Raman spectral detection and assessment of thin organic layers on metal substrates: systematic...

JOURNAL OF RAMAN SPECTROSCOPYJ. Raman Spectrosc. 2008; 39: 515–524Published online 29 January 2008 in Wiley InterScience(www.interscience.wiley.com) DOI: 10.1002/jrs.1872

Raman spectral detection and assessment of thinorganic layers on metal substrates: systematic approachfrom substrate preparation to map evaluation

Martin Clupek,∗ Vadym Prokopec, Pavel Matejka and Karel Volka

Department of Analytical Chemistry, Institute of Chemical Technology, Technicka 5, Prague 6, CZ 166 28 Czech Republic

Received 6 April 2007; Accepted 10 October 2007

Raman spectral mapping of thin organic layers on metal substrates is an important analytical toolto characterize these systems. Surface-enhanced Raman scattering (SERS) spectroscopy is a suitabletechnique for analysis of such layers. Development of new SERS-active surfaces with repeatable propertiesand without disturbing adsorbed species is one of the important steps for reliable assessment of thethin organic layers designed. This paper presents new SERS-active substrates suitable for both macro(millimeter scale) and microscopic (micrometer scale) spectral mapping, which allow easy regeneration forrepetitive experiments. Both gold and silver SERS-active surfaces prepared by electrochemical depositionwere tested. Complete map data evaluation utilities were newly designed and applied, using bothordinarily used and newly modified mathematical algorithms and chemometric procedures. Evaluationof data starts with finite impulse response (FIR) filtration algorithms to eliminate spectral interferencesin individual spectra. Principal component analysis was used for transformation of multidimensionaldata to understandable dimensions. Various mathematical/statistical techniques were then used for datavisualization as spectral maps and for similarity testing. Copyright 2008 John Wiley & Sons, Ltd.

Supplementary electronic material for this paper is available in Wiley InterScience at http://www.interscience.wiley.com/jpages/0377-0486/suppmat/

KEYWORDS: massive SERS-active substrate; electrochemical deposition; spectral mapping; assembled monolayer;chemometric analysis

INTRODUCTION

Organic layers deposited on metal substrates1 can be usedas active layers (selectors) in chemical sensors or as partsof various nanodevices. In many chemical applications,especially in multicomponent quantitative analysis, it isnecessary to use very wide areas of receptor surfaceto guarantee proper sample analysis with reliable andrepeatable results. It is required to ensure well-definedrepeatable properties of these sensors for their correctfunction. The most important aspects are detection andcharacterization of sample attributes in wide surface areas.2

Adequate analysis of a wide area in a single measurement isnot possible and therefore spectral mapping is necessary forsuch assessment. For proper detection of sample parameters,it is essential to obtain a high signal with suppressed noise inindividual spectra. This can be achieved either by long-time

ŁCorrespondence to: Martin Clupek, Department of AnalyticalChemistry, Institute of Chemical Technology, Technicka 5, Prague6, CZ 166 28 Czech Republic. E-mail: [email protected]

data accumulation or by an appropriate data postprocessing,e.g., using filtration. The thorough surface analysis over awide area is required for a correct and full characterizationof a sample. FT-Raman/Raman spectral mapping is a goodtechnique for such analysis, because some metals (e.g. Ag,Au) possess the effect of surface enhancement of the detectedRaman signal.3 – 5

Surface-enhanced Raman scattering (SERS) spectroscopyis a commonly used method for analysis of organiccompounds.6,7 SERS-active metals enhance the intensityof the detected signal and allow analysis of very thin(even mono- and sub-monomolecular) layers.6 Homogeneityof measured signal over the surface area is influencedmainly by two factors: by the homogeneity of an individualsample layer (chiefly uniformity of its thickness) and by theregularity of SERS-active surface properties, i.e. homogeneity(or more precisely regularity) of enhancement factor values,active site distribution and the surface morphology. Hence,the SERS-active substrate preparation is a critical factor forsignal detection especially from very thin deposited layers

Copyright 2008 John Wiley & Sons, Ltd.

