Carbon 39 (2001) 2313–2324

Elucidation of the ion binding mechanism in heterogeneouscarbon-composite adsorbents

a , a b b*Alexander M. Puziy , Olga I. Poddubnaya , James A. Ritter , Armin D. Ebner ,bCharles E. Holland

aInstitute for Sorption and Problems of Endoecology, Naumov St. 13, 03680 Kiev-164, UkrainebDepartment of Chemical Engineering, University of South Carolina, Columbia, SC 29208, USA

Received 25 July 2000; accepted 31 January 2001

Abstract

A two-stage analysis of the mechanism of metal ion binding by a heterogeneous adsorbent was developed. In the firststage, a continuous proton affinity distribution was calculated from potentiometric titration data using the CONTIN methodwith a Langmuir kernel. Electrostatic effects were accounted for using a diffuse layer model. In the second stage, theparameters obtained from the continuous distribution function (i.e. the number of different types of surface sites, sitedensities and their protonation constants) were utilized in a discrete distribution to represent the adsorbent in surfacecomplexation and double layer models using the GRFIT speciation code. This information on the surface groups was appliedto metal ion potentiometric titration experiments to calculate the surface complexation equilibrium constants of the metalions and hence elucidate the mechanism of ion binding to these sites. The proposed method was applied successfully to theadsorption of Sr and Cu ions on carbon-composite adsorbents, KAU-mod and SCN-mod. The continuous distribution method(CONTIN) revealed three types of surface sites within these carbon-composite adsorbents with pK values ranging between3.5–4.1, 5.3–6.3 and 7.7–8.2. The analysis of the metal ion adsorption data using the GRFIT speciation code showed thatonly the first two surface sites were capable of forming surface complexes with the Sr ions, and that only the first sitegoverned the adsorption of the Cu ions. 2001 Elsevier Science Ltd. All rights reserved.

Keywords: A. Carbon composites; B. Impregnation; D. Adsorption properties; Surface properties; Functional groups

1. Introduction from experimental data, such as HYDRAQL [8], FITEQL[9], and GRFIT [10,11]. This approach requires detailed

Ion binding to heterogeneous adsorbents plays an essen- information about the molecular structure of the adsorbenttial role in biochemistry, polymer chemistry, chromatog- and the spatial arrangement of individual adsorption sites.raphy, material science, and environmental chemistry [1– Usually, this information is available for very simple oxide5]. Knowledge of the multicomponent binding mechanisms adsorbents that contain one to two homogeneous surfaceis necessary for a quantitative description and prediction of sites. As a result, considerable progress has been achieved,the adsorption of one or more components as a function of but only in revealing the mechanisms behind ion bindingthe solution composition. Furthermore, the role of a in oxide adsorbents [12–16]. In contrast, the use of theparticular surface site is critical in the design of new existing speciation codes for the solution of chemicaladvanced adsorbents with enhanced performance. The equilibrium constants involving heterogeneous adsorbents,standard approach to the analysis of the ion binding such as activated carbons or carbon-composite adsorbents,mechanism is through the solution of a chemical equilib- presents considerable difficulties. These difficulties arerium problem represented by a chemical matrix or tableau basically connected with the structural uncertainty of the[6,7]. Several speciation codes have been developed for the adsorption sites on heterogeneous surfaces. For example,calculation of surface complexation equilibrium constants carbon adsorbents have been reported to contain four to

five surface sites [17–23].Information on surface sites can be obtained, however,*Corresponding author. Fax: 1380-44-452-9327.

