate bacteria growth in produced water, can be removed by

adsorption using activated carbon materials but with mixed results depending on the

technology, process efficiencies and deployment cost.

Oxidation processes have been studied to degrade organic compounds through

chemical oxidation[12] or advanced oxidation processes including electrochemical

methods[13], Fenton oxidation [14], and heterogeneous Fenton-like chemistry.[15]

Electrochemical treatments are limited by the high cost of electrodes and high energy

requirements.[13,16] Fenton oxidation requires the continuous delivery and use of

chemicals (i.e., H2O2 and ferrous iron, Fe2+) and operation at low pH values, such that

117!!

H2O2 is converted into the reactive "OH radical species. Hydroxyl radicals are desirable

for organic oxidative removal due to its higher redox potential (2.80 V vs. SHE) than

H2O2 (1.78 V vs. SHE), but they are highly reactive and have short lifetime (τ < 1 s)

unless generated in situ.[17] Catalytic wet peroxide oxidation replaces the homogeneous

iron catalyst with a heterogeneous supported version, but material stability remains a

challenge and H2O2 input is still required.[18] The on-site production of the oxidant

would be advantageous towards a cost-effective technology for organics removal.

Formic acid is an organic acid commonly found in HF-PW, and is a potential

precursor in the production of H2O2 oxidant. Yalfani et al. reported that H2O2 production

from formic acid and O2 can be accomplished using a supported palladium (Pd)

catalyst.[19] They later demonstrated the degradation of phenol by in situ generated H2O2

combined with ferrous iron [20] and with Pd-Fe catalyst [21]. The iron content generated

"OH radicals from the H2O2 via Fenton/Fenton-like chemistry. The irreversible loss of

ferrous iron activity and iron leaching from Pd-Fe catalyst at acidic conditions require the

continuous addition of active iron reagents. However, these systems would not be

economical for treating the large volumes of HF-PW that is the focus of this study. Iron is

not strictly required to generate "OH radicals from H2O2, as Han et al. reported that a

monometallic gold (Au) catalyst can degrade organic compounds with H2O2 in water at

70 °C.[22]

Bimetallic PdAu catalysts are generally more active (and often times more

selective and resistant to deactivation) than monometallic Pd or Au for various reactions,

including hydrogen production from formic acid [23–26] and H2O2 generation from H2

and O2 [27]. In this work, we studied the generation of H2O2 from formic acid and

118!!

oxygen using PdAu/Al2O3, and compared it to monometallic Pd/Al2O3 and Au/Al2O3,

quantifying H2O2 generation rate and also that of "OH radicals. We inferred the

mechanism of organic compound degradation using phenol as a model compound.

Considering Fe2+ species are present in HF-PW, we studied its concentration effect on

phenol degradation. We also studied the effects of salinity and pH on phenol degradation,

identifying the limits of catalytic activity. Our results show, for the first time, that PdAu

are more active than the monometallic precious metals in degrading phenol in moderately

saline water, using formic acid and O2.

4.2. Experimental

4.2.1. Materials

The bimetallic catalyst containing 1 wt% Pd and 1 wt% Au supported on Al2O3 pellets

("PdAu/Al2O3") was provided by Johnson Matthey. A monometallic Au catalyst

containing 1.2 wt% Au supported on alumina extrudates ("Au/Al2O3") was purchased

from Strem Chemicals. The following chemicals were purchased from Sigma-Aldrich

and used as-received: 1 wt% Pd supported on alumina ("Pd/Al2O3," in the form of a

powder), formic acid (>95%), hydrogen peroxide solution (30 wt% in water),

titanium(IV) oxysulfate solution (~15 wt% in sulfuric acid, >99.99%), phenol (>99%),

1,2-dihydroxylbenzene (>99%), hydroquinone (>99.5%), terephthalic acid (>98%),

iron(II) sulfate heptahydrate (>99%), sodium chloride (>99%), calcium chloride

dihydrate (>99%), magnesium chloride hexahydrate (>99%), magnesium sulfate

heptahydrate (>98%), and sodium bicarbonate (>99.7%). The fluorescent standard, 2-

Hydroxyterephthalic acid (>98%) was purchased from TCI. Sodium hydroxide solution

119!!

(1 N) was purchased from Fisher Scientific. Oxygen gas (99.99%) was purchased from

Airgas. All experiments were conducted using deionized (DI) water (>18 MΩ cm).

4.2.2. Catalyst preparation and characterization

The PdAu/Al2O3 pellets and Au/Al2O3 extrudates were crushed using mortar and pestle

and then sieved into finer powders with particle sizes smaller than 300 µm (US standard

50 mesh). The Pd/Al2O3 powder was sieved to 50 mesh particle sizes.

The images of PdAu/Al2O3, Pd/Al2O3, and Au/Al2O3 samples were obtained using

a JEOL 2010 transmission electron microscope (TEM). The samples for TEM were

prepared by depositing droplets of each catalyst as a methanol-suspended powder onto

200-mesh carbon/Formvar TEM grids, and then dried at room temperature (23 °C). The

number-average particle size distribution for each sample was determined by measuring

at least 200 particles using ImageJ program from the National Institutes of Health (NIH).

Each catalyst was analyzed by powder x-ray diffraction (XRD) using a Rigaku

diffractometer with Cu Kα radiation (1.5418 Å). The data was collected from 35° to 90°.

Metal leaching was assessed after the reaction experiments with highest acidity

(pH 2). The liquid was filtered using a 0.2 µm micro fiber syringe filter, and Pd and Au

concentrations were analyzed by ICP-OES.

4.2.3. H2O2 formation and detection

The H2O2 formation reaction using formic acid and O2 (HCOOH + O2 ! H2O2 + CO2)

was conducted using a screw-cap bottle (250 mL, Alltech) as a semi-batch reactor. The

bottle was capped by a Teflon-silicone septum with one stainless steel needle inserted

120!!

into the liquid as the oxygen inlet, and another syringe inserted just above the liquid level

as the oxygen outlet. In a typical experiment, a 0.2 M (~10,000 ppm) formic acid solution

was prepared from formic acid (820 µL) and 100 mL of DI water. As formic acid was

used as a model organic acid compound, the concentration of formic acid was selected in

the possible concentration range of organic acids (<0.001–10,000 ppm) in produced

water.[28] The resulting solution had an initial pH of 2. The reaction temperature was at

room temperature (23 °C) as measured by a thermometer and stirred using a magnetic stir

bar. The catalyst powder (20 mg PdAu/Al2O3, 20 mg of Pd/Al2O3, or 200 mg Au/Al2O3)

was added to the reactor. The reactions of formic acid conversion and H2O2 formation

were too slow to be accurately quantified if the same amount of Au catalyst was used as

PdAu or Pd catalyst. Though 10 times of Au catalyst than the PdAu or Pd catalyst was

used in the reaction, when comparing the different catalyst, the reaction rate constants of

different catalysts were normalized by the amount of catalyst. Oxygen gas - from an

oxygen cylinder was then continuously bubbled into the reactor at 50 mL min-1, and

stirring rate was adjusted to, and maintained at, 1000 rpm marking the start of the

reaction. Aliquots of the reaction fluid (2 mL) were periodically withdrawn by a 5 mL

plastic syringe using a stainless-steel needle, filtered by a 0.2 µm syringe filter (25 mm,

VWR). and stored in the 2 mL microcentrifuge tube at 4 °C prior to analysis.

Solution [H2O2] was quantified by reaction with a titanium(IV) oxysulfate reagent

to produce a yellow solution of pertitanic acid (Ti4+ + H2O2 + 2 H2O ! H2TiO4 + 4 H+).

This solution was quantified using UV-vis at the wavelength of 405 nm. In a typical

experiment, a 1.0 mL aliquot and 50 µL titanium(IV) oxysulfate was added into a capped

quartz cuvette sequentially and then vigorously shaken. The UV-vis spectrum (365-450

121!!

nm) of the solution was recorded and the concentration of H2O2 was calculated indirectly

using a calibration curve of concentration verses absorbance (at 405 nm).

Formic acid concentration in the aliquot was quantified using an Agilent/HP 1100

series system (Cambridge Scientific Product, Watertown, MA, USA) equipped with an

HPX-87H organic acid column (Bio-Rad, Hercules, CA, USA), a refractive index

detector (RID) and a UV detector (210 nm). The operation conditions for the HPLC were

at 30 °C with 5 mM H2SO4 as mobile phase flowing at 0.3 cm3 min-1. Pure reactants were

used for determining their retention times and concentration calibration curves.

The conversion of formic acid as the reactant XHCOOH was defined by:

!!"##! =!!"##!,! − !!"##!

!!"##!,!

where CHCOOH,0 is the initial formic acid concentration and CHCOOH is formic acid

concentration at each sampling time. Reaction kinetics were modeled as a first-order

reaction with respect to the formic acid concentration[23,29,30]:

−!!!"##!!" = !!"#$×!!"##!

The formic acid efficiency (ηHCOOH) in the phenol degradation experiments was

defined by:

!!"##! =!!!!"#$,! − !!!!"#$!!"##!,! − !!"##!

Yield of H2O2 (YH2O2) was defined as:

122!!

!!!!! =!!!!!

!!"##!,!

Selectivity of H2O2 (SH2O2) was defined as:

!!!!! =!!!!!!!"##!

The H2O2 formation rates (RH2O2 and R’H2O2) was calculated by normalizing H2O2

concentration (CH2O2) with reaction time (t) and the concentration of catalyst metal (Ccat)

or the molar concentration of calculated surface metal (C’surface metal):

!!!!! =!!!!!!×!!"#

!!"!!′!!!! =!!!!!

!×!!"#$%&'!!"#$%

The amount of surface metal was estimated using the magic cluster model,[31–

34] where, for example, the 4 nm monometallic Au and Pd NPs were modeled as clusters

with 7 shells of atoms, and the surface atoms were estimated to be the atoms in the 7th

shell of the cluster.

4.2.4. Detection of hydroxyl radicals

Hydroxyl radicals ("OH) were detected using a fluorescent assay using terephthalic acid

(TA) as a radical trap.[35] As shown in Scheme S4.1, reaction of non-fluorescent TA

with "OH lead to the formation of 2-hydroxyterephthalic acid (HTA) that emits a

fluorescent signal at 425 nm when excited at 315 nm. These experiments were conducted

in the same reactor with same liquid volume (100 mL) and formic acid concentration (0.2

M) except for the addition of TA for a final concentration of 5 mM. Aliquots of the

reaction fluid (0.5 mL) were periodically withdrawn, filtered to remove catalyst, and

123!!

stored in the glass bottle. Next a 0.5 mL sample of 1 M NaOH solution was added to the

0.5 mL of sample containing TA, and the fluorescence spectrum was recorded on a Jobin-

Yvon-Horiba fluorescence spectrometer (FluoroMax 3). The concentration of generated

HTA was calculated based on using the calibration curve generated from HTA

concentration and fluorescent peak intensity. The concentration of "OH radical was

estimated by assuming a 20% trapping efficiency of HTA.[36]

4.2.5. Phenol degradation reaction

Phenol degradation experiments were conducted using the same reaction conditions as

before (100 mL liquid volume, 0.2 M formic acid, 20 mg PdAu/Al2O3, or 20 mg of

Pd/Al2O3, or 200 mg Au/Al2O3, bubbled with 50 mL/min O2) with the exception of the

addition of 1.0 mL of a phenol stock solution (10,000 ppm) into the liquid to make a final

concentration of 100 ppm phenol in the reactor. Formic acid was used as a model organic

acid to represent organic acids in the produced water. Phenol was used as a model

organic compound to represent TOC in the produced water. As phenol was used as a

model organic compound, the concentration of phenol was selected in the possible

concentration range of TOC (<0.1–11,000 ppm) in produced water.[28] In some

experiments, 0.1, 0.5 or 1.0 mL of a FeSO4 stock solution (1,000 ppm Fe(II)) was added

into the liquid to simulate the possible presence of ferrous iron in produced water. To

investigate the effect of pH, the initial solution pH was adjusted in the range of 2 to 9 by

adding 0-2.4 mL of 1 M sodium hydroxide solution into the 100 mL formic acid solution

(0.2 M).

124!!The salinity of the reaction fluid was varied by dilution of simulated HF-PW. The

simulated HF-PW had a total dissolved solids (TDS) content of ~164,000 ppm and

contains primarily Na+, Cl-, and Ca2+ (Table S4.1). Formic acid, phenol, and degradation

products (catechol) were detected and quantified via HPLC. The possible formation of

hydroquinone was also considered and monitored via HPLC, but none was detected in

any of the reactions.

4.3. Results and discussion

4.3.1. H2O2 and hydroxyl radical generation

Fig. 4.1 shows example TEM images of alumina supported PdAu, Pd, and Au NP

catalysts. The NPs had a relatively uniform size distribution, with similar mean diameters

of 3.7, 2.7, and 3.4 nm and standard deviations of 1.2, 1.0, and 1.8 nm, respectively.

These catalysts were evaluated for the synthesis of H2O2 without any pretreatment.

According to the closest calculated NP size with the actual NP size, the Pd NPs were

modeled as magic clusters with 4 shells (Table S4.2), and Au NPs were modeled as

magic clusters with 6 shells (Table S4.3). PdAu NPs were modeled as clusters with 6

shells with the surface shell having 362 atoms (including Pd and Au). Though XRD

results were not able to distinguish the bimetallic PdAu catalyst structure due to the

overlap of Al2O3, Pd and Au peaks (Fig. S4.1), the unclear structure does not affect the

using of magic cluster model (which based on the size) and the calculations of reaction

rate constants (which based on the catalyst weight or the surface atoms amount).

125!!

!

Figure 4.1 (a-c) TEM image (scale bar =50 nm) and (d-f) size distribution of alumina supported PdAu (a, d), Pd (b, e) and Au (c, f) NPs catalysts. Each bar represents percentage of NPs in the diameter range 0.5 nm.

The H2O2 generation profiles using three catalysts are shown in Fig. 4.2a. The

concentration of H2O2 increased to 1.5 mM rapidly using PdAu catalyst, and then

decreased after 30 min of reaction. The H2O2 decomposition rate over PdAu is higher

than its generation rate, consistent with the literature.[37] In the Pd-only case, H2O2

concentration also increased and then decreased; H2O2 decomposition was faster

compared to the PdAu case. The concentration of H2O2 increased continuously using Au

catalyst (using 10 times the amount of catalyst) over two hours without decreasing,

indicating the decomposition of H2O2 is slower over Au.[38] Carrying out the same

reactions in the absence of formic acid did not yield H2O2.

126!!

Figure 4.2 Time profiles for (a) H2O2 concentrations, (b) H2O2 formation rates, and (c) formic acid conversion using PdAu, Pd, and Au catalysts. (d) H2O2 selectivity-formic acid conversion plot. Reaction conditions: 20 mg PdAu/Al2O3 or 20 mg Pd/Al2O3 or 200 mg Au/Al2O3, 23 °C, 100 mL, 0.2 M formic acid, 50 mL min-1 O2, and initial pH = 2.