516 M. Clupek et al.

(e.g. self-assembled organic (mono) layers). One of the easiestways, that is widely used, is an electrochemical rougheningof more or less ideally flat electrodes by potential cycles.8,9

Regeneration of SERS metal electrodes after deposition ofsamples is problematic and the use of a new electrode foreach repetitive experiment is expensive.

Other methods are based on generation of thin gold SERS-active coatings on inactive substrates. Industrial surfacesare commonly based on vacuum thermal evaporation10 orsputtering11 of gold particles onto proper materials. Thesetechniques require expensive instruments. From a routinelaboratory point of view, a usable SERS-active surface canbe prepared easily electrochemically by coating an inactivematerial by cathodic reduction. Electrochemical preparationis a cheap method applicable for day-to-day experiments. It isnecessary to take into account the fact that the current densityhas the primary effect on the quality of an electrochemicallyformed gold surface.12

The main goals of this study are to present a compre-hensive approach to detection and evaluation of organiclayers on metal substrates using Raman spectroscopy fromappropriate design of an SERS-active metal surface for spec-tral evaluation including different ways of spectral mapcalculations. An improved procedure of electrochemicalpreparation of Au SERS-active surface and a new procedureof analogous Ag surface are reported and various algorithmsof spectral maps calculation are compared from the pointof view of their use for evaluation of metal surface quality,homogeneity and stability of the organic layers deposited.

The main goal of the development of a preparationprocedure was to find a method of repeatable formationof a plane surface from the macroscopic point of view (camillimeter scale) with suitable nanostructure that allowsSERS activity, which means maximum visual uniformity onthe millimeter scale (e.g. the same tone of gold color withoutany apparent alterations, no scratches and abrasions), andspectral homogeneity of the SERS-active surface at the sametime (i.e. maximum and uniform surface enhancement overa wide surface area). The other important aspect is the purityof the surface; i.e. no Raman bands should be observed inthe signal measured on the substrates prior deposition oforganic substances under common measuring conditions.

Electrochemical preparation procedure of an SERS-activegold surface on a Pt substrate developed by Zaruba et al.13

was the starting point of the present study. The gold-coated Pt substrate has suitable enhancement for a singleFT-Raman measurement but it is not appropriate for spectralmapping of organic layers. The main disadvantage ofthis very thin substrate (thickness of Pt target, 0.4 mm;thickness of gold layer, ca 1 µm) is an elastic form thatdoes not guarantee a plane surface. A plane and robustsubstrate is necessary to make sure that the measured signal(in)homogeneity is caused by parameters of the depositedorganic layers. Hence, the use of massive Pt targets wasfound to be appropriate, but an optimization of parameters

for electrochemical preparation of the Au layer was neededand a new procedure of Ag SERS-active surface formationhad to be developed.

Also, the homogeneity of deposited organic layer isa crucial factor for proper functioning of the developedsensor and its future use. On the basis of the compositionof deposited sample, self-assembled layers (monolayers ormultilayers) and organic films can be distinguished. Self-assembled layers are ordered forms of deposited organicspecies that consist of small amounts of organic substancesin a regular form, in which each molecule of the specifiedlayer is strongly (mostly covalently) bonded to a metalsubstrate or to a previous molecular layer. Fluctuationsof both species amounts and surface enhancement factorsrepresent the critical factors for the intensity of the detectedsignal of any molecular layer. On the other hand, there isa large number of organic compounds that can form theso-called organic films (unordered multilayers), in which themolecules of a specified substance may not be covalentlybonded to the surface or with another molecule together.The total amount of sample in the case of organic films cansuperimpose markedly the effect of weak interferences andsurface enhancement fluctuations. Organic films are suitableonly for qualitative detection of relatively small amount oforganic compound, but for the possibility of precise studyof molecular interactions and for preparation of sensingsurface, well-defined monolayers are required.

EXPERIMENTAL

Material preparation and procedureExperiments were performed mainly on massive platinumtargets (diameter 10 mm, thickness 2 mm, Safina, CzechRepublic). Various modifications of electrochemical depo-sition of either gold or silver were tested for preparation ofSERS-active surfaces. A special sample holder of the mas-sive targets manufactured in workshop of the Departmentof Analytical Chemistry, Institute of Chemical Technology,Prague, Czech Republic, was used for target fixation.