E-mail address: alexander.puziy@ispe.kiev.ua (A.M. Puziy). from the analysis of single ion binding (proton binding)

0008-6223/01/$ – see front matter 2001 Elsevier Science Ltd. All rights reserved.PI I : S0008-6223( 01 )00048-3

2314 A.M. Puziy et al. / Carbon 39 (2001) 2313 –2324

experiments in the context of a linear combination of dioxide and titanium silicate are good strontium adsorbentsadsorption sites; this is the most popular approach for [32–38].modeling adsorption on heterogeneous surfaces [24–27].With this model, surface properties are uniquely defined by 2.2. Characterizationa distribution function (proton affinity distribution), whichdescribes the site concentration as a function of the binding Nitrogen adsorption measurements were carried outconstant of the site. Hence quantitative (site density) and using an ASAP 2010 volumetric adsorption analyzerqualitative (binding constant) information can be obtained (Micromeritics, Norcross, GA, USA) at liquid nitrogenwith some a priori knowledge about the distribution temperature (77 K) in a relative pressure range from about

27function (typically non-negativity and smoothness) [27,28]. 10 to 0.998. Before any measurements were done, theThis information on surface sites can then be used to samples were outgassed for 2 h at 2008C. Mercuryprovide a basis for constructing a binding model that is intrusion measurements were carried out using a PoreSizerobtained from the solution of the chemical equilibrium M9300 apparatus (Micromeritics) in a pressure range fromproblem using the existing speciation codes. In this way, 0.01 to 206.8 MPa. The contact angle of mercury at thethe number of adjustable parameters needed to correctly mercury /adsorbent interface was assumed to be 1428 (cosdescribe the chemical equilibrium is reduced. u520.788).

The purpose of this study is to report on the develop- The potentiometric titration experiments were carriedment of a new two-step approach that can be used to out as follows. A weighed amount of adsorbentelucidate the ion binding mechanism in heterogeneous (0.12560.0001 g) was placed into a 100-ml round-bot-adsorbents including electrostatic interactions. In the first tomed three-neck flask containing 25 ml of 0.1 M NaClstep, CONTIN [29] is used to obtain the information on solution. The adsorption system was equilibrated to con-surface sites in terms of a continuous distribution (proton stant pH under a protective N flow. The titrations were2

affinity distribution). In the second step, the data obtained carried out with 0.1 M HCl or 0.1 M NaOH solutionsfrom the continuous distribution is used to construct a using a Titrino 716 microburette (Metrohm, Switzerland)surface complexation model using the GRFIT speciation interfaced to a PC computer utilizing LabView softwarecode [10,11]. This two-step analysis was successfully (developed in-house), which controlled the equilibriumapplied to proton, strontium and copper ion binding condition and titrant delivery. The criterion for equilibriumexperiments to obtain the binding constants of three was set at a pH drift of less than 0.0001 pH units /min.specific surface sites within two novel carbon composite The specific moles of protons adsorbed, Q, was calcu-adsorbents, KAU-mod and SCN-mod. The participation of lated from:each of these surface sites in the metal ion binding process

V 1V0 tis revealed. ]]Q 5 ([H] 2 [OH] 2 [H] 1 [OH] ) (1)i i e em

where V and V are the volumes of background electrolyte0 t

2. Experimental and titrant added, respectively, and m is the mass ofadsorbent. [H] and [OH] are, respectively, the proton and

2.1. Adsorbent samples hydroxyl group concentrations with subscripts i and ereferring to the initial and equilibrium concentrations. The

Carbon composite adsorbents were prepared according equilibrium proton concentration was calculated from theto the procedure described elsewhere [30]. Briefly, carbon measured pH using an activity coefficient correction fromof fruit stone origin (apricot) — KAU and carbon of Davis’ equation [39]. A constant ionic medium of 0.1 Mpolymer origin (copolymer of vinylpyridine and di- NaCl was maintained in all of the experiments, whichvinylbenzene [31]) — SCN were first oxidized by boiling minimized the variation in the activity coefficientsin 20 wt.% nitric acid for 5 h. These oxidized carbons were throughout the titration. As inferred from Eq. (1), Q isimpregnated with a 4 M solution of TiCl and washed with positive for proton binding and negative for proton release.4

distilled water. Then, they were impregnated with a 2 M The potentiometric titration experiments were carried outsolution of Na SiO , followed by extensive washing with in a pH window between 3 and 11. Outside this region2 3

distilled water until neutral pH. This method allows for the there is a progressively increasing error in the calculationintroduction of up to 20 wt.% of mineral matter into the of Q, due to the buffering power of water [1]. This effectcarbon adsorbent. Moreover, the resulting carbon-compo- becomes significant for pH,2 and pH.12, which makessite adsorbents are heterogeneous in that they contain the titration of surface groups with pK,2 and pK.12surface sites (or groups) originating from both the oxidized inaccurate.carbon and the titanium silicate. The choice of these The metal ion binding experiments were carried out asmodifying agents was dictated by the fact that both follows. The same weighed amount of adsorbenttitanium and silicon readily produce water-insoluble oxides (0.160.0001 g) was placed into numerous Erlenmeyerthat are not toxic, and it was very important that titanium flasks, each containing 20 ml of solution comprised of 0.1