Since the total amounts of metals charged to the batch reactor and the metallic NP

sizes were different, H2O2 formation rates were normalized on a g-metal and also on a

molsurface metal basis calculated from magic cluster model. H2O2 formation rate (Fig. 4.2b)

decreased greatly with time in the PdAu and Pd cases, while H2O2 formation rate was low

but steady in the Au case. The initial H2O2 formation rate on a gmetal basis using PdAu

catalyst (2.7 mmol-H2O2 g-metal-1 h-1) was 1.5× lower than that using Pd catalyst (4.3

mmol-H2O2 g-metal-1 h-1), but 27× higher than that using Au catalyst (0.1 mmol-H2O2 g-

127!!

metal-1 h-1). On a molsurface metal basis, however, the initial H2O2 formation rate using PdAu

catalyst (1043 mmol-H2O2 molsurface PdAu-1 h-1) was 1.2× higher than Pd (869 mmol-H2O2

molsurface Pd-1 h-1) and 21× higher than that using Au catalyst (50 mmol-H2O2 molsurface Au

-1

h-1), indicating a synergistic effect of the bimetallic combination.

Terephthalic acid (TA) was used as a hydroxyl radical trap to demonstrate

generation of "OH radicals by adding TA to aliquots of the formic acid/O2/catalyst

reaction mixture collected periodically. The fluorescent reaction product, HTA, increased

with time, indicating continuous hydroxyl radical formation (Fig. S4.2). The

concentration of generated HTA at different time intervals was calculated using a

calibration curve generated from HTA concentration and fluorescent peak intensity.

Micromolar amounts of "OH radicals were estimated by assuming a 20% trapping

efficiency of HTA.[36] (Fig. S4.3). On a total metal weight (g-metal) basis, the PdAu

catalyst was ~2× and 30× more active for "OH radical formation than Pd and Au

monometallics, respectively (Table 4.1). On a surface metal atoms (molsurface metal) basis,

the PdAu catalyst was also ~3× and 23× more active for "OH radical formation than Pd

and Au monometallics, respectively.

Table 4.1 Initial H2O2 formation rate, initial formic acid reaction constant and zero-conversion H2O2 selectivity of PdAu, Pd, and Au catalysts.

Catalyst Initial H2O2 formation rate (mmol-H2O2 g-

metal-1 h-1)

Initial "OH radical

formation rate (mmol-OH g-

metal-1 h-1)

Initial formic acid reaction

rate constant (L g-metal-1 h-1)

Zero-conversion

H2O2 selectivity (%)

PdAu 2.7 [1043*] 1.5 [579*] 63.8 [24,627*] 43 Pd 4.3 [869*] 0.8 [162*] 338.0 [68,445*] 11

128!!

Au 0.1 [50*] 0.05 [25*] 1.1 [550*] 83

*Formation rate in the unit of mmol-H2O2 molsurface metal-1 h-1, or reaction rate constant in

the unit of L molsurface metal-1 h-1.

Formic acid concentrations were measured by HPLC (Fig. 4.2c). After 2 h, 1.7%

of the formic acid was converted over 200 mg of the 1.2%Au/Al2O3 catalyst, but

complete conversion was achieved using 20 mg monometallic 1%Pd/Al2O3. The

bimetallic 1%Pd1%Au/Al2O3 catalyst (20 mg), however, had an intermediate conversion

of 45%. The conversion–time profiles for all catalyst compositions followed first-order

kinetics well (Fig. S4.4). The normalized initial formic acid reaction rate constants (both

on g-metal and molsurface metal basis) indicated PdAu was more active in formic acid

conversion than Au but less active than Pd (Table 4.1).

H2O2 selectivity as a function of formic acid conversion was calculated for the

catalysts (Fig. 4.2d). The selectivity decreased with conversion (and reaction time) due to

H2O2 decomposing after its formation. The zero-conversion selectivity was determined

by fitting the experimental selectivity values to a monotonic, third-order polynomial

function and extrapolating to zero formic acid conversion. The zero-conversion

selectivity of H2O2 using PdAu was 43%, which was higher than that for Pd (11%) but

lower than that for Au (83%). At a given formic acid conversion, H2O2 selectivity

decreased in order of Au > PdAu > and Pd.

Gold was the least active catalyst for formic acid conversion, H2O2 formation, and

H2O2 conversion, while Pd was the most active catalyst for formic acid and H2O2

conversion. Intriguingly, formation of H2O2 and "OH radicals followed the order of

129!!

PdAu > Pd > Au on a molsurface metal basis. All three catalysts were stable with no metal

leaching during the reaction according to the ICP measurement.

To understand how the bimetallic catalyst performs differently form the

monometallics, we considered the related reaction of hydrogen production from formic

acid. PdAu bimetallic catalysts have enhanced selectivity to hydrogen compared with Pd,

which is due to the geometric effect of the bimetallic catalyst.[23,24] Formate adsorbs on

the Pd ensembles on Au (or the PdAu neighboring interfacial sites) in a bridge form,

which favors formic acid dehydrogenation (HCOOH ! CO2 + H2) and not the undesired

dehydration pathway (HCOOH ! CO + H2O).[39] We further considered the mechanism

of the direct synthesis of H2O2 from H2 and O2. Pd dissociates H2 while Au adsorbs the

O2, which then hydrogenates to form H2O2 via spillover of H adatoms.[40]

We propose a reaction mechanism for the H2O2 generation through formic acid

oxidation on a PdAu catalyst surface (Scheme 4.1). Formic acid decomposes to adsorbed

hydrogen atoms and CO2 through a HCOO intermediate on the PdAu catalyst surface,

and the adsorbed dioxygen is hydrogenated sequentially by the surface hydrogen to H2O2

through a "OOH intermediate. The "OOH intermediate can further dissociate to form

surface "OH radicals. "OH could be generated from H2O2 decomposition on Au

nanoparticles through a redox cycle (Au0 +H2O2 ! "OH + OH- + Au+; Au+ + H2O2 !

"OOH + H+ +Au0).[41]

130!!

!

Scheme 4.1 Proposed reaction mechanism of formic acid decomposition, surface •OH radical and H2O2 formation PdAu catalyst surfaces

4.3.2. Phenol degradation

PdAu catalyst was tested for the phenol degradation using the same system with Pd and

Au as a control. As shown in the Fig. 4.3a, the phenol concentration decreased ~16%

after 8 h of reaction time and using PdAu catalyst, while the concentration of the product

catechol increased. The total concentration of phenol and catechol decreased and more

peaks showed up in the HPLC spectra (Fig. S4.5), indicating the presence of other

oxidized products, including small organic acids such as acetic acid and oxalic acid.

131!!

Figure 4.3 (a, c, e) Phenol and catechol concentration profiles using (a) PdAu, (c) Pd and (e) Au catalysts; (b, d, f) formic acid and H2O2 concentration profiles using (b) PdAu, (d) Pd and (f) Au catalysts. Reaction conditions: 50 mg PdAu/Al2O3, or 50 mg Pd/Al2O3 or 200 mg PdAu/Al2O3, 23 °C, 100 mL, 0.2 M formic acid, 100 ppm phenol, 50 mL min-1 O2, and initial pH = 2.

132!!The concentrations of formic acid and H2O2 were also measured (Fig. 4.3b). The

formic acid concentration decreased ~90% in 8 hours with a normalized reaction rate

constant of 30.8 L g-metal-1 h-1 (or 11,889 molsurface metal-1 h-1). The reaction constant was

twice as low as compared to that without phenol, which is possibly due to active site

competition between phenol and formic acid. The concentration of H2O2 increased and

then decreased, following the same pattern as the previous case (without phenol

addition). However, the decomposition of H2O2 was slower, which may also be attributed

to the active site competition between phenol and H2O2. Fig. 4.3 shows a 16% conversion

of phenol converted with a 29% generated H2O2 remaining unreacted. Control

experiments conducted by mixing H2O2 (2 mM or 155 mM), phenol and PdAu catalyst.

In the control experiment using the same amount of bulk H2O2 (~2 mM) as the in-situ

generated H2O2 (~2 mM), no phenol degradation was observed. To confirm that H2O2 is

ineffective to degrade phenol, the amount of H2O2 was increased to 155 mM by assuming

~75 mol% of formic acid (200 mM) converted to H2O2 (155 mM). The high

concentration of H2O2 case showed H2O2 is indeed ineffective in phenol degradation in

our system (Fig. S4.6). Another control experiment of phenol degradation using catalyst

and oxygen without formic acid or H2O2 showed no degradation over eight hours, which

suggested oxygen was not capable to oxidize phenol with PdAu catalysts in atmospheric

pressure and room temperature.

The reactant and product profiles were observed using the monometallic Pd (Fig.

4.3c and 4.3d) were similar to those using PdAu catalyst. In contrast, the H2O2 generation

profile (Fig. 4.3e) of the monometallic Au catalyst showed a continuous increase in

concentration, which indicated that H2O2 decomposition is much slower using the Au

133!!

catalyst. This pattern matched with the H2O2 generation experiment in absence of phenol

(Fig. 4.2a).

Table 4.2 summarizes the phenol degradation reaction rate constants and formic

acid reaction rate constants for the three catalysts. The PdAu catalyst showed the highest

phenol degradation reaction rate constant, correlating to the highest •OH radical

formation rate (Table 4.1). The generated highly reactive •OH radicals immediately

reacted with excessive amount of phenol to form catechol. The efficiency of the H2O2

using PdAu catalyst (321.4%) is highest, followed by Au (133.3%) and Pd (17.6%)

catalysts (Table S4.4). The calculated efficiency is larger than 100% because some H2O2

reacted as it formed and therefore cannot be measured ex-situ. The percentage decrease in

initial formic acid reaction rate constant may be attributed to the active site competition

between phenol and formic acid. Significant formic acid reaction rate constant decrease

(~81%) using Pd catalyst indicates stronger adsorption for phenol than for formic acid.

The presence of phenol did not affect the formic acid reaction using Au catalyst,

indicating negligible active site competition between phenol and formic acid on Au

surface. The bimetallic PdAu catalyst showed intermediate formic acid reaction rate

decrease compared with monometallics.

Table 4.2 Initial phenol degradation reaction constant, initial formic acid decomposition reaction constant and formic acid utilization efficiency of PdAu, Pd, and Au catalysts.

Catalyst Initial phenol degradation reaction rate constant (L g-metal-1 h-1)

Initial formic acid reaction rate constant (L g-metal-1 h-1)

PdAu 7.5 [2895*] 30.8 [11,889*] [~52% decrease**] Pd 1.8 [365*] 63.4 [12,856*] [~81%**] Au 0.5 [250*] 1.2 [600*] [~0%**]

134!!

*Reaction rate constant in the unit of L molsurface metal

-1 h-1. **Percentage decrease in initial formic acid reaction rate constant, in the presence of phenol

4.3.3. Effect of ferrous iron

Iron is one of the common cations present in HF-PW.[6] Both ferrous and ferric cations

(Fe(II) and Fe(III), respectively) come mainly from the dissolution of Fe(II)-containing

minerals and the corrosion of carbon steel tubing depending on the water pH.[42] Due to

the highly anoxic conditions downhole, most of the iron remains as Fe(II) ions. The

concentration of iron can vary from a few ppm to several thousand ppm based on

reservoir geochemistry, type of hydrocarbon produced, water pH, and characteristics of

the production well.[43] We expect Fenton chemistry to occur in our reaction system if

Fe(II) is present, which would convert the in situ generated H2O2 into OH radicals at low

pH, thus increasing phenol degradation.[44]

The phenol degradation rates were significantly enhanced with the addition of

ferrous iron (Fig. S4.7). After 8 h, phenol degradation increased from 6.1% to 41.2%

after the addition of 1 ppm ferrous iron with 20 mg PdAu/Al2O3. Similar improvement

was found using 20 mg Pd/Al2O3 (2.2% to 33.2%) and 200 mg Au/Al2O3 (11.7% to

56.4%). The PdAu catalyst showed lower phenol degradation rate than Pd catalyst,

because H2O2 formation rate was higher in the Pd case and the H2O2 was activated by the

ferrous iron to generate additional OH radicals.

The phenol degradation reaction rate constants of PdAu, Pd, and Au catalytic

systems with different concentration of ferrous iron are shown in Fig. 4.4 (on a g-metal

135!!

basis) and Fig. S4.8 (on a molsurface metal basis). Ferrous iron concentration increased the

phenol degradation rate constants for the PdAu and Au catalysts, but it increased to a

much greater extent the phenol degradation rate for the Pd catalyst.

The formic acid conversion of PdAu, Pd, and Au catalytic systems with different

concentration of ferrous iron are shown in Fig. S4.9. The presence of iron sulfate

significantly suppressed the formic acid conversion due to the active sites blocked by the

iron sulfate, while it increased the formic acid efficiency η (Table S4.5). The formic acid

efficiency is highest in the PdAu system in absence of Fe(II) while the formic acid

efficiency is highest in the Au system in presence of Fe(II).

!

Figure 4.4 Phenol degradation reaction constant (on a g-metal basis) in PdAu, Pd, and Au catalytic systems with the presence of different concentration of ferrous iron. Reaction conditions: 20 mg PdAu/Al2O3 or 20 mg Pd/Al2O3 or 200 mg Au/Al2O3, 23 °C, 100 mL, 0.2 M formic acid, 100 ppm phenol, 0-10 ppm Fe(II), 50 mL min-1 O2, and initial pH = 2.

4.3.4. Effect of pH and salinity

The common pH range in the HF-PW is 5 to 9. To test if our system can work in this pH

range, we increased the solution pH by sodium hydroxide addition. As shown in the Fig.

136!!

4.5a, the reaction pH significantly decreased phenol degradation rate; no degradation was

observed above pH 4. As expected, we observed ferrous iron precipitation in the pH

range of 4 to 9, which made the system unable to induce Fenton chemistry.

!

Figure 4.5 Initial phenol degradation reaction rate constant on a g-metal basis (kcat) in water ([TDS]~0 mg/L) (a) at different pH and (b) with different TDS concentrations (corresponding to 1×, 10×, 102×, 103×, 104×, 105×, and 106× dilutions of simulated HF-PW stock solution). Reaction conditions: 20 mg PdAu/Al2O3 or 20 mg Pd/Al2O3 or 200 mg Au/Al2O3, 23 °C, 100 mL, 0.2 M formic acid, 100 ppm phenol, 5 ppm Fe(II), 50 mL min-1 O2.

We next challenged our reaction system by increasing the salinity of the reaction

liquid, while testing at pH 2. The initial phenol degradation reaction constant versus TDS

concentration are shown in Fig. 4.5b (on a g-metal basis) and Fig. S4.10 (on a molsurface

metal basis). The salt concentration significantly suppressed the phenol degradation for the

tested three catalytic systems. No catalysis was detected at the highest salinity value

tested (164,000 ppm). The reason for the reaction rate decrease may be due to the active

site inhibited by adsorption of anions (especially chloride).[45–47]

137!!The Pd-catalyzed phenol degradation rate decreased continuously with increasing

TDS concentration. When the TDS concentration reached 16,400 ppm, Pd was inactive.

The Au-catalyzed phenol degradation rate was comparatively the lowest. It showed some

activity at 16,400 ppm, indicating that Au was more resistant to salt (e.g., Cl)

deactivation than Pd.

PdAu presented contrasting behavior. While it was less active than Pd at 1.64

ppm and below, PdAu showed higher activity compared to Pd at 16.4 ppm and up to

16,400 ppm. It was more active than Au at salinities tested up to 1640 ppm. PdAu was

more resistant to the salinity effect than Pd, which may be attributed to the weaker

chloride chemisorption onto the PdAu bimetallic surface as reported previously.[48] This

unexpected deactivation resistance raises questions as to how the bimetallic structure and

composition contribute to this catalyst property.