Platinum targets were first polished with metallographicpaper (Emery Paper, SIA, Switzerland), alumina and calciumcarbonate consecutively to obtain a clean, (macroscopically)flat surface of the target. Polished targets were then immersedinto a mixture of 30% hydrogen peroxide and 98% sulfuricacid (1 : 3 v/v) for 30 min and finally thoroughly washedwith redistilled water. Platinum targets were then coatedwith SERS-active metals (gold or silver).

The gold coating was performed electrochemically froma solution of K[Au(CN)2].13 Various current densities andcycles were tested. Table 1A shows the details of three mostimportant procedures (G1, G2 and G3) which are comparedlater. A large amount of cyanide ions was caught on thesubstrate during the gold coating process and needed tobe eliminated. Modification of the original procedure13 forelimination of cyanides was tested (Table 1B). Finally, the

Copyright 2008 John Wiley & Sons, Ltd. J. Raman Spectrosc. 2008; 39: 515–524DOI: 10.1002/jrs

Detection and assessment of thin organic layers on metal substrates 517

Table 1. Conditions of SERS-active surface preparation

(A) Current densities and cycles used during gold coating

Procedure Step no. Used current (mA) Current density (mA/cm2) Time (min)

G1 1 5 2.3 30G2 1 5 2.3 25

2 10 4.5 5G3 1 5 2.3 20

2 10 4.5 153 15 6.8 10

(B) Methods used for elimination of cyanides from Au SERS-active surfaces

Procedure Used method Interval (h)

C1 Immersion into boiling ammonium persulfate solution 5C2 Immersion into ammonium persulfate solution (50 °C) 5

(C) Silver plating procedures

Procedure Electrochemical bath Sequence of current densities Elimination of cyanides

S1 [Ag(CN)2]� prepared as follows:AgCN (1.4 g KCN, 6 g AgNO3 in50 ml H2O) dissolved in 200 ml ofbath (13 g KCN, 2.5 g K2CO3, 0.1 gNa2S2O3, 0.5 ml 30% NH3 in H2O)

Three steps: 5 min at2.3 mA/cm2, 10 min at9.1 mA/cm2 and 15 minat 15.9 mA/cm2

Immersion into a 15%solution of hydrogenperoxide for 5 h andreduction of oxidized silverby sodium sulfite.

S2 [Ag�NH3�2]C prepared from Ag2O(6%AgNO3, 10% NaOH in H2O) byexact dissolution in 30% ammonia.

Two steps: 5 min at2.3 mA/cm2, 1.5 min atca 33 mA/cm2

–

prepared SERS-active targets were thoroughly rinsed withredistilled water.

For silver coating of the targets, two different electro-chemical procedures (S1 and S2) were tested. The solutionsand current densities used are summarized in Table 1C. A flatsilver electrode was used as anode during the silver coating.Finally, the prepared SERS-active targets were thoroughlyrinsed with redistilled water.

The morphological comparison with commercially avail-able gold SERS-active substrates KLARITE (MesophotonicsLtd., UK) with regular nanometer-scale pattern was usedas a first check of the prepared SERS-active substrates. Thenanostructure comparison of these substrates was performedusing optical and scanning electron microscopy.

The process of sample deposition onto selected SERS-active substrates differs basically for organic self-assembledlayers and films. In case of preparation of organic films,the commonly used14 – 16 method involves deposition from asample solution in a volatile solvent. The sample solution isbasically dropped onto the substrate. Unordered multilayerorganic film is formed on the active surface after evaporationof the solvent. On the other hand, in the case of organic layersthe excess amount of sample is removed by washing witha pure solvent (that means, only strongly bonded moleculesremain on the surface).

