CGA PDF Banner - static.ifp.tuwien.ac.at

Journal of Microscopy, Vol. 00, Issue 0 2016, pp. 1–8 doi: 10.1111/jmi.12506

Received 18 May 2016; accepted 30 October 2016

A novel substrate for multisensor hyperspectral imaging

J . O F N E R ∗, J . K I R S C H N E R†, E . E I T E N B E R G E R ∗, G . F R I E D B A C H E R ∗, A . K A S P E R - G I E B L ∗,H . L O H N I N G E R ∗, C . E I S E N M E N G E R - S I T T N E R† & B . L E N D L ∗∗TU Wien, Institute of Chemical Technologies and Analytics, Vienna, Austria

†TU Wien, Institute of Solide State Physics, Vienna, Austria

Key words. Electron microscopy, energy dispersive X-ray spectroscopy,imaging substrate, multisensor hyperspectral imaging, Ramanmicrospectroscopy.

Summary

The quality of chemical imaging, especially multisensor hy-perspectral imaging, strongly depends on sample prepara-tion techniques and instrumental infrastructure but also onthe choice of an appropriate imaging substrate. To opti-mize the combined imaging of Raman microspectroscopy,scanning-electron microscopy and energy-dispersive X-rayspectroscopy, a novel substrate was developed based on sput-tering of highly purified aluminium onto classical microscopeslides. The novel aluminium substrate overcomes severaldisadvantages of classical substrates like impurities of the sub-strate material and contamination of the surface as well as sur-face roughness and homogeneity. Therefore, it provides excel-lent conditions for various hyperspectral imaging techniquesand enables high-quality multisensor hyperspectral chemicalimaging at submicron lateral resolutions.

Introduction

Chemical imaging and hyperspectral imaging became a majortask in modern analytical chemistry. Due to rapid develop-ment of spectroscopic techniques and instrumentation, today,chemical imaging is available for a large number of spectro-scopic techniques.

In case of vibrational spectroscopic imaging, Raman mi-crospectroscopy (RMS) in the submicron lateral scale has beenapplied to a variety of analytical issues such as, e.g. fine arts(Kosarova et al., 2016), integrated circuits (De Wolf, 1996),aerosol particle analysis (Batonneau et al., 2006), geology(Burke, 2001) or biomedicals (Antonio & Schultz, 2014). Op-tical near-field techniques also extend RMS to the nanometerscale (Bailo & Deckert, 2008). Although RMS allows an image-based vibrational analysis of the sample, energy-dispersive X-ray (EDX) imaging is widely used to uncover the elemental

Correspondence to: J. Ofner, TU Wien, Institute of Chemical Technologies and Ana-

lytics, Getreidemarkt 9, 1060 Vienna, Austria. Tel: +43 (1) 58801 15177; e-mail:

[email protected]

composition of various samples (Krejci et al., 2005; Laskinet al., 2006; Conny, 2013). Infrared spectroscopic imagingas a complementary technique to RMS also contributes tothe field of vibrational chemical imaging (Bhargava, 2012)with the ability of doing near-field spectroscopy and imaging(Centrone, 2015). Also, mass spectrometric methods like, e.g.time-of-flight secondary ion mass spectrometry (ToF-SIMS)contribute to hyperspectral image-based analysis (Font Palmaet al., 2007).

These and other imaging techniques have been combined toallow a sequential chemical analysis of the same target analyteand structure, especially in the case of atmospheric particulatematter (Ryu & Ro, 2009; Sobanska et al., 2014).

Lohninger & Ofner (2014) published a chemometric ap-proach to combine several hyperspectral datasets, originatingfrom different imaging techniques, into a single multisensorhyperspectral image (MSHSI). The combined statisticalanalysis using multivariate algorithms such as principal-component analysis, hierarchical cluster analysis and vertexcomponent analysis could be demonstrated successfully andhighlighted the advantages of MSHSI (Ofner et al., 2015).