4.4. Conclusion

Phenol contained in simulated HF-PW of moderate salinities can be oxidatively degraded

at room temperature and atmospheric pressure, using a combination of oxygen, formic

acid and catalyst (PdAu/Al2O3, Pd/Al2O3, or Au/Al2O3). PdAu/Al2O3 was found to be the

most active catalyst for phenol degradation due to its ability to generate "OH radical most

rapidly. Ferrous ion can improve the generation of •OH radicals which increased the

phenol degradation rate. The bimetallic composition provides improved deactivation

resistance to salinity, as demonstrated by the higher degradation rate of PdAu/Al2O3

compared to that of Pd/Al2O3 and Au/Al2O3. Only one bimetallic composition was tested

138!!

(1 wt% Pd and 1 wt% Au), which motivates further studies with other PdAu

compositions.


Scheme S4.1 Reaction scheme between non-fluorescent terephthalic acid (TA) and hydroxyl radical with the formation of fluorescent 2-hydroxyterepthalic acid. Table S4.1 Composition of the simulated hydraulic fracturing produced water (HF-PW)



pH adjusted with HCl 7.0±0.25 Temperature 20±2.5 C

Constituents Concentration (mg/L) Concentration (mM) Phenol (C6H6O) 100 1.1 Formic acid (HCOOH) 10,000 200 Bicarbonate (HCO3

-, initial) 50 0.82 Calcium (Ca2+) 6,940 173 Chloride (Cl-) 99,719 2813 Magnesium (Mg2+) 520 21.4 Sodium (Na+) 56,000 2436 Sulfate (SO4

2-) 558 5.8 Iron (Fe2+) 5 0.09 Total Diss. Solids (TDS) 163,792 - Ionic Strength - 3,025

139!!

The concentrations above are achieved by adding the following to DI water:

A. 147,181 mg/L NaCl B. 25,457 mg/L CaCl2-2H2O C. 3,436 mg/L MgCl2-6H2O D. 1,411 mg/L MgSO4-7H2O E. 69 mg/L NaHCO3

After adjusting the pH down to 7.0 with HCl, the solution is expected to have an alkalinity of approximately 0.67 meq/L.

Table S4.2 Magic cluster model calculations for different sized Pd particles.

Shell number (n) Number of atoms in shell (natom)a

Total number of atoms per NP (ntot)b

Calculated particle diameter (nm)

1 1 0.28 1 12 13 0.84 2 42 55 1.40 3 92 147 1.96 4 162 309 2.52 5 252 561 3.08 6 362 923 3.64 7 492 1415 4.20

a natom = 10n2 + 2

b ntot = (10n3 + 15n2 + 11n + 3)/3

!

Table S4.3. Magic cluster model calculations for different sized Au particles.




1 1 0.27 1 12 13 0.80 2 42 55 1.34 3 92 147 1.88 4 162 309 2.41 5 252 561 2.95 6 362 923 3.48 7 492 1415 4.02

140!!

a natom = 10n2 + 2

b ntot = (10n3 + 15n2 + 11n + 3)/3

!

Figure S4.1 XRD patterns of PdAu/Al2O3 (blue), Pd/Al2O3 (black), Au/Al2O3 (red) and Al2O3 (pink, from database).

!

Figure S4.2 Fluorescence spectra of aliquots sampled at different time intervals. Reaction conditions: 20 mg PdAu/Al2O3, 23 °C, 100 mL, 5 mM terephthalic acid, 50 mL min-1 O2 and initial pH=2.

141!!

!

Figure S4.3 Estimated •OH generation profile (•OH trapping efficiency ~20%). Reaction conditions: 20 mg 1%Pd1%Au/Al2O3, 23 °C, 100 mL, 5 mM terephthalic acid, 50 mL min-1 O2 and initial pH=2. !

!Figure S4.4 Plot of ln(C/C0) vs. time for PdAu/Al2O3, Pd/Al2O3, and Au/Al2O3 catalysts. Solid lines are the fitted values to the reaction profiles using 1st order kinetics for each catalyst. !

142!!

!

Figure S4.5 Example HPLC spectrum with formic acid, phenol, catechol and small organic acid before and after 8h reaction

!

Figure S4.6 (a) Phenol and catechol concentration profile and (b) H2O2 concentration profile. Reaction conditions: 20 mg PdAu/Al2O3, 23 °C, 100 mL, 0.155 M H2O2, 100 ppm phenol, 50 mL min-1 O2 and initial pH=2.

!

143!!

Table S4.4 Efficiency of H2O2 in the phenol degradation using the alumina supported PdAu, Pd and Au catalysts.

Catalyst Efficiency of H2O2 (%) PdAu/Al2O3 321.4

Pd/Al2O3 17.6 Au/Al2O3 133.3

!

!

Figure S4.7 Phenol degradation profile at different ferrous ion concentrations using (a) 20 mg PdAu/Al2O3, (b) 20 mg Pd/Al2O3, and (c) 200 mg Au/Al2O3. Reaction conditions: 23 °C, 100 mL, 0.2 M formic acid, 100 ppm phenol, 50 mL min-1 O2 and initial pH=2.

!

Figure S4.8 Phenol degradation reaction constant normalized by surface metal atoms (k'cat) in PdAu, Pd, and Au catalytic systems with the presence of different concentration of ferrous iron. Reaction conditions: 20 mg PdAu/Al2O3 or 20 mg Pd/Al2O3 or 200 mg

144!!

Au/Al2O3, 23 °C, 100 mL, 0.2 M formic acid, 100 ppm phenol, 0-10 ppm Fe(II), 50 mL min-1 O2, and initial pH = 2.

!

Figure S4.9 Formic acid conversion profile using (a) 20 mg PdAu/Al2O3, (b) 20 mg Pd/Al2O3, and (c) 200 mg Au/Al2O3. Reaction conditions: 23 °C, 100 mL, 0.2 M formic acid, 100 ppm phenol, 50 mL min-1 O2 and initial pH=2.

!

Table S4.5 Formic acid efficiency in PdAu, Pd and Au systems with 0 ppm, 1 ppm, 5 ppm and 10 ppm Fe(II)

Catalyst ηHCOOH with 0 ppm Fe(II) (%)

ηHCOOH with 1 ppm Fe(II) (%)



PdAu/Al2O3 0.07 0.83 1.91 2.00 Pd/Al2O3 0.01 1.36 2.67 3.40 Au/Al2O3 0.25 3.06 3.50 3.61

!

145!!

!

Figure S4.10 Initial phenol degradation reaction rate constant normalized by surface metal atoms (k’cat) in water ([TDS]~0 mg/L) (a) at different pH and (b) with different TDS concentrations (corresponding to 1×, 10×, 102×, 103×, 104×, 105×, and 106× dilutions of simulated HF-PW stock solution). Reaction conditions: 20 mg PdAu/Al2O3 or 20 mg Pd/Al2O3 or 200 mg Au/Al2O3, 23 °C, 100 mL, 0.2 M formic acid, 100 ppm phenol, 5 ppm Fe(II), 50 mL min-1 O2.

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[44] A. Babuponnusami, K. Muthukumar, A review on Fenton and improvements to the Fenton process for wastewater treatment, J. Environ. Chem. Eng. 2 (2014) 557–572. doi:10.1016/J.JECE.2013.10.011.

[45] K.N. Heck, M.O. Nutt, P. Alvarez, M.S. Wong, Deactivation resistance of Pd/Au nanoparticle catalysts for water-phase hydrodechlorination, J. Catal. 267 (2009) 97–104. doi:10.1016/J.JCAT.2009.07.015.

[46] Brian P. Chaplin, Eric Roundy, Kathryn A. Guy, John R. Shapley, Charles J. Werth, Effects of Natural Water Ions and Humic Acid on Catalytic Nitrate Reduction Kinetics Using an Alumina Supported Pd−Cu Catalyst, (2006). doi:10.1021/ES0525298.

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150!!

Chapter 5

Room-temperature Catalytic Treatment of High-salinity Produced Water at Neutral pH

5.1. Introduction

Hydraulic fracturing technology enabled the recovery of natural gas and tight oil from

unconventional shale and carbonate formations, which has revolutionized the energy

industry over the last two decades.[1] Along with the desired oil and gas products,

hydraulic fracturing produced water (HFPW) surfaces as a highly complex wastewater on

the order of 0.5-4 million gallons per well. Due to a combination of technological

limitations and economic constraints, the majority of this contaminated wastewater is

typically disposed of via direct injection.[2] An increasingly attractive alternative

management practice for HFPW is to reuse it on site for other hydraulic fracturing

operations, particularly in arid or semi-arid regions.[1]

151!!A crucial requirement for reuse prospects is to remove and/or degrade organic

compounds and suppress the growth of bacteria which can lead well souring or the

corrosion of drilling equipment and wellbore tubulars.[3] Currently, organic

contamination is typically addressed through adsorption, electrocoagulation, or

ozonation, but these treatment processes are still hampered by low process efficiency and

high deployment cost.[4]

Advanced oxidation processes driven by heterogeneous catalysis are a promising

method to selectively degrade organic compounds and suppress bacterial growth in these

waters, potentially enabling on-site HFPW reuse. Heterogeneous catalysis directly

converts toxic or problematic contaminants to non-harmful products without generating

separate, more concentrated waste streams as is typical with other conventional water

treatment technologies.[5,6] It is more stable than bioremediation processes, which are

sensitive to operational conditions (e.g., pH and salinity) and which require long

treatment times. As a heterogeneous catalysis approach, catalytic wet air oxidation

(CWAO) uses air or oxygen gas as oxidants to degrade various organic compounds (e.g.,

BTEX, carbohydrate, organic acids) in industrial wastewaters to CO2 and H2O. [7][8] It

uses metal oxide-supported (e.g., alumina, ceria, titania) noble metal catalysts (e.g., Pt,

Pd, Ru), operating at elevated temperatures and pressures (200-300 °C, 20-200 bar) [9].

A less severe process is catalytic wet peroxide oxidation (CWPO), wherein hydrogen

peroxide (H2O2) is used as the oxidant instead of air.[10][11] However, H2O2 usage

requires continuous addition, which increases treatment cost. In situ H2O2 generation

could be promising method to degrade the organic compounds in produced water.[12]

152!!Recently, we found that a bimetallic PdAu catalyst has activity for the oxidative

degradation of a model organic compound in simulated HFPW in the presence of formic

acid (an organic contaminant found in HFPW) and air [3]. We showed that the catalyst

generated H2O2 (and hydroxyl radicals) during the reaction as the oxidant over a wide

range of salinities. The bimetallic catalyst was the most active in terms of initial hydroxyl

radicals formation rate. At moderate salinities (~100-10,000 ppm), PdAu remained active

and showed the highest rate of phenol degradation. The reaction system was restricted to

acidic conditions (pH 3 and lower), however, as none of the catalysts exhibited activity at

pH 4 and higher.

In this work, we studied the generation of H2O2 from hydroxylamine (HA) and

oxygen gas using PdAu/Al2O3, with monometallic Pd/Al2O3 and Au/Al2O3 serving as

comparisons. HA is a widely used reducing agent effective in a wide pH range.[13]

Choudhary et al. reported the generation of H2O2 from HA and O2 using monometallic

Pd and Au catalysts in neutral pH water.[14,15] However, H2O2 generation at high

salinity conditions has not been studied. We studied the effects of salinity (0-100,000

ppm) and pH (5-8) on the generation of H2O2 from HA oxidation in a semi-batch reactor,

using Al2O3 supported PdAu, Pd and Au catalysts. The reaction system was tested for

organics degradation, using phenol as the model compound. We designed, constructed,

and tested a recirculating trickle bed reactor (TBR) that effectively treated 5 L of

simulated produced water (160,000 ppm TDS, pH ~7) containing 100 ppm phenol.

153!!

5.2. Experimental

5.2.1. Materials

The bimetallic catalyst containing 1 wt.% Pd and 1 wt.% Au supported on Al2O3 pellets

("PdAu/Al2O3") was provided by Johnson Matthey. A monometallic Au catalyst

containing 1.2 wt.% Au supported on alumina extrudate ("Au/Al2O3") was purchased

from Strem Chemicals. 1 wt.% Pd supported on alumina ("Pd/Al2O3," in the form of a

powder) was purchased from Sigma-Aldrich. The following chemicals were purchased

from Sigma-Aldrich and used as-received: hydroxylamine (HA) solution (50 wt.% in

H2O), hydrogen peroxide solution (30 wt.% in water), titanium(IV) oxysulfate solution

(~15 wt.% in sulfuric acid, >99.99%), phenol (>99%), 1,2-dihydroxybenzene (>99%),

potassium hydroxide (≥99.97%), phosphoric acid (85 wt.% in H2O, 99.99%), sodium

chloride (>99%), calcium chloride dihydrate (>99%), magnesium chloride hexahydrate

(>99%), magnesium sulfate heptahydrate (>98%), and sodium bicarbonate (>99.7%).

Oxygen gas (99.99%) was purchased from Airgas. All experiments were conducted using

deionized (DI) water (>18 MΩ cm).


All three types of catalysts (PdAu/Al2O3, Pd/Al2O3, and Au/Al2O3) were ground using

mortar and pestle and then sieved into fine powders with particle sizes smaller than 300

µm (US standard 50 mesh). The PdAu, Pd and Au NPs had a relatively uniform size

distribution with similar mean diameters of 3.7, 2.7, and 3.4 nm, respectively, as

characterized by TEM in our previous publication.[3] ICP-OES was used to confirm that

no metal leaching had occurred.

154!!

5.2.3. H2O2 formation in batch reactor

Experiments for studying the H2O2 formation reaction using HA and O2 (NH2OH + O2 !

1.5 H2O2 + 0.5 N2) were conducted using a screw-cap bottle (250 mL, Alltech) as a semi-

batch reactor. The bottle was capped by a Teflon-silicone septum with one stainless steel

needle inserted into the liquid as the oxygen inlet, and another needle inserted above the

liquid level as the oxygen outlet. In a typical experiment, a 10 mM HA solution was

prepared from concentrated (50 wt.% in H2O) HA solution (60 µL) and 100 mL of DI

water. The resulting solution had an initial pH of 9.0 measured by pH meter (Thermo

Scientific). Reactions were conducted at room temperature (23 °C) as measured by a

thermometer inserted into the solution and stirred using a magnetic stir bar (1000 rpm).

The liquid filled reactors were charged with catalyst powder (20 mg PdAu/Al2O3,

20 mg of Pd/Al2O3, or 200 mg Au/Al2O3). The metal to reactant HA molar ratio of PdAu,

Pd and Au catalyst in reaction medium is 1:3446, 1:5300 and 1:985, respectively. Note

that the larger (10×) catalyst mass for the Au/Al2O3 trials was employed because the

observed reaction rates for HA conversion and H2O2 formation were too slow to be

accurately quantified within the set reaction time if the same amount (i.e., 20 mg) of Au

catalyst was used. Reaction rate analysis and catalyst comparisons are normalized by the

mass of catalyst. The reaction was then initiated by bubbling oxygen gas into the reactor

at 50 mL·min-1. Aliquots of the reaction fluid (4 mL) were periodically withdrawn by a 5

mL plastic syringe using a stainless-steel needle, filtered by a 0.2-µm syringe filter (25

mm, VWR), and then stored in the 2 mL microcentrifuge tube at 4 °C prior to analysis.