Various types of thiol derivates, either aromatic oraliphatic, were used for formation of thin organic layers.The results reported in this study were obtained usingthree compounds: 4-aminothiophenol (90–95%, Fluka), 11-mercaptoundecanoic acid (95%, Sigma-Aldrich) and 16-mercaptohexadecanoic acid (90%, Sigma-Aldrich). All depo-sition processes were performed from solutions of samplesin volatile alcohols (either methanol p.a. or ethanol p.a.).Concentration range from 10�2 to 10�5 mol l�1 was tested.The SERS-active substrate was immersed into the samplesolution for different periods from several hours up to threedays. For preparation of organic films, the substrate was leftin air till the spontaneous evaporation of the solvent. Forpreparation of organic layers, the surface was thoroughlyrinsed with solvent and redistilled water repeatedly. Thesolvent removed any excess of organic substance that wasnot strongly/covalently bonded to the metal surface.

Data acquisition and evaluation methodsFT-Raman spectra of samples were measured on an FT-Raman spectrometer (Bruker FT-NIR spectrometerEQUINOX 55, Raman module FRA 106/S, Nd : YAG laser(excitation line 1064 nm, laser power ca 50 mW)) and a Gediode detector cooled with liquid nitrogen (Bruker Optics).



The FT-Raman spectrometer was equipped with a TLC map-ping stage (Bruker Optics) designed by the manufacturer formacroscopic mapping of thin-layer chromatographic plates.The diameter of the laser spot on the target was ca 0.3 mm.

The dispersive micro-Raman spectrometer LabRam(Dilor Jobin-Yvon, France) with excitation line 633 nm(He–Ne laser 633 nm, maximum laser power ca 20 mW) wasused for the micromapping measurement. The spectrometersystem was equipped with microscopic objectives (mag-nification 10ð, 50ð and 100ð) and a computer-controlledmapping sample stage. The diameter of the laser spot on thetarget was ca 2 µm under common experimental conditions(objective 100ð, fully opened aperture).

A Scanning electron microscope, S4700 (Hitachi, Japan),was used for checking the morphology and microstructureof the SERS-active surfaces.

The FT and dispersive Raman spectral data were col-lected using software OPUS 4.2 (Bruker Optics) and LabSpec2.6 (DILOR, France; University de Reims), respectively. Bothdata were exported to ASCII XY format for further process-ing. The data evaluation was performed under the Matlabsystem 6.5 (The MathWorks Inc., USA) using utilities basedon the filtration and transformation algorithms describedbelow. Experimental Raman spectra represent a multidi-mensional complex data (vectors in multidimensional space)with mutually correlated information frequently interferedwith a series of influences. These vectors are not easily inter-pretable. Matlab utilities have been programed to solve theproblem of data preprocessing, data evaluation and propervisualization of results.

Filtration of spectral noise was performed by a low-pass finite impulse response (FIR) filter programed inMatlab system, which separates the high-frequency noisefrom the measured signal. Other FIR filter with a lowercut-off frequency was then used for the creation of acorrection curve. This correction curve was subtractedafterwards from the measured spectral data to eliminatebroadband (longtime) background interferences. Detaileddescription of algorithms of these filtration techniques hasbeen published.17

Hence, after the suppression of interfered influences(noise, background), the complete data set was analyzedfor homogeneity and similarity of spectral parameters over awide sample area using various methods of chemometricanalysis. The goal of chemometric assessment was thetransformation of a matrix of the measured spectra tonew datasets, which are more suitable for interpretationof experimental results and easy viewability.

The visualization of spectral results was demonstrated inseveral types of maps, which could be divided into two maingroups, i.e. the correlation maps and maps based on principalcomponent analysis (PCA). The group of PCA maps consistsof the maps of individual principal component (PC) levels(score values) and the newly designed RGB-PCA maps. TheRGB-PCA map means that each map point has the color

Figure 1. Control chart calculated for the comparison of FTRaman spectral data measured on a gold surface withdeposited 4-aminothiophenole with the data of the targetbefore deposition. Control chart was calibrated toPCA-transformed data of a gold SERS-active target withoutorganic layer. Both spectral data sets contain 315 measuredspatial points.