For every single hyperspectral imaging technique, optimizedand dedicated imaging substrates are available, which allowchemical imaging at optimal background conditions. How-ever, the choice of an appropriate substrate becomes crucial,when different imaging techniques are combined. Fourier-Transform Infrared Spectroscopy (FTIR) and EDX Imagingwere combined for the analysis of atmospheric aerosol par-ticles using aluminium foils (Ryu & Ro, 2009), where surfacepatterning of the foil is even visible in the chemical images.Combined Attenuated Total Reflectance (ATR)-FTIR and EDXimaging of particles on silver foils also exhibit an influence offlutes of the lumbered foils on the chemical images (Jung et al.,2010). Silicon wafer were used for atomic force microscopy,EDX, Raman and ToF-SIMS imaging (Sobanska et al. (2014)).Lanni et al. (2014) combined SIMS and confocal Raman mi-croscopy also using silicon as a substrate. Silicon exhibits astrong Raman signature, which is able to cause saturation of

C© 2016 The AuthorsJournal of Microscopy C© 2016 Royal Microscopical Society

2 J . O F N E R E T A L .

Fig. 1. Comparison of RMS and EDX spectra of commonly used Raman imaging substrates.

the detector and therefore hides vibrational features of possi-ble target analytes. Nelson et al. (2001), performing combinedRMS and Scanning Electron Microscopy (SEM), point out that‘A key step in Raman/SEM analysis of fine particulate matter ischoosing an appropriate filter substrate that meets the require-ments of both techniques’. They have selected polycarbonatefor the combined analysis as a filter material, although theystate that quartz appears to be the best-suited target material.However, some bands of the quartz are visible in the Ramanspectra. Therefore, the choice of an appropriate substrate is a

challenging task when combining different techniques as it isthe case in MSHSI. The present study will discuss disadvan-tages of different existing target substrates and introduce anovel target substrate for multisensor hyperspectral imagingon the example of RMS and SEM-EDX imaging.

Commonly used substrates and multisensor imaging

Different substrates for RMS have been reviewed recentlyby Ramoji et al. (2016). For RMS and Raman imaging, e.g.

C© 2016 The AuthorsJournal of Microscopy C© 2016 Royal Microscopical Society, 00, 1–8

S U B S T R A T E F O R M U L T I S E N S O R H Y P E R S P E C T R A L I M A G I N G 3

Fig. 2. Superimposition of Raman chemical images and SEM images to compare (A) household aluminium foil, (B) technical aluminium foil (Rotilabo R©-aluminium foil), (C) GoodFellow and (D) ADVENT research-grade aluminium foils: blue spots – silicon inclusions; red spots – carbon contaminations.

glass, quartz, CaF2 and silicon substrates are widely used(Fig. 1). These substrates exhibit significant Raman bands,which might cover features of the target analyte. Therefore, abackground-free target substrate for RMS measurements is ofhighest interest. The EDX spectra of glass, CaF2 or silicon ei-ther prevent the detection of included elements or cover X-rayemissions of other elements of interest (Fig. 1). Therefore, forenvironmental samples like precipitated particles, SEM-EDXmeasurements of the substrates for RMS measurements (men-tioned above) fail because of their complex X-ray spectrum.

Organic substrates such as, e.g. glassy carbon, polycarbon-ate or Polytetrafluoroethylene (PTFE) are possible substratesfor electron microscopy. These carbon-based substrates ex-hibit a significant X-ray fluorescence which covers organicfeatures of the target analyte. These organic substrates causecomplex Raman bands and therefore hamper the interpre-tation of RMS images. Further, sputtering with conductiveelements is important for interference-free image formationby electron microscopy.

For other imaging techniques, for example, mass spectrome-try (MS), also spectroscopically, simple background substratesare needed because complex fragmentation patterns of, e.g.organic substrates like glassy carbon or polycarbonates alsosignificantly influence the resulting spectrum and hamper theinterpretation.

For MSHSI approaches, the choice of a substrate which al-lows a nearly background-free imaging approach of all ap-plied techniques is crucial. Especially the significance of thecombined chemometric approach using multivariate statis-tics is depending on the quality of the target substrate. For theabove-mentioned methods, it turned out that an aluminiumsurface appears to be highly promising. Pure metallic alu-minium exhibits no Raman bands and the passivation layerof aluminium is hardly visible in Raman measurements. ForSEM, aluminium provides conductivity as a substrate. There-fore, sputtering of the samples with, e.g. gold or carbon is notnecessary. The X-ray spectrum of aluminium in EDX anal-ysis exhibits a Kα band at 1.486 keV, which overlaps with



Fig. 3. . Superimposition of EDX chemical images and SEM images to compare (A) household aluminium foil, (B) technical aluminium foil (Rotilabo R©-aluminium foil), (C) GoodFellow and (D) ADVENT research-grade aluminium foils: blue spots – silicon inclusions; green spots – iron inclusions.