155!!Bulk H2O2 was quantified through the reaction with a titanium (IV) oxysulfate

reagent to produce a yellow solution of pertitanic acid (Ti4+ + H2O2 + 2 H2O ! H2TiO4 +

4H+). This solution was quantified using UV-vis spectroscopy at the wavelength of 405

nm. In a typical experiment, 50 µL of titanium(IV) oxysulfate was added to a 1.0 mL

aliquot of solution in a capped quartz cuvette. The UV-vis spectrum (365-450 nm) of the

solution was recorded and the concentration of H2O2 was calculated using a calibration

curve of concentration vs. absorbance (at 405 nm).

HA concentration was quantified using a Thermo Scientific Dionex Aquion Ion

Chromatograph (IC) system equipped with a cation-exchange column (Dionex IonPac

CS12A, 4×250 mm) for cation separation and a conductivity detector. The IC operated at

25°C with 20 mM methanesulfonic acid as the cation mobile phase at the flowrate of 1

cm3·min-1.

The conversion of HA, XHA, was defined as:

!!" =!!",! − !!"

!!",!

where CHA,0 is the initial HA concentration and CHA is HA concentration at each

sampling time. Reaction kinetics were modeled as a first-order reaction with respect to

the HA concentration:

−!!!"!" = !!"#$×!!"

!!"# =!!"#$!!"#

156!!Selectivity of H2O2 (SH2O2) was defined as:

!!!!! =!!!!!

!!",! − !!"× 23×100%

5.2.4. Phenol degradation in batch reactor

Phenol degradation experiments were also conducted in the same screw-cap bottle

(250 mL, Alltech) as a semi-batch reactor with 50 mL min-1 O2 flowing through. In a

typical experiment, 1.0 mL of a 10,000-ppm phenol stock solution was added into the

100 mL 10 mM HA solution such that the initial phenol concentration was 100 ppm

(~1.06 mM). Catalyst power (20 mg PdAu/Al2O3, 20 mg of Pd/Al2O3 or 200 mg

Au/Al2O3) was then added to the solution to initiate the reaction. Phenol and its oxidation

byproducts (e.g. catechol) were quantified via HPLC (Agilent/HP 1100).[16] The phenol

removal percentage, Xphenol, was defined as:

!!!!"#$ =!!!!"#$,! − !!!!"#$

!!!!"#$,!

where Cphenol,0 is the initial phenol concentration and Cphenol is phenol

concentration at each sampling time.

Total organic carbon (TOC, expressed in unit of ppm) was measured separately

using a Shimadzu TOC analyzer to qualify and quantify the organic compounds from the

experiments. Examples of the organic samples identified include: phenol, catechol, oxalic

acid, and acetic acid. The decrease of TOC concentration indicates the complete

mineralization of phenol. The TOC removal percentage, XTOC, was defined as:

157!!

!!"# =!!"#,! − !!"#

!!"#,!

where CTOC,0 is the initial TOC concentration and CTOC is TOC concentration at

each sampling time.

To investigate the effect of pH on the phenol degradation, the initial solution pH

was adjusted in the range of 5 to 8 using 8 mM phosphate buffer in DI water. To

investigate the effect of salinity, potassium chloride salt was added to the HA solution

such that the chloride concentration was in the range of 0-100,000 ppm (or 0-3,000 mM).

5.2.5. Quantification of nitrogen byproducts from HA oxidation

It is assumed that the H2O2 formation reaction from HA and O2 generates only N2.[15] To

verify this, we measured for any nitrite (NO2-) and nitrate (NO3

-) byproducts using a

Thermo Scientific Dionex Aquion IC system equipped with an anion-exchange column

(Dionex IonPac AS23, 4×250 mm) and a conductivity detector. The IC operated at 25 °C

with a solution of 4.5 mM Na2CO3 and 0.8 mM NaHCO3 as the anion mobile phase at the

flowrate of 1 mL·min-1.

5.2.6. Phenol degradation in recirculating trickle bed reactor (TBR)

To investigate this reaction system under continuous-flow conditions, we

constructed a recirculating TBR connected to a larger-volume reservoir tank (Scheme

5.1a). The specifications and actual photos of the recirculating TBR are detailed in

Supporting Information (SI). The reactor (empty volume of 0.6 L) was loaded with 250 g

of catalyst pellet (0.5 wt.% Pd/Al2O3 or Al2O3 control sample) diluted with an additional

158!!

100 g inert packing of 2-mm diameter glass beads (borosilicate, Sigma Aldrich). The

catalyst-to-inert packing ratio was 2.5. The Pd/Al2O3 catalyst pellets with cylindrical

shape (4-mm length × 3-mm diameter) were purchased from Riogen Inc. (Table 5.1).

!

!

Scheme 5.1 (a) Schematic of TBR operating in recirculating mode, and (b) corresponding semi-batch reactor model to account for phenol concentration changes in reservoir tank.

Table 5.1 Catalyst pellet characteristics

Parameter Value Pd loading (wt%) 0.5

Pellet Diameter (mm) 3 ± 0.1 Pellet Length (mm) 3-5 Pellet Density (g/L) 1850 ± 150

159!!In a typical experiment, the reservoir tank (9.5 L capacity) was charged with 5 L

of water (TDS of 0 or 160,000 ppm) with 100 ppm phenol, which was delivered at a flow

rate of 0.5 L·min-1. Air was supplied at a rate of 12 L·min-1 from an air compressor

mounted on the rear of the reactor housing. All flowrates were set and monitored using

ball flowmeters. A concentrated HA stream (1 wt%) was delivered via a flow pump at 1.4

mL/min at the top of the distributor head. During operation, the reservoir temperature and

pH were recorded. Samples were collected from the reservoir tank at set time intervals to

quantify phenol concentration and TOC values.

5.2.7. Modeling of overall phenol degradation rate in recirculating TBR

We treated the recirculating TBR+tank system as a semi-batch reactor, in which the

overall reaction (C6H5OH + 2 NH2OH + 7.5 O2 ! 6 CO2 + 6 H2O + N2) is carried out

(Scheme 5.1b). The HA inlet stream increases the reservoir liquid volume with time, and

the air stream flows continuously through the system. !

A mole balance on phenol,

!"#$!!" − !"#$!!"# + !"#$!!"!!"#"$%&'(! = [!"#$!!"!!""#$#%!&'()],

gives 0− 0+ !!!!"#$×! ! = !!!!!"#$!" . Since the moles of phenol (Nphenol) is the

product of phenol concentration (Cphenol) and the liquid volume (V), the mole balance

becomes !!!!"!"×! =!(!!!!"#$!×!)

!" = ! !!!!!"#$!" + !!!!"#$ !"!" . The liquid volume (V)

increases with time due the HA solution flowing at constant volumetric flow rate (v):

! = !! + !×!. Phenol degradation is treated as an irreversible first-order reaction (rphenol

160!!

= kCphenol), with k as overall phenol degradation rate constant (units of min-1). The mole

balance equation readily yielded the following differential equation:

!!!!!"#$!" = !!!!!"#$ −

!!!!"#$×!!!!!×!

Eqn 1.

Phenol degradation rate constant values were determined by collecting phenol

concentration data as a function of time and numerically fitting to the differential

equation using MATLAB.

Catalyst performance decay during the reaction (! = !!!!!!!) was also

considered, to improve the data fit. k0 is the overall phenol degradation rate constant and

kd is the catalyst deactivation rate constant. Substituting the rate equation into the mole

balance equation gives

!!!!!"#$!" = !!!!!!!!!!!"#$ −

!!!!"#$×!!!!!×!

, Eqn 2.

The k0 and kd were determined by fitting the experimental data using MATLAB.


5.3.1. H2O2 generation from HA oxidation in batch reactor

The H2O2 generation profiles for the three catalysts are shown in Fig. 5.1a. All three

catalysts displayed a similar trend with respect to H2O2 generation and consumption of

HA (Fig. 5.1b) within the first hour of reaction, with Pd exhibiting the greatest activity

(reaching 5.9 mM H2O2 after 60 min). Au was the least active (3.2 mM H2O2), and the

bimetallic showing intermediate activity (4.7 mM H2O2). In the absence of HA or O2,

161!!

none of the catalysts generated H2O2. In the absence of catalyst (i.e., only Al2O3 support),

no HA loss was detected and no H2O2 was formed.

!

Figure 5.1 Time profiles for (a) H2O2 and (b) HA concentrations, and (c) H2O2 selectivity-HA conversion plots for PdAu, Pd, and Au catalysts. Reaction conditions: 20 mg PdAu/Al2O3 or 20 mg Pd/Al2O3 or 200 mg Au/Al2O3, 23 °C, 100 mL, 10 mM HA, 50 mL min-1 O2, and initial pH = 9.0.

Since the total amounts of metals charged to the batch reactor and the metallic NP

sizes were different, H2O2 formation rates were compared on a g-metal basis (and also on

a molsurface metal basis, calculated from magic cluster model) (Table 5.2). The initial H2O2

formation rate using PdAu catalyst (64.9 mmol-H2O2 g-metal-1 min-1) was 2.3× lower

than that using Pd catalyst (151.0 mmol-H2O2 g-metal-1 min-1), but 7.6× higher than that

using Au catalyst (8.5 mmol-H2O2 g-metal-1 min-1).

Table 5.2 Initial H2O2 formation rate, initial HA reaction constant and zero-conversion H2O2 selectivity for PdAu, Pd, and Au catalysts.

Catalyst Initial H2O2 formation rate (mmol-H2O2 g-metal-

1 min-1)

Initial HA reaction rate constant (L g-

metal-1 min-1)

Zero-conversion H2O2 selectivity

(%) PdAu 64.9 [25,071a] 15.8 [6,104b] 33

Pd 151.0 [30,516a] 30.0 [6,063b] 41

162!!

Au 8.5 [4,250 a] 1.6 [800b] 26 a Rate constants normalized to surface atoms (in units of mmol-H2O2 molsurface metal

-1 h-1)

b Rate constants normalized to surface atoms (in units of L molsurface metal-1 h-1)

On a molsurface metal basis, the initial H2O2 formation rate showed similar trend,

with PdAu catalyst (25,071 mmol-H2O2 molsurface metal-1

min-1) 1.2× lower than Pd (30,516

mmol-H2O2 molsurface metal-1

min-1) and 5.9× higher than Au catalyst (4250 mmol-H2O2

molsurface metal-1

min-1).

HA concentrations were measured by IC (Fig. 5.1b). After one hour, 90.4% of the

HA was converted over 200 mg of the 1.2%Au/Al2O3 catalyst whereas 94.6% conversion

was achieved using 20 mg monometallic 1%Pd/Al2O3. The bimetallic 1%Pd1%Au/Al2O3

catalyst (20 mg), however, had a highest conversion of 97.8%. The initial HA reaction

rate constant on a gmetal basis using PdAu catalyst (15.8 L g-metal-1 min-1) was 2× lower

than that using Pd catalyst (30.0 L g-metal-1 min-1), but 10× higher than that using Au

catalyst (1.6 L g-metal-1 min-1). On a molsurface metal basis, however, the initial HA reaction

rate constant using PdAu catalyst (6104 L molsurface metal-1 min-1) was slightly higher than

Pd (6063 L molsurface metal-1 min-1) and 7.6× higher than that using Au catalyst (800 L

molsurface metal-1 min-1).

H2O2 selectivity was determined for each catalyst as a function of HA conversion

(Fig. 5.1c). The selectivity generally did not change much with conversion. Extrapolated

to zero HA conversion, the zero-conversion H2O2 selectivities were 41%, 26%, and 33%

for Pd, Au, and PdAu, respectively. These values were not 100%, indicating a parallel

reaction that consumed HA but did not form H2O2 (and presumably formed H2O).

163!!

5.3.2. Phenol degradation in batch reactor

The PdAu catalyst was tested for phenol degradation using the same system with Pd and

Au as controls. Fig. 5.2a shows that the phenol concentration decreased ~11% after one

hour of reaction time when using 20 mg PdAu catalyst. Over the course of one hour

experiment, phenol mass was degraded by ~11% over 200 mg of the Au/Al2O3 catalyst

whereas 21% degradation was achieved using 20 mg Pd/Al2O3. The Pd catalyst exhibited

the highest initial phenol degradation reaction rate constant (Table 5.3), which was 4×

and 50× higher than PdAu and Au on gmetal basis (or 2× and 20× higher than PdAu and

Au on a molsurface metal basis).

Figure 5.2 Time profiles for (a) phenol (solid lines) and TOC (dashed lines), (b) HA, and (c) H2O2 concentration using PdAu, Pd, and Au catalysts. Reaction conditions: 20 mg PdAu/Al2O3, or 20 mg Pd/Al2O3 or 200 mg PdAu/Al2O3, 23 °C, 100 mL, 10 mM HA, 100 ppm phenol (~1.06 mM), 50 mL min-1 O2, and initial pH = 9.

164!!

Table 5.3 Initial phenol degradation reaction constant, initial HA reaction constant and zero-conversion H2O2 selectivity for PdAu, Pd, and Au catalysts.

Catalyst Initial phenol degradation reaction rate constant (L g-

metal-1 min-1)

Initial HA reaction rate constant (L g-

metal-1 min-1)

Zero-conversion H2O2 selectivity

(%) PdAu 0.53 [204*] 14.9 [5751*]

[6% decrease**] 47

Pd 2.15 [436*] 23.8 [4826*] [21% decrease**]

49

Au 0.04 [20*] 1.3 [650*] [19% decrease**]

46

*Reaction rate constant in the unit of L molsurface metal-1 min-1.

**Percentage decrease in initial HA reaction rate constant, in the presence of phenol

There was no decrease in TOC of the liquid samples before 30 min reaction time

using PdAu, indicating that the phenol was converted to mostly intermediate products

(e.g., catechol, small organic acids) (dash lines, Fig. 5.2a). TOC removal by 2.7 wt%

was observed after a 1 h reaction using PdAu catalyst. A similar TOC removal trend was

observed using Au catalyst (2.1%) after 1 h while Pd showed the highest TOC removal of

4.8%.

The HA was completely consumed in one hour with the PdAu catalyst (Fig.

5.2b), with a normalized reaction rate constant of 14.9 L g-metal-1 min-1 (or 5751

molsurface metal-1 min-1) (Table 5.3). The reaction rate constant was 6% lower compared to

that without phenol (Table 5.2), believed to be due to active site competition between

phenol and HA. In the monometallic Pd and Au catalyst cases, 21% and 19% decrease of

165!!

HA reaction rate constant were observed, respectively. The bimetallic PdAu catalyst was

least affected by the presence of the organic contaminant.

H2O2 accumulated during the phenol degradation reaction (Fig. 5.2c): selectivity

gradually decreased as HA converted (Fig. S5.2) indicating the consumption of H2O2 in

the phenol oxidation. Interestingly, the zero-conversion H2O2 selectivity for all three

catalysts were higher compared with the previous cases (Table 5.3), suggesting that

phenol partially blocked active sites that oxidize HA to H2O instead of H2O2.!