A.M. Puziy et al. / Carbon 39 (2001) 2313 –2324 2315

M NaCl, and 0.01 M or 0.001 M of either SrCl or Provencher [45,46] and subsequently modified for ad-2

Cu(NO ) . Then, a different amount of 0.1 M HCl or 0.1 sorption problems by Puziy et al. [27,29]. CONTIN is3 2

M NaOH was added to each flask to obtain adsorption data advantageous because it automatically chooses the regu-points at different solution pHs ranging from about 3 to 11. larization parameter based on an F-test and confidenceThe flasks were shaken for 24 h to ensure equilibrium was regions. Thus, the regularization parameter can be adaptedachieved. After equilibration, the pH was measured with a to the noise level and the amount of experimental data.glass electrode and the metal ion concentration was Another advantage of the CONTIN method is that it hasdetermined titrimetrically with EDTA. the ability to calculate a constant background term, Q . By0

using a constant background, it is possible to take intoaccount the influence of groups with a pK outside the2.3. Theoretical data analysisexperimental window. For all of the proton affinity dis-tribution calculations, CONTIN was restricted to a pKSince the carbon-composite adsorbents contain a varietywindow of 2 to 12. This approach gave information onof surface groups originating from both the carbon (car-both the protonation and deprotonation processes.boxylic –COOH, phenolic –OH) and the mixed oxides

The local isotherm (Q ) reflects the underlying mecha-l(surface hydroxyls –OH), as a first stage of the analysis, anism of ion binding by a homogeneous adsorption site. Insimple empirical model assuming a linear combination ofthis work, the Langmuir equation, which can be derivedindependent adsorption sites was applied. In this model,from mass action and mass balance equations, was used asthe carbon-composite adsorbents are considered to be anthe local isotherm:ensemble of independent monoprotic surface groups. The

special convenience of this simple empirical model was 1K [H ]Hthat it is based solely on experimental data and any other ]]]Q 5 (3)l 11 1 K [H ]Hknowledge about the structure of the surface sites isunnecessary. This model also describes equally well both 1where K is the binding constant and [H ] is the protonHthe proton binding and proton release processes. The

concentration. For the case of adsorption on a chargedconcept of a linear combination of independent adsorption

surface, the proton concentration in the surface layersites leads to the following adsorption integral equation: 1 1should be used, i.e. [H ] in lieu of [H ]. This surfaces

pKmax layer concentration is related to the bulk concentration by aBoltzmann correction factor as:Q (pH) 5 E Q (pH, pK)f(pK) dpK 1 Q (2)t l 0

1 1pKmin [H ] 5 [H ] exp(2Fc /RT ) (4)s

where Q is the experimentally measured isotherm, Q ist l where c is the electric potential at the surface, F isthe local isotherm, f(pK) is the desired distribution Faraday’s constant, R is the universal gas constant, and Tfunction, pK and pK are the limits of integration, andmin max is the absolute temperature. The relation between theQ is a constant background term defined below. The0 surface charge and electric potential in a diffuse layerdistribution function describes the site concentration as a model is given by:function of the binding constant, and is a unique charac-teristic of the adsorbent material. A similar equation has 2RT s21] ]]]c 5 sinh 2 (5)]]been used extensively for calculating adsorption energy S DF 8´´ RTIœ 0distribution and pore size distribution functions from gasadsorption data [40–43]. where s is the surface charge, ´ is the relative permittivity