defined by intensities of red (R), green (G) and blue (B) colorcomponents, which are given by the score values of threeconsecutive PCs. Thus the RGB-PCA map displays a part ofthe spectral information transformed into three consecutivePCs. Score values of the first, second and third PCs describetypically more than 80% of the spectral variability of themap data set; thus the values of these three componentsare usually used to determine the intensities of R, G and Bcontributions for specific point color. Hence, the variabilitytransformed into colors is related to the variation of spectralcharacteristics, while the noise variation is omitted (the noisevariation is related to higher PCs (above 5)). Correlationmaps are based on the ordinary correlation coefficient18

of individual spectra and selected template (reference). Inthis study the average spectrum of the whole data set,the spectrum nearest to the center of PCA model and thespectrum measured in the center of the analyzed area weretested as possible correlation templates to study the effectof template selection on the maps obtained. For the primarycheck of outliers, i.e. incorrectly measured or nonrelevantdata, either the cluster analysis based on Ward’s algorithmor a recently developed utility based on control charts19 wasapplied. The mentioned utility was also used for mutualcomparison of various spectral maps to assess their generaldissimilarity. For example, a control chart (Fig. 1) was createdto check the effect of 4-aminothiophenol deposition on agold surface. The PCA-transformed FT Raman spectral dataof a gold surface after deposition were compared with acalibration set based on data measured before deposition.The difference between the two data sets is evident, and



the data obtained after deposition are mostly close to thewarning limit calculated using the calibration set. Someoutlying points are apparent, too. That means, the furthercalculations of spectral maps are meaningful.

RESULTS AND DISCUSSION

SERS-active metal substratesIn the case of gold coating of Pt targets, the current of 5 mAused by Zaruba et al.13 was selected as a starting point forthis study. The thin bright gold film was formed at thiscurrent density of 2.3 mA/cm2 (procedure G1 – Table 1A).The gold film formed covered all sporadic microscopicimperfections of the Pt target, e.g. some few scratches orgrooves, and produced a flat, bright surface that was notsuitable for direct enhancement of Raman signal but wasvery useful as a basis for subsequent steps. Therefore, allfurther used procedures of gold-coating adopted this currentdensity as the first step (Table 1A); subsequent steps usedhigher current densities to achieve the SERS-active surface.Interfering cyanides adsorbed on the SERS-active surfaceduring the gold coating process were eliminated finally bymethod C1 (Table 1B). The Raman bands of cyanides wereobserved after the treatment C2, but they were not detectedabove noise level when the method C1 was used. The factthat the procedure previously used by Zaruba et al.13 (C2)did not remove the cyanides can be presumably explainedconsidering that in the case of using massive targets longerelectrochemical deposition of higher amount of gold fromcyanide bath was necessary and therefore a higher amountof cyanides was strongly adsorbed on the gold surface layer.

Similar procedures were used for the silver coating. Asin the case of gold surfaces, a thin bright silver film wasproduced at current density of ca 2.3 mA/cm2. The silverfilm became dark at higher current densities. The use ofthe cyanide bath (S1) was omitted finally, because we didnot find any procedure to obtain a clean surface withoutinterfering anions. The bands of cyanides were eliminatedfrom the spectra after the use of the procedure describedin Table 1B, but strong bands of sulfites appeared in thespectra measured. Procedure S2 used an ammonia bath, anda clean surface was obtained directly without any spectralinterference. Hence, the Ag surface prepared in ammoniabath is suitable for deposition of organic substances.

The morphological properties of SERS-active gold sub-strates (prepared by procedures G2 and G3) are very similarand a comparison of the developed SERS-active substratewith a commercial one is shown in Fig. 2. It illustrates boththe similarities and dissimilarities of properties of the elec-trochemically prepared gold surface with the commercialsurface KLARITE on various scales. Quite similar homoge-neous planar surfaces with a few local impurities and/ordefects are observed in the submillimeter range (Fig. 2; A1,A2). At higher optical magnification, a uniform roughness is