5.3.3. Effect of pH and salinity in batch reactor

The common pH range of the HFPW is 5 to 8. To test the performance of the catalytic

oxidation system in this pH range, we adjusted the solution pH using phosphate buffer.

Phenol degradation was observed in all buffered and unbuffered reaction systems (Fig.

5.3a). Compared with the unbuffered system (Fig. 5.2a), the buffered systems showed

greatly decreased phenol degradation reaction rates due to competitive adsorption

between phenol and phosphate species. Increased pH in the buffered systems slightly

decreased phenol degradation reaction rates (Fig. 5.3a), which is consistent with the

formation of reactive oxygen species (e.g. "OH) being less favorable at basic

conditions.[17]

166!!

Figure 5.3 Initial phenol degradation reaction rate constant on a g-metal basis (kcat) (a) in DI water ([Cl-] ~ 0 mg/L) at pH 5-8 buffered by phosphate, and (b) in water with chloride concentrations of 0, 3, 30, 300, 3000 mM (or 0, 100, 1000, 10000, 100000 ppm) buffered at pH 7. Reaction conditions: 20 mg PdAu/Al2O3 or 20 mg Pd/Al2O3 or 200 mg Au/Al2O3, 23 °C, 100 mL, 10 mM HA, 100 ppm phenol, 8 mM phosphate, 50 mL min-1 O2.

We challenged our reaction system by increasing the salinity of the reaction

liquid, buffered at neutral condition to prevent pH drift during the reaction. All tested

three catalytic systems were active even at the highest salinity value tested (3000 mM ~

100,000 ppm) (Fig. 5.3b). The reaction rate decreased with increasing salinity due to

competitive adsorption of phenol with chloride (and phosphate).[18–20]

The Pd catalyst was the most active at all salinity conditions, followed by PdAu

and Au catalysts. In increasing the chloride concentration from 0 to 3000 mM, it dropped

71% in activity, similar to the Au catalyst (75% drop). PdAu dropped 40% in activity,

indicating its greater resistance to chloride interference. The improved salinity resistance

may be attributed to weaker chloride chemisorption onto the bimetallic surface as

reported earlier.[3,18]

167!!

5.3.4. HA oxidation byproduct detection

The NO2- and NO3

- anions were observed as reaction byproducts for all catalysts,

indicating that the common assumption of N2 as the only nitrogen byproduct from using

HA as the hydrogen donor is not valid (Fig. 5.4).[14,15] The total amount of nitrogen

byproducts (mostly NO2- with a trace amount of NO3

-) increased in order of PdAu (4.5%

of initial HA amount) < Au (7.4%) < Pd (11.5%).

Figure 5.4 HA, NO2- and NO3

- concentration profiles using (a) PdAu, (b) Pd and (c) Au catalysts during phenol oxidation. Reaction conditions: 20 mg PdAu/Al2O3 or 20 mg Pd/Al2O3 or 200 mg Au/Al2O3, 23 °C, 100 mL, 10 mM HA, 100 ppm phenol, 8 mM phosphate, 50 mL min-1 O2, and pH ~ 7.

The formation of NO2- and NO3

- byproducts occurred at all salinity conditions,

and selectivity to NO2-/NO3

- byproducts did not change with HA conversion (Fig. S5.1).

Higher chloride concentrations lowered the formation of NO2- and NO3

-, for all three

catalysts (Table 5.4). The smallest byproduct amount occurred for the Au catalyst at 300

mM (0.5%).

168!!

Table 5.4 NO2-/NO3

- byproduct selectivity from HA oxidation in phenol degradation experiments at different Cl- concentrations of 0, 3, 30, and 300, mM (or 0, 10, 100, 1000 ppm).

Catalyst 0 mM Cl- 3 mM Cl- 30 mM Cl- 300 mM Cl- PdAu 4.5% 4.1% 3.5% 2.5%

Pd 11.5% 11.0% 9.3% 5.4% Au 7.4% 5.8% 1.9% 0.5%

5.3.5. Phenol degradation in circulated TBR

In order to demonstrate the potential application of heterogeneous catalysis systems

towards HFPW treatment, we constructed a recirculating three-phase TBR with a 5-L

treatment capacity. We chose to study a commercially available Pd/Al2O3 catalyst

available in large quantities, and operated the three-phase reactor under trickle flow to

reduce mass transfer limitations of the gas phase to the catalyst surface and ensure that

the oxygen was provided in stoichiometric excess.

The control experiment using catalyst support Al2O3 showed 15% phenol

concentration decrease after 48 h due to the HA solution addition (Fig. 5.5). The

measured TOC concentration also expectedly decreased (by 14%). Two water conditions

with active Pd/Al2O3 catalyst were investigated for the flow-through system: DI water

and simulated HFPW case. Simulated HFPW contained other salts besides chloride (TDS

of ~160,000 ppm, Table S5.1). The pH was maintained around 7 using phosphate buffer

in both cases.

169!!

Figure 5.5 Experimental (dots) and modeled (curves) phenol degradation profiles in recirculating TBR in DI water and simulated HFPW. Solid curve and dash curve indicate semi-batch reactor model without (Eqn 1) and with (Eqn 2) considering performance decay, respectively. Reaction condition: 250 g Pd/Al2O3, 23 °C, 100 ppm phenol, 8 mM phosphate, pH~7, 12 L min-1 air.

After correcting for the dilution effect, 46% and 28% phenol converted after 48 h

in DI water and simulated HFPW, respectively. Based on TOC concentration

measurements at the end of the 48-h experiments, 12% and 7% TOC converted to CO2,

respectively. The TOC decrease was less than the phenol concentration decrease, due to

the formation of organic intermediates.[21]

The numerical solutions to the differential equations of the semi-batch reactor

model without (solid curve of Fig. 5.5) and with performance decay (dash curve of Fig.

5.5) were least-square fit to the concentration-time experimental data. Without

considering catalyst performance decay, the phenol degradation rate constant using

Pd/Al2O3 catalyst in simulated HFPW (1.5×10-4 min-1) was 42% of that in DI water

(3.6×10-4 min-1) (Table 5.5). This percentage was consistent with batch reactor results for

170!!

Pd/Al2O3: the phenol degradation rate constant in high salinity (~100,000 ppm) water

(0.11 L g-metal-1 min-1) was 32% of that in DI water (0.34 L g-metal-1 min-1) (Fig. 5.3b).

Table 5.5 Fitted phenol degradation reaction rate constants at DI water and simulated HFPW conditions using semi-batch reactor model

Overall rate constant k (min-1) from Eqn 1

Overall rate constant k0 (min-1) accounting for TBR performance

decay kd (min-1) from Eqn 2 Pd/Al2O3 (DI water) 3.6×10-4 8.1×10-4 kd = 1.0×10-3

Pd/Al2O3 (simulated HFPW) 1.5×10-4 5.0×10-4 kd = 1.4×10-3 Al2O3 (DI water) 0 0 kd = 0

!

When including performance decay in the model, the phenol degradation rate

constant using Pd/Al2O3 catalyst in simulated HFPW (8.1×10-4 min-1) is 62% of that in

DI water (5.0×10-4 min-1) (Table 5.5). The performance decay rate constant (1.4×10-3

min-1) was 1.4 times larger than that at in DI water (1.0×10-3 min-1) (Table 5.5), which

was possibly due to the fouling the catalyst surface (i.e. blocking of the catalytic active

sites) over time by carbonaceous deposits, mainly of condensation/polymerization

byproducts formed from oxidative coupling side reactions.[10,22] The fouled catalysts

can be potentially regenerated by flushing the reactor bed with bleach (e.g. sodium

hypochlorite) solution.[23,24]!

5.4. Conclusion

Phenol degradation was achieved via catalytic advanced oxidation using in-situ generated

H2O2 from a combination of oxygen, HA and catalysts (PdAu/Al2O3, Pd/Al2O3, or

171!!

Au/Al2O3). This reaction works at neutral pH with high salinity (>100,000 ppm or >3,000

mM) in atmospheric temperature and pressure conditions. Dinitrogen gas was the major

product from HA oxidation with a small amount (<5%) of NO2- and NO3

- formed, which

is in contrast to the literature report. A recirculating TBR was constructed and used to

demonstrate as proof of concept that ~28% phenol degradation and ~8% TOC removal

could be achieved in simulated HFPW in 48 hours. TBR experimental results were

consistent with batch experiments. The ratio of phenol degradation rate constants in DI

water and simulated HFPW of TBR tests calculated from a semi-batch reactor model

matched with the rate results of batch systems. This work further demonstrates that

advanced oxidation using heterogeneous catalysts is a promising approach to treat

HFPW.

172!!


!

Figure S5.1 Photograph of the recirculating TBR+tank system including front and back views and component names.

!

Table S5.1 Composition of the simulated hydraulic fracturing produced water (HF-PW)



pH adjusted with HCl 7.0±0.25 Temperature 20±2.5 C

Constituents Concentration (mg/L) Concentration (mM) Phenol (C6H6O) 100 1.1 Formic acid (HCOOH) 10,000 200

173!!

Bicarbonate (HCO3-, initial) 50 0.82

Calcium (Ca2+) 6,940 173 Chloride (Cl-) 99,719 2813 Magnesium (Mg2+) 520 21.4 Sodium (Na+) 56,000 2436 Sulfate (SO4

2-) 558 5.8 Iron (Fe2+) 5 0.09 Total Diss. Solids (TDS) 163,792 - Ionic Strength - 3,025

!

!

Figure S5.2 H2O2 selectivity-HA conversion plot. Reaction conditions: 20 mg PdAu/Al2O3, or 20 mg Pd/Al2O3 or 200 mg PdAu/Al2O3, 23 °C, 100 mL, 10 mM HA, 100 ppm phenol, 50 mL min-1 O2, and initial pH = 9.

5.6. Reference

[1] United States Environmental Protection Agency, Hydraulic Fracturing for Oil and Gas: Impacts from the Hydraulic Fracturing Water Cycle on Drinking Water Resources in the United States, 2016. doi:EPA-600-R-16-236ES.

[2] P. Boschee, Produced and Flowback Water Recycling and Reuse: Economics, Limitations, and Technology, Oil Gas Facil. 3 (2014) 16–21. doi:10.2118/0214-0016-OGF.

[3] Y.B. Yin, K.N. Heck, C.L. Coonrod, C.D. Powell, S. Guo, M.A. Reynolds, M.S. Wong, PdAu-catalyzed oxidation through in situ generated H2O2 in simulated produced water, Catal. Today. (2019). doi:10.1016/J.CATTOD.2019.05.001.

174!!

[4] A. Butkovskyi, H. Bruning, S.A.E. Kools, H.H.M. Rijnaarts, A.P. Van Wezel, Organic Pollutants in Shale Gas Flowback and Produced Waters: Identification, Potential Ecological Impact, and Implications for Treatment Strategies, Environ. Sci. Technol. 51 (2017) 4740–4754. doi:10.1021/acs.est.6b05640.

[5] K.N. Heck, S. Garcia-Segura, P. Westerhoff, M.S. Wong, Catalytic Converters for Water Treatment, Acc. Chem. Res. 52 (2019) 906–915. doi:10.1021/acs.accounts.8b00642.

[6] B.P. Chaplin, M. Reinhard, W.F. Schneider, C. Schu, J.R. Shapley, T.J. Strathmann, C.J. Werth, Critical review of Pd-based catalytic treatment of priority contaminants in water, Environ. Sci. Technol. 46 (2012) 3655–3670. doi:10.1021/es204087q.

[7] K.-H. Kim, S.-K. Ihm, Heterogeneous catalytic wet air oxidation of refractory organic pollutants in industrial wastewaters: A review, J. Hazard. Mater. 186 (2011) 16–34. doi:10.1016/J.JHAZMAT.2010.11.011.

[8] J. Levec, A. Pintar, Catalytic wet-air oxidation processes: A review, Catal. Today. 124 (2007) 172–184. doi:10.1016/J.CATTOD.2007.03.035.

[9] F. Arena, R. Di Chio, B. Gumina, L. Spadaro, G. Trunfio, Recent advances on wet air oxidation catalysts for treatment of industrial wastewaters, Inorganica Chim. Acta. 431 (2015) 101–109. doi:10.1016/J.ICA.2014.12.017.

[10] J.A. Zazo, J.A. Casas, A.F. Mohedano, J.J. Rodríguez, Catalytic wet peroxide oxidation of phenol with a Fe/active carbon catalyst, Appl. Catal. B Environ. 65 (2006) 261–268. doi:10.1016/J.APCATB.2006.02.008.

[11] P. Bautista, A.F. Mohedano, J.A. Casas, J.A. Zazo, J.J. Rodriguez, Highly stable Fe/γ-Al2O3 catalyst for catalytic wet peroxide oxidation, J. Chem. Technol. Biotechnol. 86 (2011) 497–504. doi:10.1002/jctb.2538.

[12] M.S. Yalfani, S. Contreras, F. Medina, J. Sueiras, Phenol degradation by Fenton’s process using catalytic in situ generated hydrogen peroxide, Appl. Catal. B Environ. 89 (2009) 519–526. doi:10.1016/J.APCATB.2009.01.007.

[13] P. Politzer, J.S. Murray, The Chemistry of Hydroxylamines, Oximes and Hydroxamic Acids, 2008. doi:10.1002/9780470741962.ch1.

[14] V.R. Choudhary, P. Jana, S.K. Bhargava, Reduction of oxygen by hydroxylammonium salt or hydroxylamine over supported Au nanoparticles for in situ generation of hydrogen peroxide in aqueous or non-aqueous medium, Catal. Commun. 8 (2007) 811–816. doi:10.1016/J.CATCOM.2006.08.041.

[15] V.R. Choudhary, P. Jana, In situ generation of hydrogen peroxide from reaction of O2 with hydroxylamine from hydroxylammonium salt in neutral aqueous or non-aqueous medium using reusable Pd/Al2O3 catalyst, Catal. Commun. 8 (2007) 1578–1582. doi:10.1016/J.CATCOM.2007.01.003.

175!!

[16] J. Neff, K. Lee, E.M. DeBlois, Produced Water: Overview of Composition, Fates, and Effects, in: Prod. Water, Springer New York, New York, NY, 2011: pp. 3–54. doi:10.1007/978-1-4614-0046-2_1.

[17] H.S. Joglekar, S.D. Samant, J.B. Joshi, Kinetics of wet air oxidation of phenol and substituted phenols, Water Res. 25 (1991) 135–145. doi:10.1016/0043-1354(91)90022-I.

[18] D.-K. Lee, S.-J. Ahn, D.-S. Kim, Mechanistic studies of formation of carbon deposits on supported Pt catalysts during wet oxidation of phenol, in: 2001: pp. 69–76. doi:10.1016/s0167-2991(01)80182-8.

[19] K.N. Heck, M.O. Nutt, P. Alvarez, M.S. Wong, Deactivation resistance of Pd/Au nanoparticle catalysts for water-phase hydrodechlorination, J. Catal. 267 (2009) 97–104. doi:10.1016/J.JCAT.2009.07.015.

[20] Brian P. Chaplin, Eric Roundy, Kathryn A. Guy, John R. Shapley, Charles J. Werth, Effects of Natural Water Ions and Humic Acid on Catalytic Nitrate Reduction Kinetics Using an Alumina Supported Pd−Cu Catalyst, (2006). doi:10.1021/ES0525298.