From a mathematical point of view, Eq. (2) is a of the solution, ´ is the permittivity of vacuum, and I is0Fredholm integral equation of the first kind. Solving this ionic strength of the solution.equation with respect to the distribution function is a The metal ion binding constants were evaluated using awell-known ill-posed problem, which is manifested by the surface complexation model with a diffuse double layer. Infact that there exists an infinitely large set of possible this model, the carbon-composite adsorbents were assumedsolutions, all satisfying Eq. (2) to within the experimental to contain three independent monoprotic adsorption sites.errors. To select a meaningful solution from the set of all The determination of the ion complexation constants waspossible solutions, many methods have been developed. A done with the help of the GRFIT speciation code [10]. Thecomprehensive review of these methods for assessment of concentrations of the surface sites and their correspondingthe distribution function from Eq. (2) may be found pK values, obtained from the potentiometric titrationelsewhere [24,25,27,44]. In this work, a general purpose experiments using CONTIN [29], were used as the inputconstrained regularization method, CONTIN, was used for parameters to this code. Chemical equilibrium in theinverting the inherently noisy linear operators associated potentiometric titration experiments was described by:with the solution of Eq. (2) for solution with respect to

2 1X H↔X 1 H (6)distribution function f(pK). CONTIN was developed by i i

2316 A.M. Puziy et al. / Carbon 39 (2001) 2313 –2324

Table 1 tics of the parent carbon and the carbon-composite ad-Ash and density of the carbon-composite adsorbents sorbents, KAU-mod and SCN-mod, are presented in

Tables 1–3. The slight increases in both the bulk andAdsorbent Ash content Bulk density Apparent density3 3 apparent densities, and the decreases in the pore volume,% g/cm g/cm

and especially the decrease in the mercury surface area,KAU 0.4 0.45 0.74

were indicative of the deposition of a mixed oxideKAU-mod 12.4 0.50 0.88structure within the pores of the carbon. The mineralSCN 0.4 0.40 0.48content of the carbon composite adsorbents was estimatedSCN-mod 11.5 0.50 0.54from their ash content, which was around 12 wt.%. Fig. 1shows the pore size distribution of the parent and carbon-

where X represents a surface site. Metal ion binding, in composite adsorbents, KAU-mod (a) and SCN-mod (b),i21the case of a divalent cation (e.g. Sr ) was described by obtained by the mercury intrusion method. For KAU-mod,

deprotonation (Eq. (6)) and the following mono- and the pore size distribution revealed that the titanium andbidentate binding equations: silicon mixed oxides caused shifts within a wide range of

˚ ˚pore diameters from below 70 A to about 10,000 A. In2 21 1X 1 Sr ↔X Sr (7)i i contrast, for SCN-mod, the oxides caused shifts within

˚pores ranging from about 80 to 15,000 A in diameter.2 21 2X 1 Sr 1 OH ↔X SrOH (8) Nitrogen adsorption isotherms measured at 77 K on thei i

carbon-composite adsorbents are presented in Fig. 2. The2 212X 1 Sr ↔(X ) Sr (9) initial part of both isotherms, which was attributed toi i 2

micropore filling, constituted a substantial part of each1 2The background electrolyte ions, Na and Cl , were isotherm. For SCN-mod, which was produced from a

presumed to exist as ions that did not interact specifically synthetic carbon, a steep rise was exhibited at high relativewith any other components in the system; thus, they were pressures (P/P . 0.9), indicating that capillary condensa-0

not considered in the adsorption process. Activity co- tion occurred in some of the mesopores. Table 3 shows theefficients were also not included in these calculations; thus, porous characteristics of the carbon-composite adsorbentsthe equilibrium constants were considered as conditional obtained from the nitrogen adsorption isotherms using theconstants with validity only for concentrations at 0.1 M BET and a -methods. Both carbons contained a fairS

ionic strength. degree of microporosity and a correspondingly high sur-face area. However, SCN-mod exhibited a relatively highmesopore surface area compared to that of KAU-mod.