observed in the case of the electrochemically prepared sub-strate (Fig. 2 – B1) compared to strictly regular microstruc-ture of the commercial substrate (Fig. 2 – B2). The imageof electrochemically prepared Au surface on a micrometerscale (Fig. 2 – C1) shows the presence of gold sub-micrometerplates, which are responsible for the SERS-activity, even withnear-infrared excitation. The regular pyramidal morphologyof the gold-coated textured silicon is observed at the KLAR-ITE substrate using comparable magnification (Fig. 2 – C2).Finally, in the case of comparison of nanoscopic featuresof both substrates (Fig. 2 – D1, D2), we found quite similargold granular particles on both surfaces. Summarizing, wecould see the much higher regularity of the KLARITE sub-strate on the micrometer scale compared to electrochemicallyprepared surface, but from the point of view of macroscopicmapping (at the millimeter scale) and nano-particle structure,there is a lot of similarities of both substrates.

Organic layers and filmsDepositionThe concentration of organic solution higher than10�4 mol l�1 is suitable for forming organic monolayer atacceptable time scales; 10�4 –10�5 mol l�1 can be used for for-mation of unordered thicker films. In the case of use of lowerconcentrations, the individual spectra of spectral maps withrather limited number of scans per spectrum (usually 128)are interfered with spectral noise and therefore the evalua-tion of spectral maps is not sufficiently reliable. An increasein the number of scans, which can improve the signal tonoise (S/N) ratio, dramatically extends the collection time ofthe whole map.

Both the Raman and FT Raman signals of thicker filmswere detected at all tested surfaces regardless of immersiontime intervals. In the case of assembled layers, the immersiontime affects strongly the spectral information obtained ondifferent types of metal substrates. Reliable signal of organiclayer on silver surface was first detected after at least 5 hof immersion of the target. In the case of gold surface, it isnecessary to leave target in a solution of organic adsorbatefor at least 10 h. The S/N ratio increases with continuationof the immersion time up to 24 h, but further prolongationdoes not cause any improvement of the spectra collected.The laboratory temperature of solution used was acceptablefor all types of organic substances deposited, and an increaseof temperature up to 50 °C does not significantly influencethe Raman/FT Raman spectral data obtained.

Detection and signal assessmentThe detection and signal assessment of organic layers wasbased on the fact that in the spectra of the surface of theSERS-active substrates before deposition, there were novisible interferences, from which it follows that all detectedvibrational bands after deposition are caused by the organiclayers deposited.



Figure 2. Comparison of appearance of prepared SERS-active gold substrate (1) and commercially available substrate (2). Imageswere obtained by optical microscope (A, B) and electron microscope (C, D).

In the case of gold surfaces, the worst Raman/FT Ramansignal was detected on the surface prepared according theprocedure G1 (Table 1). Actually, the signal of relativelythick organic films dropped on this surface was still very lowand in the best points it was at the limit of 3 times higherintensity compared to the level of actual noise. The assembledlayers were undetectable on this highly reflective surface.On the other hand, the most intense signal of the organicmonolayer and the best S/N ratio for all the compoundstested were obtained on the surface prepared accordingto the procedure G2, and deposited organic samples evenat (sub-)monomolecular layer level were detected easily(Fig. 3(a)). Gold surface prepared according the procedure

G3 had also a good level of measured Raman signal (at both633 and 1024 nm excitation wavelengths) but systematicallylower than in the case of procedure G2. A higher currentdensity than used in procedure G1 was necessary for thegeneration of SERS activity of the surface, but quite shorttime of approximately twice higher current density used inthe G2 procedure (Table 1) was sufficient. Further increaseof current density applied in the procedure G3 did notimprove the surface enhancement. It may be noticed thatthe FT Raman signal obtained for layers on the KLARITEsubstrate was very weak compared with surface preparedby G1 procedure; with the 633-nm excitation better spectrawere obtained but their S/N ratio was significantly worse



than for the electrochemically prepared surfaces (proceduresG2 and G3).