Fig. 4. Recrystallization of aluminium due to the high purity of the sputtering target (AFM image (left) and SEM image (right)).

bromine (Lα at 1.480 keV). However, the X-ray spectrum ofaluminium allows to detect the main elements of interest inenvironmental, biological and material analysis. In general,pure aluminium appears to be a suitable target substrate forRMS and SEM-EDX MSHSI.

Evaluation of commercial aluminium substrates

Several types of commercial aluminium substrates are avail-able. Aluminium foils are easy to handle for sample prepara-

tion and measurements. Commercial foils span a range fromsimple and cheap household to technical and highly purifiedfoils as a so-called research material. The following aluminiumfoils were characterized in detail: (1) a household aluminiumfoil (supplied by a local food store chain, low purity (not spec-ified)), (2) a technical aluminium foil (Rotilabo R©-aluminiumfoil 20 µm – purity > 99.0% – supplied by Carl Roth GmbH +Co. KG, Germany), (3) a research grade aluminium foil(AL000540 – purity > 99.99% – supplied by GoodFellowCambridge Limited) and (4) a research grade aluminium foil



Fig. 5. Surface roughness versus density of recrystallized aluminium grains plot of the novel substrate at different sputtering rates (nm s−1, indicated inthe graph) (A) and SEM image of a high-rate sputtered substrate (B).

(AL107000 – purity > 99.99% – ADVENT Research Materi-als Ltd Oxford) (Figs. 2 and 3). To evaluate the applicabilityof these foils, RMS and SEM-EDX imaging were performed onselected substrates.

Raman measurements for the foil comparison were per-formed using a HORIBA LabRam 800 HR Raman microscopeusing a frequency-doubled 532-nm NdYAG laser (DPSS laserfrom OXXIUS) with a 300 lines/mm grating and an open-electrode charged-coupled device (CCD). The 100 × 100 µmgrids with a lateral resolution of 1 µm were sampled in SWIFT-mode using a scan time of 0.05 s per pixel. Data acquisition wasdone using the software package LabSpec 6. SEM-EDX mea-surements were performed using an FEI Quanta 200 scanningelectron microscope with an EDAX EDX detector. The micro-scope was operated at a voltage of 20 kV with an image mag-nification of 2600. All hyperspectral images were processedusing the software package Imagelab (www.imagelab.at).

Light microscopy and confocal RMS (Fig. 2) as well asSEM-EDX (Fig. 3) of the selected aluminium foils showedseveral disadvantages of these substrates. All foils exhibita structured surface, dominated by flutes, cracks and meltouts with a low surface homogeneity. These surface struc-tures influence the reflection and scattering properties ofthe laser in RMS. Further, metallic and organic contam-inants can be found on the surface but also inside thefoils. In household and technical foils, silicon inclusions andblack carbon can be detected by RMS (Figs. 2A and B).EDX uncovers strong silicon and iron inclusions in thesefoils (Figs. 3A and B). Although research grade aluminiumfoils are characterized by a lower surface roughness (Figs.2 and 3C and D) and do not exhibit any detectable metal-lic inclusions like silicon and iron, these foils are strongly

contaminated by carbon on the surface (Figs. 2C and D).These carbon contaminations hamper a background-free de-tection of carbonaceous particles.

In general research grade, aluminium foils exhibit a higherpurity related to metallic contaminations than household andtechnical foils. On a first glance, their lower surface roughnessand fewer amounts of flutes, cracks and melt outs make themmore suitable as a substrate for imaging purpose. However,RMS and SEM-EDX imaging of organic or carbonaceous sam-ples is hampered by the high carbon content on the surface.Thus, the technical foil (Figs. 2B and 3B) appears to be bettersuitable for multisensor imaging of atmospheric particles. Itexhibits a low amount of carbon on the surface and a separa-tion of the silicon band of the RMS signal from the multisensorhyperspectral dataset is possible. In conclusion, although alu-minium appears to be a well suitable substrate for multisen-sor imaging, the available aluminium foils can only be usedwith limitations, due to their surface structure, impurities andinclusions.