3. Results and discussion Adsorption energy distributions were also obtained fromthe nitrogen adsorption isotherms using the Hill–de Boer

3.1. Physicochemical characterization model for mobile adsorption [40]; these are shown in Fig.3. Both distributions exhibited three groups of peaks. The

Some of the physical properties and porous characteris- first group of peaks in the low energy region (|4.9 kJ /

Table 2Porous characteristics of the carbon-composite adsorbents obtained from the mercury intrusion method

a bAdsorbent Pore volume Macropore volume Surface area Macropore surface3 3 2 2cm /g cm /g m /g area, m /g

KAU 0.45 0.16 615 1.6KAU-mod 0.32 0.14 89 1.3SCN 0.78 0.46 682 1.8SCN-mod 0.54 0.09 196 0.4

a 6 ˚Total volume of pores having a diameter in the range of 70–1.3310 A.b 6 ˚Total surface area of pores having a diameter in the range of 70–1.3310 A.

Table 3Porous characteristics of the carbon-composite adsorbents obtained from nitrogen adsorption data

2 a 2 a 2 3 3Adsorbent A , m /g A , m /g A , m /g V , cm /g V , cm /gBET mi me mi tot

KAU-mod 1112 1095 47.6 0.553 0.599SCN-mod 997 944 124.1 0.438 0.715

a Obtained by the a -method.S

A.M. Puziy et al. / Carbon 39 (2001) 2313 –2324 2317

Fig. 2. Nitrogen adsorption isotherms at 77 K on the carbon-Fig. 1. Pore size distributions of the parent carbon, and the

composite adsorbents, KAU-mod and SCN-mod; (a) linear scale,carbon-composite adsorbents, (a) KAU-mod and (b) SCN-mod

(b) log–log scale.obtained by the mercury intrusion method.

mol) was related to the formation of a second adsorption 3.2. Model verification with a homogeneous systemlayer [40]. The second group of peaks, with a maximum at9.2 kJ /mol, was characteristic of adsorption in the first Before the potentiometric titration method was used toadsorption layer on carbon adsorbents [27]. The third determine the proton binding surface sites of the carbon-group of peaks in the high energy region corresponded to composite adsorbents, the reliability and resolution of theadsorption in the micropores, where an enhanced ad- CONTIN method for analysis of the proton bindingsorption potential exists due to an overlapping surface isotherms was first tested with titration data obtained frompotential from the close proximity of the pore walls [40]. a simple acid that is characterized by known pK constants,Two peaks were exhibited in this region, indicating a i.e. citric acid [47,48]. Fig. 4 shows the proton bindingbimodal distribution of micropores. isotherm and proton affinity distribution obtained for citric

2318 A.M. Puziy et al. / Carbon 39 (2001) 2313 –2324

acid. As expected, the proton binding isotherm fell in thenegative region, indicating that only a proton releaseprocess took place. Furthermore, at low pH values, theisotherm practically approached a zero level of protonrelease, but then increased up to about 3 moles of protonsreleased per mole of acid at a pH of about 7. The pKdistribution for citric acid exhibited three distinct andwell-resolved peaks, each with an area of about 1 mole;thus, the total amount of proton binding sites (Q ) wastot

close to about 3 moles per mole of citric acid, as shown inTable 4. The results presented in Table 4 also show thatthe background term (Q ) was practically zero, indicating0

that all of the proton binding groups were titrated in theexperiment. Table 4 also displays the apparent acidityconstants obtained from the first moment of the dis-tribution and corrected for a salt effect [1]. The calculatedthermodynamic constants were in very good agreementwith values reported in the literature [48]. These resultsconfirmed that the CONTIN method is very reliable forthese kinds of analyses.

3.3. Carbon-composite adsorbentsFig. 3. Adsorption energy distributions calculated from the nitro-gen adsorption isotherms using the Hill–de Boer adsorption Figs. 5 and 6 present the proton binding isotherms andmodel. the corresponding proton affinity distributions obtained

from the carbon-composite adsorbents, KAU-mod andSCN-mod, respectively. The corresponding continuousproton affinity distribution parameters are given in Table 5.Since both isotherms approached the zero level at low pH,all of the surface sites were again protonated. Bothisotherms also fell in the negative region, indicating thatonly proton release occurred; hence, the background term(Q ) was practically zero (Table 5). This indicated that all0

of the surface groups were contained within the ex-perimental pH window. In both cases these proton affinitydistributions revealed very clearly the heterogeneouscharacter of the carbon-composite adsorbents with eachexhibiting three types of surface groups. The distributionswere also similar, suggesting that similar surface groupswere present on each sample; however, one large peakdominated both distributions and this peak was especiallypronounced for SCN-mod at pK range 7.2–8.2. Since allthree peaks of the proton binding distributions wereobtained within the negative part of the proton bindingisotherm, they corresponded to surface sites with nega-