[21] A. Carrasquillo, J.-J. Jeng, R.J. Barriga, W.F. Temesghen, M.P. Soriaga, Electrode-surface coordination chemistry: ligand substitution and competitive coordination of halides at well-defined Pd(100) and Pd(111) single crystals, Inorganica Chim. Acta. 255 (1997) 249–254. doi:10.1016/S0020-1693(96)05371-6.

[22] J.C. Velázquez, S. Leekumjorn, G.D. Hopkins, K.N. Heck, J.S. McPherson, J.A. Wilkens, B.S. Nave, M. Reinhard, M.S. Wong, High activity and regenerability of a palladium-gold catalyst for chloroform degradation, J. Chem. Technol. Biotechnol. 91 (2016) 2590–2596. doi:10.1002/jctb.4851.

[23] G.G. Rao, G. Somidevamma, Volumetric determination of iron (III) with hydroxylamine as a reducing agent, Fresenius’ Zeitschrift Für Anal. Chemie. 165 (1959) 432–436. doi:10.1007/BF00462146.

[24] K.R. Brown, M.J. Natan, Hydroxylamine seeding of colloidal Au nanoparticles in solution and on surfaces, Langmuir. 14 (1998) 726–728. doi:10.1021/la970982u.

[25] M.N. Hughes, H.G. Nicklin, Autoxidation of hydroxylamine in alkaline solutions, J. Chem. Soc. A Inorganic, Phys. Theor. Chem. (1971) 164–168. doi:10.1039/J19710000164.

[26] A.J.J. Jebaraj, D.R.M. De Godoi, D. Scherson, The oxidation of hydroxylamine on Pt-, and Pd-modified Au electrodes in aqueous electrolytes: Electrochemical and in situ spectroscopic studies, Catal. Today. 202 (2013) 44–49. doi:10.1016/j.cattod.2012.03.038.

176!!

! !

177!!

Chapter 6

Towards Glucuronic Acid through Oxidation of Methyl-glucoside Using PdAu Catalysts

6.1. Introduction

Biomass-derived carbohydrates are a promising feedstock due to their natural abundance.

[1,2] Value-added chemicals can potentially be produced from carbohydrates by applying

dehydration, hydrogenation, and oxidation treatments.[1] Carboxylic compounds from

the oxidation of carbohydrates is of particular interest.[3,4] One example is glucuronic

acid, a precursor for pharmaceutical chemicals (e.g. heparin and hyaluronic acid) and

drink additives (e.g. glucuronolactone).[5] Current commercial processes to produce

glucuronic acid include the aerobic enzymatic oxidation of glucose by Ustulina deusta

bacteria and Bacterium industrium var. Hoshigaki [6]. However, these suffer from low

productivity. Efforts have been made to improve the productivity by using homogeneous

catalysts [7], but their separation from the product is problematic. Heterogeneous

178!!

catalysts are widely investigated due to their fast biomass conversion, and are, by

definition, readily separable from reaction mixtures [8].

In the liquid-phase catalytic oxidation of glucose over heterogeneous platinum

catalysts, selectivity to glucuronic acid (i.e. glucose oxidized at the C6 primary alcohol

group) is low, forming mostly gluconic acid (i.e. glucose oxidized at the C1 carbonyl

group) instead.[9] This highlights a problem with glucose as a biomass feedstock for

glucuronic acid [10,11]: its selective conversion to the desired product is challenging, due

to the competing functional groups. Protecting groups on the glucose ring can be used to

control selectivity, as reported recently, for example, by Chen et al. [12]. The protection

of the oxidatively more active C1 carbonyl groups was reported to increase the selectivity

toward the glucuronate structure by the oxidation of C6 primary alcohol groups. [13–16]

Acid hydrolysis can be subsequently used to remove the protecting group to generate the

glucuronic acid [15].

However, the reported examples of heterogeneously catalyzed oxidation of

protected glucose were not straightforward to carry out; there is ample room to improve

catalyst activities and glucuronic acid selectivities [13–16]. van Dam et al. studied

glucose 1-phosphate oxidation at 30 °C and pH 9 using activated carbon supported

monometallic platinum (Pt/C).[13] The authors reported ~70% conversion of 0.1 M

glucose 1-phosphate to glucuronic acid 1-phosphate at ~60% selectivity using 40 g/L

5wt%Pt/C after 23 hours. Schuurman et al. studied MG oxidation using a similar catalyst

at the reaction conditions of 20-40 °C and pH 7-10.[14] They reported ~80% conversion

of 0.5 M MG and ~70% selectivity to MGA after 28 h at 35 °C and pH 7. Catalyst

deactivation was observed in both cases though, due to platinum over-oxidation. Yuan et

179!!

al. studied the MG oxidation using supported palladium at 70 °C and pH 9.[15,16] The

authors found that the commercial carbon supported palladium (Pd/C) catalyst was

inactive in MG oxidation, but a complex metal oxide (e.g., La0.5Pb0.5Mn0.9Sn0.1O3)

supported palladium led to ~76% yield of glucuronic acid.

Bimetallic catalysts (e.g. PdPt, PdAu, and PtAu) have enhanced activity,

selectivity and/or stability compared with monometallic catalysts for aqueous alcohol

oxidation, which is commonly attributed to a combination of geometric and electronic

effects.[17,18] PdAu is one of the most widely studied bimetallic catalysts for primary

alcohol oxidation. Silva et al. reported more than 5 times improvement in activity using

Au@Pd core-shell NP catalysts compared to monometallic Au and Pd for the oxidation

of benzyl alcohol, for example.[19] Hutchings's group prepared carbon-supported PdAu

alloy NPs catalysts and found they gave ~80% selectivity to glyceric acid from glycerol

oxidation and were 50% more active than supported monometallic Pd and Au NPs.[20]

Our group has investigated structure–property relationships of Pd-on-Au NPs for the

oxidation of glycerol; the catalytic NPs exhibited volcano-shaped activity dependence on

Pd surface coverage, and had ~10 times higher activity than monometallic Pd or Au

catalysts [21,22]. Also, these Pd-on-Au NPs showed improved resistance to deactivation

from Pd over-oxidation [21,23].

In this work, we explored the oxidation of MG using Pd-on-Au NP model

catalysts to generate MGA as a precursor to glucuronic acid (Scheme 6.1). We studied if

these materials also exhibited volcano-shape oxidation activity dependence on Pd surface

coverage. We quantified MGA selectivity and yield in relation to Pd surface coverage.

180!!

!

Scheme 6.1 Direct synthesis of glucuronic acid via biocatalyzed glucose oxidation (red path), and indirect synthesis of glucuronic acid via metal-catalyzed MG oxidation (blue path).

6.2. Experimental


The carbon-supported NP catalysts were synthesized as reported previously.[21,24] The

detailed material usage, preparation procedures and catalyst characterization were

provided in Supplementary Information.

6.2.2. Catalytic testing

MG oxidation was conducted using a screw-cap bottle (100 mL, Alltech) as a semi-batch

reactor. The bottle was capped by a teflon-silicone septum with one stainless steel needle

inserted into the liquid as oxygen inlet, and a shorter one above the liquid as gas outlet.

MG was added to 50 mL DI water at a concentration of 0.1 M. The solution pH was

181!!

adjusted to 13 by adding 80 mg NaOH to the solution. The reactor was placed in an oil

bath on a heating plate to control the temperature at 50 °C and magnetically stirred. After

the temperature of liquid stabilized (~30 min), O2 flow (100 mL min-1) was started, the

stirring rate was increased to 1200 rpm, and 10 mg catalyst was added to start the

reaction.

Aliquots of the reaction fluid (1 mL) were periodically withdrawn by a 5 mL

plastic syringe via a stainless steel needle, filtered by a 0.2 µm syringe filter (25 mm,

VWR), stored in the 1 mL clear shell vials (8 × 40 mm, VWR), and analyzed by ion-

exclusion high-performance liquid chromatography (HPLC).

A Shimadzu Prominence SIL 20 system (Shimadzu Scientific Instruments, Inc.,

Columbia, MD, USA) equipped with an HPX-87H organic acid column (Bio-Rad,

Hercules, CA, USA), a refractive index detector (RID), and a UV detector (210 nm) was

used to separate and detect the reaction products. The operation conditions for the

Shimadzu HPLC were at 42 °C with 30 mM H2SO4 as mobile phase flowing at 0.3 cm3

min-1.

Pure reactant MG and reaction products (MGA, glyceric acid, oxalic acid,

glycolic acid, formic acid, acetic acid, and lactic acid) standards were used to determine

retention times, and concentration-peak area calibration curves were prepared in the

range of 0 to 0.2 M. A slight loss in liquid volume due to water evaporation was observed

during the reaction (~0.65 mL volume loss after 1 h at 50 °C), for which the measured

concentrations were corrected during calculation.! pH was checked before and after

reaction, and no significant pH change was observed (<0.4).

182!!The conversion of MG (XMG) was defined as

!!" =!!",! − !!"

!!",!

where CMG,0 is the initial MG concentration and CMG is the MG concentration at

each sampling time. The MG oxidation reaction over the whole reaction time (8 h) cannot

be modeled as pseudo first-order reaction since the generated products can also react on

the catalyst surface competing with the MG oxidation. Due to the low amount of reaction

products at beginning of reaction, MG oxidation was the dominant reaction. Thus, initial

first-order reaction rate constants were calculated using data collected in the first 2 h:

−!!!"!" = !!"#$×!!"

The initial apparent first-order reaction rate constant kmeas (with units of h-1) was

obtained from the following equation:

− ln !!"!!",!

= !!"#$×!

Initial turnover frequency, normalized to the estimated moles of exposed catalytic

surface atoms, (TOF, with units of mol-MG mol-surface-atom-1 h-1) was given by:

!"# = !!"#$×!!"!!"#$%

where Cmetal is the surface metal content of the catalysts. The amount of surface

metal was estimated using the magic cluster model,[25–28] where the 4 nm carbon-

supported monometallic Au and Pd NPs were modeled as clusters with 7 shells of atoms,

183!!

and the surface atoms were estimated to be the atoms in the 7th shell of the cluster. For

carbon-supported Pd-on-Au NPs with Pd surface coverages less than 100 sc%, all Pd

atoms were assumed to be surface atoms in the 8th layer and uncovered Au atoms in the

7th layer were also counted as surface atoms. For Pd surface coverages greater than 100

sc%, the surface atoms were the Pd atoms in the 9th layer and the exposed Pd atoms in 8th

layer. The charge amounts of catalysts with different surface coverage to reactor are

shown in Table S6.4.

To quantify the percentage of reactant MG converted to the desired product MGA

for different surface coverage catalysts, yield (YMGA) of MGA using each catalyst was

defined as:

!!"# =!!"#!!"

where CMGA and CMGA is the MGA and MG concentration, respectively.

MGA selectivity (SMGA) was defined as:

!!"# =!!"#

!!",!−!!"


6.3.1. Catalyst structure

Fig. S6.1a shows a TEM image of carbon-supported 80 sc%. Pd-on-Au NPs. The dark

black spheres were the NPs while the gray regions was the carbon support. The NPs had

a narrow size distribution, with a mean diameter of 4.2±0.6 nm (Fig. S6.1b). Elemental

184!!

analysis via ICP-OES of Pd-on-Au NPs with calculated 0, 30, 80, and 150 sc% (Table

S6.5) confirmed that actual metal content was close (within 2%) to calculated values.

From our previous studies on nanostructure analysis [29,30], the Pd-on-Au NPs have a

Pd-rich shell and a Au-rich core. At low surface coverage (<30 sc%), Pd atoms are

distributed as scattered atoms, and at medium surface coverage (30-80 sc%), Pd are

found predominantly as two-dimensional (2D) ensembles on the Au surface. At higher

surface coverages (>80 sc%), Pd additionally form three-dimensional (3D) ensembles.

The tested 80 sc% Pd-on-Au/C catalysts were stable with no detectable Au or Pd (<50

ppb) in the filtered solution after MG oxidation.

6.3.2. Effect of Pd surface coverage on catalyst activity of MG oxidation

Pd-on-Au NPs with surface coverages from 30-300% as well as monometallic Au/C�

Pd/C catalysts and activated carbon were tested for MG oxidation. The concentration–

time profiles of MG oxidation reaction showed that increasing Pd surface coverage from

0% to 80% led to higher MG conversion (Fig. 6.1a). The highest MG conversion of 92%

after 8 h was achieved using the 80 sc% Pd-on-Au catalyst. The conversions for 0 sc%

(monometallic Au), 30 sc% and 50 sc% Pd-on-Au catalysts after 8 h were 32%, 38% and

75%, respectively.

Materials with Pd surface coverages >80 sc% showed decreasing MG conversion

in the same reaction time period (Fig. 6.1b). The conversions for 100 sc%, 150 sc% and

300 sc% Pd-on-Au catalysts after 8 h were 71%, 66% and 40%, respectively. Both

synthesized and purchased monometallic Pd/C catalysts tested showed no activity for

MG oxidation after 8 h of reaction, which may due to the fast oxidation of Pd surface in

185!!

oxygen-rich condition.[31] This finding was consistent with the results reported in

literature.[16] Carrying out the same reactions using activated carbon did not show the

conversion of MG.

!

Figure 6.1 (a) Concentration-time profiles for 0, 30, 50 and 80 sc% Pd-on-Au/C catalysts and (b) concentration-time profiles for 80, 100, 150, 300 sc% Pd-on-Au/C and Pd/C (both synthesized and purchased) catalysts. Reaction conditions: 50 °C, 50 mL, 0.1 M MG, 0.4 M NaOH, pH = 13, and 100 mL min-1 O2.

The initial reaction rate constants of Pd-on-Au NPs with varying surface

coverages were calculated (Fig. S6.2). The initial TOF of the reaction using Pd-on-Au

NPs was then calculated by normalizing the initial reaction rate constant by the

concentration of surface atoms (Table S6.6). The initial TOF in the range of 0 to 300 Pd

sc% showed a volcano-shaped Pd surface coverage dependence (Fig. 6.2). All bimetallic

Pd-on-Au/C catalysts showed improved catalyst activity compared with monometallic

Au/C and Pd/C catalysts. The 80 sc% Pd-on-Au/C catalyst had the maximum activity for

MG oxidation reaction. With a relatively small Pd loading (0.20 wt% Pd), this

186!!

composition had an initial TOF value (413 h-1) that was >5 times higher than that of

Au/C (80 h-1).

Figure 6.2 Plot of initial TOF with Pd surface coverage. Reaction conditions: 50 °C, 50 mL, 0.1 M MG, 0.4 M NaOH, pH = 13, and 100 mL min-1 O2.