Processing of the novel aluminium substrate

To overcome the limitations of the aluminium foils describedabove, a novel aluminium substrate was developed. Highlypurified aluminium was chosen as surface material, due to itsgenerally good properties for multisensor chemical imaging.

An aluminium sputtering target with a purity of 99.999%(Advent Research Materials Ltd, 50 mm diameter, 5.0 mmheight) was chosen as the main aluminium source. Thishighly purified aluminium was sputtered onto commercialmicroscope cover slides (Menzel glasses, 25 mm diameter,class #1) which were cleaned by rinsing with ethanol for



Fig. 6. Comparison of the of the technical aluminium foil (Rotilabo R©-aluminium foil) (A) with the novel aluminium substrate (B): (1) superimposition ofthe intensity variations of the reflected 488 nm Raman laser and (2) of the baseline variations of the RMS measurements.

1 min. Due to the penetration depth of the electron beam forEDX measurements, a minimum required coating thickness of3 µm was required to be able to operate the EDX imaging upto 20 kV acceleration voltage.

Sputtering of highly purified aluminium onto the coverslides was done using a planar circular magnetron sourcewith a target substrate distance of 30 mm. The sputtering gaswas argon at a process pressure of 7 × 10−3 mbar, measuredusing a Baratron absolute pressure transmitter. The back-ground pressure was 8 × 10−7 mbar. The sputtering powerwas varied between 100 and 200 W with sputtering rates upto 9.9 nm s−1. Substrate temperatures spanned a range fromroom temperature to 60°C.

During the sputtering process, the high aluminium purityof the sputtering target caused recrystallization of aluminiumgrains on the surface of the new target (Fig. 4). This aluminiumgrains do not influence the baseline of the Raman spectra orchange the X-ray image of the overall aluminium substrateand therefore do not influence the chemical imaging. How-ever, during optical or electron microscopy, these grains mightbe recognized as aerosol particles themselves, e.g. by particle

finder algorithms (SOLO-MIA from eigenvector research orImageJ).

The sputtering process was optimized by increasing thesputtering rate which significantly reduced the number ofrecrystallized aluminium grains and therefore the surfaceroughness, which was determined by atomic force microscopyand calculated using the software packages SPMLabAnalysisV7.00 (Veeco) and ImageJ (Fig. 5). Due to the increased sput-tering rate, the deposited aluminium remained more amor-phous. The increased sputtering rate also caused a higherthermal stress of the glass slides. At a sputtering rate of 9.9 nms−1, a significant reduction of the density of recrystallized alu-minium grains could be achieved. Best results were achievedat this sputtering rate with a sputtering power of 200 W atroom temperature (25–29°C). The thickness of the sputteredlayer was 3 µm.

Chemical imaging using the novel aluminium substrate

To evaluate the quality of the novel substrate in comparisonto the technical aluminium foil, they were used as substrates



Fig. 7. Multisensor hyperspectral images (superimposition of the combined chemical dataset with the SEM images) of deposited atmospheric particlesfrom the city of Vienna on (A) the technical aluminium foil and (B) the novel aluminium substrate: soot (red), organics (yellow), NaNO3 (ocean), Fe2O3

(orange), silicates (pink) and CaCO3 (green).

for sampling of atmospheric aerosol particles and subse-quent multisensor hyperspectral imaging including RMS andSEM-EDX.

Sampling was done in November 2015 in the city ofVienna (Austria). Two Sioutas cascade impactors (SKC, PA,USA) were used with Leland Legacy sampling pumps (alsoSKC) at a nominal flow rate of 10 L min−1 for 2 h. Thedeposited particles were analysed afterwards by RMS usinga WITec alpha300 RSA+ confocal Raman microscope. A488 nm DPSS laser at 2 mW power was applied. Recording ofthe Raman spectra was done using a 600 lines mm−1

grating and an EMCCD camera. An area of 200 ×200 µm with a lateral resolution of 250 nm (800 ×800 spots) was scanned at an integration time of 0.01 s perspot. The same area was subsequently analysed using electronmicroscopy (FEI Quanta 200 as mentioned above) and EDXimaging (EDAX EDX detector) at an acceleration voltage of20 kV. Multisensor fusion of the RMS and EDX hyperspectraldatasets with the high-resolution SEM image was done usingthe software package Imagelab (Epina GmbH, Austria).