¨tively charged Bronsted acid–base forms; thus, they allcould contribute to the adsorption of metal ions fromaqueous solutions. The assignment of these groups or sitesto a specific chemical structure was difficult, however,since they could be attributed to those originating from thecarbon surface (carboxylic or lactone with pK,8 andphenolic with pK.8) [17,21,23,49,50], as well as varioushydroxyl groups on the mixed oxides of titanium andsilicon [51]. Most likely, the first group with pK aroundFig. 4. Proton binding isotherm (a) and proton affinity distribution3.5–3.9 may be assigned to carboxylic groups, the third(b) for citric acid. Symbols, experimental data; solid line, CON-

TIN fit to Eq. (2). group with pK around 7.7–8.0 may be connected with

A.M. Puziy et al. / Carbon 39 (2001) 2313 –2324 2319

Table 4Continuous proton affinity distribution parameters of citric acid, and thermodynamic pK constants and reference values

a*Q , Q , Q , pK pK Ref. valuesi tot 0 i i

mmol /mmol mmol /mmol mmol /mmol measured corrected [47,48]

0.99060.68% 3.01260.41% 0.023620% 3.0061.6% 3.12 3.1281.06160.68% 4.4261.3% 4.78 4.7610.96160.75% 5.7761.1% 6.37 6.396

a *pK , corrected for salt effect [1].i

phenolic groups, and the second group with pK around present study, the electrostatic effects were not considered5.3–5.9 may be related to hydroxyl groups associated with in the previously cited references.the mixed oxides of titanium and silicon. The information obtained from the continuous affinity

It is noteworthy that in earlier studies, another regulari- distribution functions (i.e. the number of different types ofzation method developed by Jagiel«l«o [52] (SAIEUS) was sites, the site densities and their pK values, as reported insuccessfully used in titration data analysis. In comparison, Table 5) was then used in the surface complexation modelJagiel«l«o et al. [21] reported a four-peak distribution with to describe the metal ion adsorption process. This surfacesimilar peak positions (pK54.2, 5.6, 7.6, 10.0) for a complexation model treats the surface sites as ligands thatWestvaco carbon oxidized with HNO . Oxide systems also form complexes with the metal ions in an analogous3

fall into this same region. For instance, Contescu at al. [51] fashion to the formation of complexes in bulk solutions.reported a three-peak distribution for rutile (pK55.6, 6.9, The main difference between solution- and surface-com-9.1), a five-peak distribution for anatase (pK54.4, 5.4, 6.9, plexes is the development of a surface charge during the8.8, 9.7), a two-peak distribution for silica (pK58.0, 9.7), adsorption or desorption processes. This charging of theand a three-peak distribution for mixed titania–silica adsorbent surface can be accounted for by using ansamples (pK54.5–5.8, 6.3–8.2, 9.2–10.8). However, a electrical ‘double layer’ model, such as a constant capaci-direct comparison of the present findings with all of this tance, diffuse double layer or triple layer model [6].data was not possible due to the fact that, contrary to the Moreover, since the existing speciation codes can handle

Fig. 5. Proton binding isotherm (a) and proton affinity distribution Fig. 6. Proton binding isotherm (a) and proton affinity distribution(b) for carbon-composite adsorbent KAU-mod. Symbols, ex- (b) for carbon-composite adsorbent SCN-mod. Symbols, ex-perimental data; solid line, CONTIN fit to Eq. (2). perimental data; solid line, CONTIN fit to Eq. (2).