The volcano behavior of Pd-on-Au NPs for this reaction was similar to their

behavior for glycerol oxidation reaction.[21] Previous XAS results showed the Pd surface

species at surface coverages below the volcano peak were in the form of 2D ensembles,

which were relatively resistant to oxidation; and the Pd species above the peak were in

the form of 3D ensembles, which were susceptible to oxidation, resulting in lowered

catalyst activity.[21,23]

6.3.3. Effect of Pd surface coverage on MGA yield from MG oxidation

In the MG oxidation using the 80 sc% Pd-on-Au/C catalyst, the concentration of the

desired product MGA increased from 0 to 45 mM over 8 h (Fig. 6.3). At the same time,

the concentration of small organic acids (e.g. glyceric acid, oxalic acid, glycolic acid,

0

50

100

150

200

250

300

350

400

450

500

0 50 100 150 200 250 300 350

Initi

al T

OF

(mol

-MG

mol

-sur

face

-ato

m-1

h-1

)

Pd surface coverage (sc%)

0

50

100

150

200

250

300

350

400

450

0 50 100 150 200 250 300 350

Initi

al T

OF

(mol

-MG

/mol

-sur

face

ato

m/h

)

Pd surface coverage (sc%) Pd

187!!

formic acid, acetic acid, and lactic acid) were found to increase over time. These products

were generated from the oxidative dehydrogenation of secondary hydroxyl groups in

MG, which led to the cleavage of C-C bonds and the generation of the shorter chain

compounds. The MGA selectivities did not vary with Pd-on-Au composition, which was

roughly 55-57% at 20% MG conversion, higher than that for Au NPs (~50% at 20% MG

conversion) (Fig. S6.3).

Figure 6.3 Reaction products and carbon balance of MG oxidation using 80 sc% Pd-on-Au/C catalyst. Reaction conditions: 50 °C, 50 mL, 0.1 M MG, 0.4 M NaOH, pH = 13, and 100 mL min-1 O2.

By dividing the sum of the carbon content of the HPLC-detected compounds over

the initial carbon content of MG, the carbon balance for the 80 sc% Pd-on-Au/C catalyst

was ~89% at the end of the 8 h reaction (Fig. 6.3). The decreasing carbon balance

suggested the generation of CO and/or CO2 undetected though HPLC, consistent with

glycerol oxidation reported in literature. [21,32]

The concentration of MGA increased with reaction time for all catalysts,

indicating no additional reaction of MGA with further MG conversion. The highest

188!!

concentration of MGA (45 mM) was observed using 80 sc% Pd-on-Au catalyst (Fig. 6.4).

The yield of MGA at reaction time of 8 h (calculated by dividing the concentration of

generated MGA by initial concentration of MG) showed that the highest MGA yield

(~46%) was achieved at the 80% Pd surface coverage, which was >2 times greater than

that for Au/C (20%).

!

Figure 6.4 Plot of MGA yields (at the end of the 8-hr reaction) with Pd surface coverage (black squares). Glucuronic acid yield from glucose oxidation using 80 sc% Pd-on-Au NPs (blue cross). Reaction conditions: 50 °C, 50 mL, 0.1 M MG (or glucose), 0.4 M NaOH, pH =13, and 100 mL min-1 O2.

For comparison, glucose oxidation at the same reaction conditions was conducted

using the 80 sc% Pd-on-Au composition. The conversion of glucose was much faster than

MG oxidation (Fig. S6.4). Glucose was completely oxidized in two hours and yielded

100% of the C1 oxidized product gluconic acid, consistent with literature.[33] The desired

C6 oxidized product (i.e. glucuronic acid) was not detected during the reaction.

189!!

6.4. Conclusion

Carbon supported Pd, Au and Pd-on-Au NPs were tested for MG oxidation. Carbon

supported bimetallic Pd-on-Au NPs exhibited a volcano-shape dependence of activity on

Pd surface coverage, while monometallic Pd/C catalysts were inactive for the reaction.

All Pd-on-Au NP catalysts were more active than monometallic Au/C, with maximum

activity and yield to MGA observed over the 80 sc% Pd-on-Au/C. This study suggests

carbon supported Pd-on-Au NPs are promising catalysts for the selective oxidation of

primary alcohol group in MG for producing glucuronic acid.


6.5.1. Materials

Tetrachloroauric(III) acid (HAuCl4·3H2O, 99.99%), palladium(II) chloride (99.99%),

tannic acid (>99.5%), potassium carbonate (>99.5%), D-(+)-glucose (≥99.5%), D-

gluconic acid sodium salt (≥99%), D-glucuronic acid (≥98%), methyl β-D-

glucopyranoside (methyl-glucoside or "MG" for short, ≥99%) and activated carbon

(Darco G-60) were purchased from Sigma-Aldrich. Methyl-glucuronic acid (1-O-methyl-

β-D-glucuronic acid sodium salt or "MGA" for short, ≥99%) was purchased from Santa

Cruz Biotechnology. Commercially available 1 wt% Pd/C was purchased from Alfa

Aesar. Trisodium citrate (>99.5%), sodium hydroxide solution (1 N), sulfuric acid

solution (0.1 N) and HCl solution (1 N) were purchased from Fisher. Oxygen gas

(99.99%) and hydrogen gas (99.99%) were purchased from Matheson Tri-Gas. All

experiments were conducted using deionized (DI) water (>18 MΩ cm).

190!!

6.5.2. NP Synthesis

Briefly, for Au NPs 0.05 g tannic acid, 0.018 g potassium carbonate and 0.04 g trisodium

citrate were added to 20 mL of DI water. This solution and a second flask containing 80

mL of 315 mM HAuCl4 solutions were heated to 60 °C at which point the first solution

was added to the second. The solution was heated to boiling for 2 min, then cooled to

room temperature and stored at 4 °C. The calculated Au NP concentration was 1.07 ×

1014 NPs per mL using a magic cluster model of 7 shells (Table S6.1).

A similar procedure was followed to synthesize Pd NPs except that the HAuCl4

solution was replaced with a H2PdCl4 solution (12 mL of 2.49 mM H2PdCl4 solution

diluted in 68 mL of H2O) and 25 min boiling time. The resulting sol had a calculated

particle concentration of 1.27×1014 NPs/mL (31.8 mg Pd/L) assuming complete reduction

of the Pd salt.

To synthesize Pd-on-Au NPs with different surface coverages (30-300 sc%,),

specific volumes of 2.49 mM H2PdCl4 solution were added to 100 mL of Au NPs (Table

S6.2). The mixture was bubbled with H2 gas at a flow rate of 200 mL min-1 for 30 min.

Metal content of Pd-on-Au NPs with varying calculated surface coverages is shown in

Table S6.3.

Table S6.1 Magic cluster model calculations for different sized Au particles.




1 1 0.28 1 12 13 0.84 2 42 55 1.40

191!!

3 92 147 1.96 4 162 309 2.52 5 252 561 3.08 6 362 923 3.64 7 492 1415 4.20 8 642 2057 4.76 9 812 2869 5.32 10 1002 3871 5.88

a natom = 10n2 + 2

b ntot = (10n3 + 15n2 + 11n + 3)/3

Table S6.2 Synthesis amounts of Pd precursor and calculated metal content of 4 nm Pd-

on-Au NPs.a

Pd surface coverage (sc%) Volume of H2PdCl4 precursor (mL)b

Pd metal content (mol%)c

30 1.38 12.0 50 2.31 18.5 60 2.77 21.4 80 3.69 26.6 100 4.62 31.2 150 7.55 42.5 300 15.10 63.4

a All calculations are based on the magic cluster model.

b Volumes shown are for addition of a 2.49 mM H2PdCl4 solution to 100 mL of Au NP sol.

c Pd metal content of one Pd-on-Au NP.

Table S6.3 Metal content of Pd-on-Au NPs with varying calculated surface coverages

Pd surface coverage (sc%) wt% of Pd wt% of Au 30 6.8 93.2

192!!

50 10.9 89.1 60 12.8 87.2 80 16.3 83.7 100 19.6 80.4 150 28.5 71.5 300 48.3 51.7

6.5.3. Carbon-supported catalyst preparation

The carbon support helped to stabilize the NPs while the unsupported colloidal

nanoparticles was unstable and precipitated out of suspension at high pH (~13). 0.5 g of

activated carbon support was added to a 0.1 M sulfuric acid solution (pH = 1) and stirred

at 500 rpm for 30 min. For a carbon-supported Au catalyst with a loading of 1 wt% Au

(Au/C), 100 mL of Au NP sol (49.7 mg Au per L) was added to the acidified activated

carbon solution. The mixture was stirred for 2 h at 700 rpm, then filtered and washed

with DI water until the pH of filtrate remained constant (pH~6). The carbon slurry was

dried in a drying oven at 105 °C overnight. The material was then stored in the dark at

ambient condition (23 °C and 1 atm). Both untreated and treated activated carbon were

used for control experiments. Carbon-supported with 1 wt% Pd (Pd/C) was prepared

similarly by mixing 157 mL of Pd sol (31.8 mg Pd per L) with 0.5 g of activated carbon.

For carbon-supported Pd-on-Au catalysts, the immobilization procedure was the

same except that as-synthesized Pd-on-Au sols were used in place of the Au sol. The Au

loading for all Pd-on-Au/C catalysts was kept constant at 1 wt%, while the Pd loading

varied according to the Pd surface coverage. Specifically, 30, 50, 80, 100, 150 and 300

193!!

surface coverage (sc%) Pd-on-Au/C catalysts have calculated Pd loadings of 0.025,

0.074, 0.123, 0.147, 0.245, and 0.938 wt%, respectively.

6.5.4. Catalyst characterization

6.5.4.1. Transmission electron microscopy (TEM)

The images carbon-supported 80 sc% Pd-on-Au NPs samples were obtained using a

JEOL 2010 transmission electron microscope (TEM). The samples for TEM were

prepared by depositing methanol-suspended carbon supported materials onto 200-mesh

carbon/Formvar TEM grids, and then dried at room temperature (23 °C). The number-

average particle size distribution, particle size mean and standard deviation for 80 sc%

Pd-on-Au NPs sample was determined by measuring at least 200 particles using ImageJ.

6.5.4.2. Inductively Couples Plasma Optical Emission Spectrometer (ICP-OES)

To assess the metal loading on carbon support, catalyst powder was mixed with aqua

regia (HCl/HNO3=3/1(v/v)) and digested at room temperature (23 °C) for 24 h. The

solution was treated with a 0.2-µm filter before the analysis of Pd and Au loadings using

Perkin Elmer Optima 8300 Inductively Couples Plasma Optical Emission Spectrometer

(ICP-OES). Metal leaching was assessed after the MG oxidation experiments. The liquid

was filtered using a 0.2 µm micro fiber syringe filter, and Pd and Au concentrations were

analyzed by ICP-OES.

Table S6.4 Catalyst charge amounts to reactor

Catalyst Total amount

Reactor content of

Reactor content of

Reactor content of

Reactor content of

194!!

charged (mg)

total Au (mg L-1)

total Pd (mg L-1)

Au surface atoms (mg

L-1)a

Pd surface atoms (mg

L-1)a 30 sc% Pd-on-Au/C 100 20 1.5 4.9 1.5 50 sc% Pd-on-Au/C 100 20 2.4 2.4 2.4 60 sc% Pd-on-Au/C 100 20 2.9 1.0 2.9 80 sc% Pd-on-Au/C 100 20 3.9 0.2 3.9 100 sc% Pd-on-Au/C 100 20 4.9 0 4.9 150 sc% Pd-on-Au/C 100 20 8.0 0 5.5 300 sc% Pd-on-Au/C 100 20 18.7 0 7.6

Au/C 100 20 0 7.0 0 Pd/C 100 0 20 0 7.0

a Calculated based on the magic cluster model, used to report kcat values.

Figure S6.1 (a) TEM image and (b) size distribution of carbon-supported 80 sc% Pd-on-Au NPs. Each bar in the size distribution diagram represents percentage of NPs in the diameter range of 0.5 nm.

Table S6.5 Comparison of calculated and measured (*) metal loading

Catalyst Total metal loading (%) Au loading (%) Pd loading (%) Au/C 1.000 (1.02*) 1.00 (1.02*) 0.000 (0.00*) 30 sc% Pd-on-Au/C 1.025 (1.04*) 1.00 (1.01*) 0.025 (0.03*) 80 sc% Pd-on-Au/C 1.123 (1.12*) 1.00 (0.99*) 0.123 (0.13*) 150 sc% Pd-on-Au/C 1.245 (1.26*) 1.00 (1.01*) 0.245 (0.25*)

0

5

10

15

20

25

30

35

2.5 3.0 3.5 4.0 4.5 5.0 5.5

Perc

enta

ge (%

)

Particle size (nm) 10 nm

(a) (b)

195!!

Figure S6.2 (a) Plot of ln(C/C0) vs. time for 0, 30, 50 and 80 sc% Pd-on-Au/C catalysts and (b) Plot of ln(C/C0) vs. time for 80, 100, 150, 300 sc% Pd-on-Au/C and Pd/C catalysts. Reaction conditions: 50 °C, 50 mL, 0.1 M MG, 0.4 M NaOH, pH = 13, and 100 mL min-1 O2.

Table S6.6 Initial MG/metal molar ratios and catalytic activity results for carbon-supported Au, Pd, and Pd-on-Au NPs. Reaction conditions: 50°C, 50 mL, 0.1 M MG, 0.4 M NaOH, pH = 13, and 100 mL min-1 O2.

Catalyst kmeas (h-1)

TOF (h-1)

C 0 0 0 sc% Pd-onAu (Au/C) 0.07 80

30 sc% Pd-onAu 0.09 94 50 sc% Pd-onAu 0.24 162 80 sc% Pd-onAu 0.45 413 100 sc% Pd-onAu 0.30 263 150 sc% Pd-onAu 0.21 162 300 sc% Pd-onAu 0.14 78

Pd/C 0 0

196!!

Figure S6.3 MGA selectivity vs. MG conversion. Reaction conditions: 50 °C, 50 mL, 0.1 M MG, 0.4 M NaOH, pH =13, and 100 mL min-1 O2.

Figure S6.4 Glucose and MG conversion-time profiles for their oxidation reaction. Reaction conditions: 80 sc% Pd-on-Au/C, 50 °C, 50 mL, 0.1 M glucose (or MG), pH 13 and 100 mL min-1 O2.

6.6. Reference

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[2] A. Corma Canos, S. Iborra, A. Velty, Chemical routes for the transformation of biomass into chemicals, Chem. Rev. 107 (2007) 2411–2502. doi:10.1021/cr050989d.

[3] S. Biella, L. Prati, M. Rossi, Selective Oxidation of D-Glucose on Gold Catalyst, J. Catal. 206 (2002) 242–247. doi:10.1006/jcat.2001.3497.

[4] B.T. Kusema, D.Y. Murzin, Catalytic oxidation of rare sugars over gold catalysts, Catal. Sci. Technol. 3 (2013) 297–307. doi:10.1039/C2CY20379K.

[5] G.F. Dutton, Glucuronic acid Free and Combined: Chemistry, Biochemistry, Pharmacology, and Medicine, 1966.

[6] H. Röper, Selective Oxidation of D-Glucose: Chiral Intermediates for Industrial Utilization, Starch - Stärke. 42 (1990) 342–349. doi:10.1002/star.19900420905.

[7] P.L. Bragd, A.C. Besemer, H. van Bekkum, Bromide-free TEMPO-mediated oxidation of primary alcohol groups in starch and methyl α-d-glucopyranoside, Carbohydr. Res. 328 (2000) 355–363. doi:10.1016/S0008-6215(00)00109-9.

[8] S. De, S. Dutta, B. Saha, Critical design of heterogeneous catalysts for biomass valorization: current thrust and emerging prospects, Catal. Sci. Technol. 6 (2016) 7364–7385. doi:10.1039/C6CY01370H.