The preparation procedure S2 based on ammonium bathallowed preparation of a clean silver SERS-active surfacewithout observation of any spectral interference. Both theorganic films and assembled monolayers were detectable onthis silver surface. High S/N ratio was achieved for differentthiolate layers over the whole measured area but the signalhomogeneity was lower than in the case of gold surface. As inthe case of the gold surface, the silver SERS-active substrateallowed the detection of deposited organic species at (sub-)monomolecular layer level (Fig. 3(b)).

Summarizing, on both Au and Ag surfaces it is possibleto observe good-quality detailed parts of Raman spectra andto analyze the structure of overlapping vibrational bands(Fig. 3). For example, differences between two aliphaticcompounds are clearly visible in the range of the bandsof CH stretching vibrations at about 2880 cm�1. Intensitiesof individual bands can be used reliably for generation ofclassical spectral maps.

Data evaluation and map generationSpectral data collected in individual mapping experimentswere evaluated by mathematical and chemometric algo-rithms. Modification of FIR filtration was used for the sup-pression of spectral interferences, especially for the reductionof spectral noise and correction of spectral background.17 It isshown in Fig. 4 that a proper selection of filtration parameterslead to a considerable suppression of spectral backgroundand noise, while the relevant vibrational bands of an ana-lyte were preserved without apparent distortion even in thecase of very noisy data with deformed background shape

Figure 3. Details of Raman spectra measured on preparedSERS-active substrates using dispersive Raman spectrometer.Spectrum of 16-mercaptohexadecanoic acid measured on Auactive surface (a), and spectrum of 11-mercaptoundecanoicacid measured on Ag substrate (b). Spectrum (a) is offset by3000 units.

obtained for a weakly bonded species. This data processingallowed considerable shortening of FT Raman data accu-mulation because the number of scans per spectrum couldbe reduced from 1024 (routinely used in individual spectracollection) to 128. Nevertheless, a proper analysis of largemaps with increased number of acquisition points (for exam-ple 27 ð 27 (i.e. 729 acquisition points) instead of 10 ð 10) oforganic layers is preserved. Thus, either better spatial reso-lution can be achieved or bigger area can be analyzed in anacceptable time.

An integral of a part of the spectrum is mostly used inthe classical approach of spectral mapping; a spatial distri-bution of some selected species is viewed. The aim of thisstudy was to generate maps based on a broad spectral rangeto cover many spectral features and to evaluate repeatabil-ity of preparation/deposition procedures, homogeneity andtime stability of the layers prepared. The generated spec-tral maps based either on correlation coefficients or PCAdescribe clearly the spectral homogeneity and/or hetero-geneity in wide areas of examined surfaces. A similar colortone means that the spectra are very similar either in thevalue of correlation coefficient or in the selected PC’s scorevalues. Figure 5 (A1, A2) shows that the PCA-transformedspectral data of substrate surface and ambient sample holdersurface are more similar in the case of the uncovered SERS-active substrate without deposited organic sample (wherethe spectra without any apparent Raman bands are col-lected) than in the case of the surface with deposited thiolatemonolayer, where the PCA-transformed data are markedlydifferent, enhancing the contrast between the target area withthe deposited organic layer and the surroundings withoutany deposition. It is clearly visible from generated spectral

Figure 4. Measured FT-Raman spectrum ofN,N0,N00-(nitrilotriethane-2,1-diyl)trinicotinamide on Au target(a) and the filtered one with both background and noise FIRfilters (b). The spectra are in the same scale.



Figure 5. Comparison of various maps of SERS-active surface before deposition of organic substances (1), and after deposition of4-aminothiophenole (2). Maps of intensity of first principal component (score values) (A), correlation maps based on correlation withcentral spectrum of PCA model (spectrum outside the target) (B), and with central spectrum of target area (C). Maps were generatedon the basis of FT-Raman spectra.