2320 A.M. Puziy et al. / Carbon 39 (2001) 2313 –2324

Table 5Continuous proton affinity distribution parameters of the carbon-composite adsorbents, KAU-mod and SCN-mod

Adsorbent Q , Q , Q , pKi tot 0 i

mmol /g mmol /g mmol /g

KAU-mod 0.61962.1% 1.88761.6% 20.028617% 4.1064.2%0.38762.8% 6.3065.7%0.88162.7% 8.2465.0%

SCN-mod 0.647633% 2.68868.6% 0.0806200% 3.52656%0.386621% 5.25632%1.65661.6% 7.6963.3%

only discrete affinity distributions, problems could arise inrepresenting the heterogeneous carbon-composite adsor-bents with a discrete distribution [12]. However, theseproblems were actually minimized due to the fact that theelectrostatic interactions broadened the energy of adsorp-tion interaction (stability constant) from a single discretevalue to a distribution of values. Since the composition ofthe surface complexes and their stability constants dependson the surface charge, a diffuse double layer model wasused in this work.

The surfaces of the carbon-composite adsorbents in thismodel were represented as three independent monoproticsurface sites. The site densities and their corresponding pKvalues from the CONTIN analysis (Table 5) were used asan initial guess. Figs. 7 and 8 show the titration curves ofthe carbon-composite adsorbents in 0.1 M NaCl, and Table

Fig. 8. Titration curve of SCN-mod in 0.1 M NaCl (a) anddistribution of surface species (b). Symbols, experimental data;solid line, calculated by GRFIT optimization.

6 displays the resulting discrete proton affinity distributionparameters. The titration experiments were well repre-sented by the discrete affinity spectra; only small differ-ences were observed between the experimental results and

Table 6Discrete proton affinity distribution parameters of the carbon-composite adsorbents, KAU-mod and SCN-mod

Q pKi i

mmol /g

KAU-mod 0.467 3.890.446 5.860.713 8.02

SCN-mod 0.502 3.54Fig. 7. Titration curve of KAU-mod in 0.1 M NaCl (a) and

0.450 5.31distribution of surface species (b). Symbols, experimental data;

1.385 7.74solid line, calculated by GRFIT optimization.

A.M. Puziy et al. / Carbon 39 (2001) 2313 –2324 2321

the model predictions at high pH values, where the glasselectrode was known to deviate from ideality. Furthermore,the parameters obtained from the continuous and discretedistributions agreed well with each other (compare thevalues in Tables 5 and 6); thus, these refined protonbinding constants and site densities (Table 6) were used inmodeling the metal ion adsorption experiments. During thefit, only the metal ion binding constants were allowed tovary, with the other parameters (site densities and pKvalues) being fixed. Figs. 9–12 show the pH dependence ofthe Sr and Cu ion adsorption (a) and correspondingspeciation plot (b), assuming that the equilibrium wasdescribed by monodentate binding (Eqs. (7) and (8)) andbidentate binding (Eq. (9)). The calculated binding con-stants are listed in Table 7.

These data revealed that the mechanism of Sr binding onboth carbon-composite adsorbents was similar. The maintrend observed for metal ion adsorption was the formationof neutral surface complexes according to Eqs. (8) (mono-dentate binding) and (9) (bidentate binding). For Sradsorption up to a pH of 6, the adsorption was dominatedby the formation of a bidentate surface complex, (X ) Sr,1 2

with the most acidic surface group. Then, at increasing pHFig. 10. (a) Adsorption of strontium from 0.1 M NaCl on carbon-values, the second (slightly less acidic) surface groupcomposite adsorbent SCN-mod. Open symbols, data for total Srconcentration of 0.001 M; closed symbols, data for total Srconcentration of 0.01 M; solid line, GRFIT optimization. (b)Distribution of Sr species calculated for the total Sr concentrationof 0.001 M and 5 g/ l of adsorbent.

began to dominate with the formation of a bidentatecomplex, (X ) Sr. The formation of hydroxo-complexes2 2

was characteristic of KAU-mod at high pHs. In contrast,Cu adsorption was governed by the formation of complex-es with only the most acidic surface group (Table 8). Theother surface groups played minor roles in the Cu ad-sorption process. For example, at pH values between 2.3and 2.7, a bidentate surface complex, (X ) Cu, was1 2

formed with the most acidic surface group. At higher pHs,the stoichiometry changed to a monodentate hydroxo-complex, X CuOH.1