[9] A. Abbadi, H. van Bekkum, Effect of pH in the Pt-catalyzed oxidation of d-glucose to d-gluconic acid, J. Mol. Catal. A Chem. 97 (1995) 111–118. doi:10.1016/1381-1169(94)00078-6.

[10] J. Song, H. Fan, J. Ma, B. Han, Conversion of glucose and cellulose into value-added products in water and ionic liquids, Green Chem. 15 (2013) 2619. doi:10.1039/c3gc41141a.

[11] M.J. Climent, A. Corma, S. Iborra, Converting carbohydrates to bulk chemicals and fine chemicals over heterogeneous catalysts, Green Chem. 13 (2011) 520. doi:10.1039/c0gc00639d.

[12] L. Chen, J. Zhao, S. Pradhan, B.E. Brinson, G.E. Scuseria, Z.C. Zhang, M.S. Wong, Ring-locking enables selective anhydrosugar synthesis from carbohydrate pyrolysis, Green Chem. 18 (2016) 5438–5447. doi:10.1039/C6GC01600F.

[13] H.E. Van Dam, A.P.G. Kieboom, H. Van Bekkum, Pt/C oxidation catalysts. Part 1. Effect of carrier structure on catalyst deactivation during the oxidation of glucose 1-phosphate into glucuronic acid 1-phosphate, Appl. Catal. 33 (1987) 361–372. doi:10.1016/S0166-9834(00)83067-5.

[14] Y. Schuurman, B.F.M. Kuster, K. van der Wiele, G.B. Marin, The Selective

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Oxidation Of Methyl-alpha-D-Glucoside On A Carbon Supported Pt Catalyst, Stud. Surf. Sci. Catal. 72 (1992) 43–55. doi:10.1016/S0167-2991(08)61657-2.

[15] H. Yuan, H. Liu, Z. Du, Y. Wu, Synthesis of glucuronic acid from methyl glucoside by heterogeneous selective catalytic oxidation, Chem. Eng. J. 207 (2012) 72–75. doi:10.1016/j.cej.2012.07.010.

[16] H. Yuan, Z. Du, Z. Yan, Y. Wu, Selective oxidation of primary alcohol from methyl glucoside over Pd/La0.5Pb0.5Mn0.9 Sn0.1O3 catalyst, Acta Chim. Sin. 67 (2009) 345–351.

[17] A. Wang, X.Y. Liu, C.-Y. Mou, T. Zhang, Understanding the synergistic effects of gold bimetallic catalysts, J. Catal. 308 (2013) 258–271. doi:10.1016/j.jcat.2013.08.023.

[18] F. Tao, Synthesis, catalysis, surface chemistry and structure of bimetallic nanocatalysts, Chem. Soc. Rev. 41 (2012) 7977. doi:10.1039/c2cs90093a.

[19] T.A.G. Silva, E. Teixeira-Neto, N. López, L.M. Rossi, Volcano-like behavior of Au-Pd core-shell nanoparticles in the selective oxidation of alcohols, Sci. Rep. 4 (2015) 5766. doi:10.1038/srep05766.

[20] C.L. Bianchi, P. Canton, N. Dimitratos, F. Porta, L. Prati, Selective oxidation of glycerol with oxygen using mono and bimetallic catalysts based on Au, Pd and Pt metals, Catal. Today. 102 (2005) 203–212. doi:10.1016/j.cattod.2005.02.003.

[21] Z. Zhao, J. Arentz, L.A. Pretzer, P. Limpornpipat, J.M. Clomburg, R. Gonzalez, N.M. Schweitzer, T. Wu, J.T. Miller, M.S. Wong, Volcano-shape glycerol oxidation activity of palladium-decorated gold nanoparticles, Chem. Sci. 5 (2014) 3715. doi:10.1039/C4SC01001A.

[22] K.N. Heck, B.G. Janesko, G.E. Scuseria, N.J. Halas, M.S. Wong, Using catalytic and surface-enhanced Raman spectroscopy-active gold nanoshells to understand the role of basicity in glycerol oxidation, ACS Catal. 3 (2013) 2430–2435. doi:10.1021/cs400643f.

[23] Z. Zhao, J. Miller, N.M. Schweitzer, M. Wong, J.T. Miller, @bullet Tianpin, W. @bullet, N.M. Schweitzer, M.S. Wong, EXAFS characterization of palladium-on-gold catalysts before and after glycerol oxidation, (n.d.). doi:10.1007/s11244-015-0371-3.

[24] H. Qian, Z. Zhao, J. Velazquez, L. Pretzer, Supporting palladium metal on gold nanoparticles improves its catalysis for nitrite reduction, Nanoscale. (2014) 358–364. doi:10.1039/c3nr04540d.

[25] L.N. Lewis, Chemical catalysis by colloids and clusters, Chem. Rev. 93 (1993) 2693–2730. doi:10.1021/cr00024a006.

[26] J.M. Thomas, Colloidal metals: past, present and future, Pure Appl. Chem. 60 (1988). doi:10.1351/pac198860101517.

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[27] T. Teranishi, M. Miyake, Size Control of Palladium Nanoparticles and Their Crystal Structures, Chem. Mater. 10 (1998) 594–600. doi:10.1021/cm9705808.


[29] Y.-L. Fang, J.T. Miller, N. Guo, K.N. Heck, P.J.J. Alvarez, M.S. Wong, Structural analysis of palladium-decorated gold nanoparticles as colloidal bimetallic catalysts, Catal. Today. 160 (2011) 96–102. doi:10.1016/j.cattod.2010.08.010.

[30] L.A. Pretzer, H.J. Song, Y.-L. Fang, Z. Zhao, N. Guo, T. Wu, I. Arslan, J.T. Miller, M.S. Wong, Hydrodechlorination catalysis of Pd-on-Au nanoparticles varies with particle size, J. Catal. 298 (2013) 206–217. doi:10.1016/j.jcat.2012.11.005.

[31] S.E. Davis, M.S. Ide, R.J. Davis, Selective oxidation of alcohols and aldehydes over supported metal nanoparticles, Green Chem. 15 (2013) 17–45. doi:10.1039/C2GC36441G.

[32] S. Carrettin, P. McMorn, P. Johnston, K. Griffin, C.J. Kiely, G.J. Hutchings, Oxidation of glycerol using supported Pt, Pd and Au catalysts, Phys. Chem. Chem. Phys. 5 (2003) 1329–1336. doi:10.1039/b212047j.

[33] M. Comotti, C. Della Pina, M. Rossi, Mono- and bimetallic catalysts for glucose oxidation, J. Mol. Catal. A Chem. 251 (2006) 89–92. doi:10.1016/j.molcata.2006.02.014.

! !

200!!

Chapter 7

Recommendations for Future Work

7.1. Recommendations for future work

The idea of using Au-based nanostructures to deign new DWTM systems including novel

sensors and catalytic converters guided this thesis work and also opens up new thoughts

and directions for future researchers to follow. Several recommendations for future work

are discussed below.

7.1.1. Simultaneous sensing multiple contaminants using luminescent Au

nanostructures

Chapter 2 discussed the use of novel Au microcapsules for selective sensing of Cr(VI) at

ultralow concentration level and the design of paper-based test strip for household water

monitoring. However, multiple contaminants are usually present in water together. It is

desired to have a device that can simultaneously detect the presence of various

contaminants and indicate the contamination level.

201!!The luminescent Au NCs have the capacity to achieve the sensing of multiple

contaminants, because the Au NCs with different surface ligands can interact with

different types of contaminants specifically. For example, lysozyme type VI-stabilized

gold nanoclusters (Lys VI-AuNCs) was studied for the ultrasensitive detection of

Hg2+ based on fluorescence quenching.[1]! L-proline-stabilized fluorescent gold

nanoclusters was studied as sensing probes for iron ion.[2] Depositing Au NCs with

sensing specificity to different contaminates onto a paper strip at different areas is an

approach to design a sensor for detecting multiple contaminants. More research for Au

NCs sensing different contaminant is therefore needed (Scheme 7.1).

!

Scheme 7.1 Example of paper-based multiple contaminants test strip. Different colors indicate different contaminants sensing areas with different Au NCs

Apart from Cr(VI) contaminant discussed in Chapter 2, another common water

contaminants required POU monitoring is lead (Pb). Pb shows adverse effects on the

central nervous system of human. The United States Environmental Protection Agency

(US EPA) has established a maximum contaminant level (MCL) of 15 ppb for Pb in

drinking water. Unfortunately, the unmonitored Pb leaching from pipeline caused the

Flint water crisis in 2014 in Flint, Michigan, which exposed several thousands of people

to high dosages of Pb. Currently, there is no low-cost and high-sensitivity household

device can detect Pb in water.

I have been investigating luminescent Au NCs stabilized by bovine serum

202!!

albumin (BSA-Au NCs) for the sensing of Pb in water with my supervised undergraduate

student and a new graduate student. The preliminary data showed the BSA-Au NCs

experienced strong fluorescence quenching in the presence of Pb ions in water (Fig. 7.1).

The observed fluorescence quenching is hypothesized to occur because of interparticle

aggregation since residual groups in BSA could easily interact with Pb. However, the

specificity of the BSA-Au NCs for sensing Pb is not good (Fig. 7.2) and the current

sensitivity of Pb is still not low enough for practical sensing applications.

!

Figure 7.1 (a) Fluorescence intensity spectra of BSA-Au NCs for different concentrations of Pb2+ at pH ~7. (b) Fluorescence quenching as a function of Pb2+ concentration in water at pH ~7. F denotes the fluorescence intensity at a certain amount of Pb2+ present, while F0 represents the original fluorescence of BSA-Au NCs with no Pb in the water sample.

Figure 7.2 Effect of 10 !M of chloride metals on the fluorescence of 2 !M of BSA-AuNCs at a neutral pH.

Future research could focus on 1) exploring the effect of masking agents such as

203!!

L-cysteine and glutamic acid to improve selectivity towards Pb in water in the presence

of multiple metal ions, 2) investigating the Pb sensitivity in real water samples, 3)

investigating fluorescence enhancement approach to improve the sensitivity, and 4)

investigating other scaffolding materials of Au NCs to improve versatility for POU

applications.

7.1.2. Improving the catalyst and reactor for on-site produced water cleanup

Chapter 4 and 5 discussed the promising usage of PdAu catalyst for H2O2 generation and

phenol degradation in simulated HFPW. Currently, the structure of PdAu catalyst is still

unknown and the configuration of reactor is not optimized. To improve the performance

of this on-site HFPW treatment system, one of the approaches is to improve the catalyst

performance by tuning its structures and another is to optimize the reactor by tuning the

operating parameters.

My earlier research in Chapter 6 demonstrated the successful synthesis of Pd-on-

Au nanostructures. Pd with preciously controlled amounts can be deposited on the 4-nm

Au NPs. The formed Pd-on-Au nanostructures usually has enhanced catalytic activity

and/or stability compared to the monometallic Pd and Au NPs. The Pd-on-Au

nanostructures may be the next version of PdAu catalyst and have the potential

application for design of the on-site produced water treatment unit.

Preliminary experiments on H2O2 generation from the oxidation of

hydroxylamine using Pd-on-Au nanostructures were conducted. The H2O2 generation

activity showed volcano-shape dependence on the Pd surface coverage on Au, with the

highest activity achieved at 100% sc Pd-on-Au catalyst. The 2-D Pd ensembles on the Au

204!!

surface were possibly the active sites for the hydroxylamine oxidation on Pd-on-Au

catalysts.

!

Figure 7.3 Plot of initial H2O2 productivity with Pd surface coverage. Reaction conditions: 23 °C, 50 mL, 10 mM hydroxylamine, pH = 9, and 50 mL min-1 O2.

Although 100% sc Pd-on-Au showed the initial highest H2O2 productivity, the

questions remained if this composition is still the best catalyst for hydroxyl radical

generation and the degradation of organic compounds. Also, further investigations on the

TDS and pH effects on the Pd-on-Au catalysts are needed.

The phenol degradation using a constructed circulating packed bed flow reactor

was demonstrated in Chapter 5, which served as the proof-of-concept purpose. The

design of the reactor is still rudimental and has much room for improvements. The

optimizations of the reactor can be conducted on tuning operating parameters such as the

gas-to-liquid ratio, flowrate, and catalyst dilution.

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0 50 100 150 200 250 300 350

H2O

2 pro

duct

ivity

(m

mol

per

h p

er P

d su

rfac

e at

om)

Pd surface coverage (%)

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0 50 100 150 200 250 300 350

H2O

2 pro

duct

ivity

(m

mol

per

h p

er P

d su

rfac

e at

om)

Pd surface coverage (%) Pd

205!!

7.1.3. Development of the simultaneous contaminants sensing and degradation

systems

The current DWTM systems maintain high-quality water by using separated sensing and

degradation processes. A desired feature for the future DWTM systems is to

simultaneously sense and degrade contaminants using the same material, which can

minimize the size of the system, reduce the use of materials and lower the cost of the

system.

The idea of simultaneous contaminants sensing and degradation is not new.

Several nanostructures have been proposed and investigated for this application. Kamat et

al. studied the dual roles of ZnO semiconductor film as a luminescence-based sensor and

as a photocatalyst for the simultaneous sensing and degradation of 4-chlorocatechol.[3]

Alam et al. reported the SERS and photocatalytic features of semiconductor-graphene

oxide-metal film, which can be used for organic contaminants sensing and

degradation.[4] Rakkesh et al. studied a similar SERS-based sensor with photocatalytic

property using ZnO-Ag-graphene nanosheets materials.[5] However, the complicated

preparation processof these reported materials limits their practical applications.

Au-based nanostructures exhibiting the catalytic and optical properties at the same

time are good candidates for design of the simultaneous sensing and degradation system.

However, current research focused on investigating these properties separately. Future

research on multi-functional Au-based nanostructures is a promising direction to pursue.

206!!

7.2. Reference

[1] Y.H. Lin, W.L. Tseng, Ultrasensitive sensing of Hg2+ and CH3Hg+ based on the fluorescence quenching of lysozyme Type VI-stabilized gold nanoclusters, Anal. Chem. 82 (2010) 9194–9200. doi:10.1021/ac101427y.

[2] X. Mu, L. Qi, P. Dong, J. Qiao, J. Hou, Z. Nie, H. Ma, Facile one-pot synthesis of l-proline-stabilized fluorescent gold nanoclusters and its application as sensing probes for serum iron, Biosens. Bioelectron. 49 (2013) 249–255. doi:10.1016/j.bios.2013.05.019.

[3] P. V. Kamat, R. Huehn, R. Nicolaescu, A “sense and shoot” approach for photocatalytic degradation of organic contaminants in water, J. Phys. Chem. B. 106 (2002) 788–794. doi:10.1021/jp013602t.

[4] R. Alam, I. V. Lightcap, C.J. Karwacki, P. V. Kamat, Sense and Shoot": Simultaneous Detection and Degradation of Low-Level Contaminants Using Graphene-Based Smart Material Assembly, ACS Nano. 8 (2014) 7272–7278. doi:10.1021/nn502336x.

[5] R.A. Rakkesh, D. Durgalakshmi, S. Balakumar, Graphene based nanoassembly for simultaneous detection and degradation of harmful organic contaminants from aqueous solution, RSC Adv. 6 (2016) 34342–34349. doi:10.1039/c6ra01784c.

!

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