maps (Fig. 5) that the mathematical algorithm used for theirgeneration highly affected their patterns. Each map typeprovides an enhancement of some type of information andthus a proper algorithm has to be selected on the basis of thecharacter of information required. For example, in the caseof a correlation map with the template spectrum closest tothe center of PCA model (Fig. 5(B)), the effect of differencesamong individual spectra in an area outside the target is sup-pressed in the final map, while the contrast between the dataobtained on the target and outside is enhanced. (Note: thecenter of PCA model of described example lies outside theanalyzed massive Pt target, which is affected by the numberof points on the target and outside it). On the other hand, inthe case of correlation with a central spectrum of the wholeanalyzed area (Fig. 5(C)), the differences in the area outsidethe target are clearly visible. Furthermore, there is an appar-ent similarity of several points on the metal target withoutorganic deposits and points outside the target. The describedanalysis shows high similarity of spectra measured on thewhole area of a target, demonstrating uniformity of surfaceenhancement on a very large substrate and homogeneity ofthe deposited layer, especially in the case of gold surfaces.The mapping procedure and spectral map evaluation can beused further for tests of repeatability of the results. Mapsgenerated from repeated analyses (Fig. 6 – PCA-RGB maps)of the same area of an identical organic monolayer on a sil-ver SERS-active substrate show the unchanged characteristicfeatures of the sample layer while the effect of the overallaging of layer is also visible. The patterns along rows andcolumns of the map are preserved in repeated experimentswhile the general color tone is moved. The relative mutualdifferences among individual points are repeatable while theoverall intensity of signal is changed (see SupplementaryMaterials or online version for colored graphical maps).

CONCLUSIONS

Optimized methods of electrochemical preparation of bothgold and silver SERS-active surfaces on massive Pt targets,

deposition of organic thiol derivatives on these surfacesand the subsequent procedures of spectral data processingand spectral maps generation were developed in onecomprehensive process. The prepared SERS-active metalsurfaces do not exhibit any Raman band prior to thesample deposition, demonstrating that the surfaces arenot contaminated with any interfering adsorbate (ions ormolecules originating from the preparation procedure). Thehomogeneity of spectral response (somewhat noisy straightline) of these clean surfaces was confirmed. Both goldand silver SERS-active substrates allow detection of theorganic self-assembled monolayers both with visible andnear-infrared excitation. The spectral responses of layers ongold surfaces are more homogeneous (uniform) than of thoseprepared on silver surfaces. The form of massive Pt targetallows repeatable use of this substrate. The massiveness ofthe Pt target allow easy handling with the sample withoutany risk of mechanical deformation (some flexion, bulge,etc.) of the flat Pt surface during preparation and verysimple regeneration of SERS-active layer based on a preciseabrasion of previous Au (Ag)-deposited layer system and ondeposition of a new one.

Previously developed algorithms for post-eliminationof interfered spectral features based on FIR filtrationwere successfully applied. Various methods of spectralmap generation based on PCA calculation and correlationcoefficient evaluation were used to enhance the requiredpart of information from the original data, especially fromthe point of view of overall uniformity of spectral featuresand stability of signals. Utilities for computing of PCAmaps and correlation maps can be used not only for Ramanspectroscopic analysis of organic layers on metal substratesbut more generally also for any spectroscopic mapping.These types of maps can be used for rather quick evaluationof possible changes in properties (both spatial and temporal)of a surface layer. Both the (in)homogeneity and (in)stabilityof the systems can be viewed easily. Furthermore, therepeatability of system preparation can be evaluated reliably.

Figure 6. PCA maps (converted to gray scale) of a segment of Ag SERS-active target with deposited 16-mercaptohexadecanoicacid immediately after deposition (A), and one day later (B). Both maps were created using dispersive Raman spectra.



Therefore, the time-consuming evaluation of individuallymeasured spectra (hundreds or even thousands in oneexperiment) is necessary only if evident changes (or outlyingcharacteristics) are detected. This process of data evaluationminimizes the time required for the study of preparedorganic layers and makes easier the prospective study oftheir interactions with some analytes.

Supplementary materialSupplementary electronic material for this paper is availablein Wiley InterScience at: http://www.interscience.wiley.com/jpages/0377-0486/suppmat/

AcknowledgementsFinancial support of Ministry of Education, Youth and Sportsof the Czech Republic (grant MSM 6046137307) is gratefullyacknowledged.

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Raman spectral detection and assessment of thin organic layers on metal substrates: systematic...

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