These results showed very clearly that only two of thethree surface groups participated in the Sr binding process,and only one of the three surface groups took part in theadsorption of Cu. Moreover, the reactivity of these sites inall cases was strongly pH dependent. Clearly, this kind ofinformation is very important for the development of moreefficient adsorbents, depending on the field of application.For example, for the adsorption of Cu, it would beessential to increase the site density of only the most acidic

Fig. 9. (a) Adsorption of strontium from 0.1 M NaCl on carbon-surface group, whereas for the adsorption of Sr, increasingcomposite adsorbent KAU-mod. Open symbols, data for total Srthe site densities of both the most acidic and the secondconcentration of 0.001 M; closed symbols, data for total Srmost acidic surface groups would be important.concentration of 0.01 M; solid line, GRFIT optimization. (b)

Distribution of Sr species calculated for the total Sr concentrationof 0.001 M and 5 g/ l of adsorbent.

2322 A.M. Puziy et al. / Carbon 39 (2001) 2313 –2324

Fig. 12. (a) Adsorption of copper from 0.1 M NaCl on carbon-Fig. 11. (a) Adsorption of copper from 0.1 M NaCl on carbon-

composite adsorbent SCN-mod. Open symbols, data for total Cucomposite adsorbent KAU-mod. Open symbols, data for total Cu

concentration of 0.001 M; closed symbols, data for total Cuconcentration of 0.001 M; closed symbols, data for total Cu

concentration of 0.01 M; solid line, GRFIT optimization. (b)concentration of 0.01 M; solid line, GRFIT optimization. (b)

Distribution of Cu species calculated for the total Cu concen-Distribution of Cu species calculated for the total Cu concen-

tration of 0.001 M and 5 g/ l of adsorbent.tration of 0.001 M and 5 g/ l of adsorbent.

Table 74. Conclusions Stability constants of the Sr surface complexes

1X Sr X SrOH (X ) Sri i i 2CONTIN, a general purpose constrained regularizationKAU-mod 215.3 29.5 21.8method, was shown to be a powerful tool to characterize

.220.0 210.5 24.6surface heterogeneity in terms of a continuous proton

.220.0 214.2 219.0affinity distribution obtained from a potentiometric titrationSCN-mod .220.0 210.5 21.1experiment. Information on the number of different types

.220.0 212.9 24.3of surface sites, site densities and their protonation con-

.220.0 218.2 .220.0stants can be obtained in an objective manner provided thatthe electrostatic effects are taken into account. Using adiffuse double layer model and a flexible continuousdistribution function, it was shown that the carbon-compo- This method and the information obtained from it shouldsite adsorbents studied here each contained three distinct prove to be very useful in tailoring the design of metal iontypes of surface groups or sites. adsorbents for specific applications. For example, of the

It was also shown that these heterogeneous carboncomposite adsorbents could be well represented by a Table 8discrete distribution (three surface sites), as opposed to a Stability constants of the Cu surface complexescontinuous distribution, in the GRFIT chemical equilib-

1X Cu X CuOH (X ) Cui i i 2rium speciation code. Using surface complexation with adiffuse layer model within GRFIT, the analysis of metal KAU-mod .220.0 21.8 2.0

.220.0 26.3 .220.0ion adsorption data, coupled together with the information

.220.0 27.5 .220.0obtained from CONTIN, revealed the role of each surfaceSCN-mod .220.0 21.2 2.3group in the metal ion binding process. Thus, a robust

212.8 25.8 25.5two-step analysis was developed to elucidate the mecha-213.6 27.7 212.8nism of metal ion binding in heterogeneous adsorbents.

A.M. Puziy et al. / Carbon 39 (2001) 2313 –2324 2323

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[16] Westall JC, Jones JD, Turner GD, Zachara JM. Environ Sciion adsorption and only one was active for Cu ionTechnol 1995;29:951.adsorption. These results suggested that increasing the site

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