Surface roughness and inhomogeneity of the aluminiumfoils strongly influence the reflected intensity of the 488 nmRaman laser (Figs. 6 , 1A). The novel substrate does not exhibitthese fluctuations (Figs. 6 , 1B). Due to the fluctuation in lightscattering, also the scattered Raman intensities vary. Hence,the novel substrate assists the mapping of quantitative Ramanscattering in a better way. Additionally, the baseline of theRMS dataset is strongly influenced by the substrate. Cracks andflutes of the aluminium foil significantly contribute to changesof the baseline (Figs. 6, 2A), whereas the baseline achievedfrom the novel substrate appears very homogeneous (Figs. 6 ,2B). Therefore, the novel substrate fulfils major requirementsfor high-quality and possible quantitative Raman imaging.

No contamination of other metals than aluminium could beverified at EDX measurements at an acceleration voltage up to20 kV. At 30 kV, characteristic elements of the glass substratebecame visible.

The multisensor hyperspectral imaging could be signifi-cantly improved by applying the novel aluminium substrate(Fig. 7). The allocation of chemical species to atmosphericparticles deposited on the substrate can be achieved with-out background and scattering variations and impurities ofthe substrate itself. The images are not disturbed by cracks,flutes and blooming. For particles collected in Vienna, typi-cal chemical fingerprints like soot, organic species, NaNO3,Fe2O3, silicates and CaCO3 could be demonstrated usingRMS and SEM-EDX multisensor hyperspectral imaging at asignificantly increased image quality (Fig. 7).

Conclusions

The choice of an appropriate substrate is crucial for chemi-cal imaging, especially when several imaging techniques arecombined as in the case of multisensor hyperspectral imaging.Commercial substrates exhibit several disadvantages whichsignificantly influence the image quality, the possibility forquantitative imaging as well as the chemical assignment.Sputtered highly purified aluminium overcomes several ofthese main disadvantages. A major requirement to processan optimal substrate is the optimization of the conditions ofthe sputtering process due to the basic requirements suchas limitation of recrystallized aluminium grains, the requiredthickness of the aluminium layer and the thermal stability ofthe base substrate. However, high-rate sputtered highly pu-rified aluminium gains access to background-free chemicalimaging up to multisensor hyperspectral imaging with lateral



resolutions in the submicron range. Future work will explorethe new substrate for other multisensor imaging approacheslike, e.g. FTIR and TOF-SIMS imaging among others.

Acknowledgements

The authors would like to thank for funding the Hochschulju-bilaumsstiftung of the City of Vienna within the project H-297306/2014, the Austrian Science Fund(FWF) within theproject TRP265-N20 and the Austrian Research PromotionAgency(FFG) and the COMET program within the imPACtsproject (FFG 843546).

References

Antonio, K.A. & Schultz, Z.D. (2014) Advances in biomedical Ramanmicroscopy. Anal. Chem. 86(1), 30–46.

Bailo, E. & Deckert, V. (2008) Tip-enhanced Raman scattering. Chem. Soc.Rev. 37(5), 921–930.

Batonneau, Y., Sobanska, S., Laureyns, J. & Bremard, C. (2006). Confocalmicroprobe Raman imaging of urban tropospheric aerosol particles.Environ. Sci. Technol. 40(4), 1300–1306.

Bhargava, R. (2012) Infrared spectroscopic imaging: the next generation.Appl. Spectrosc. 66(10), 1091–1120.

Burke, E.A.J. (2001) Raman microspectrometry of fluid inclusions. 55(1–4), 139–158.

Centrone, A. (2015) Infrared imaging and spectroscopy beyond thediffraction limit. Annu. Rev. Anal. Chem. (Palo Alto Calif.) 8(1), 101–126.

Conny, J.M. (2013) Internal composition of atmospheric dust particlesfrom focused ion-beam scanning electron microscopy. Environ. Sci.Technol. 47(15), 8575–8581.

Font Palma, C., Evans, G.J. & Sodhi, R.N.S. (2007) Imaging of aerosolsusing time of flight secondary ion mass spectrometry. Appl. Surf. Sci.253(14), 5951–5956.

Jung, H.-J., Malek, M.A., Ryu, J., Kim, B., Song, Y.-C., Kim, H. & Ro, C.-U. (2010) Speciation of individual mineral particles of micrometer sizeby the combined use of attenuated total reflectance-Fourier transform-infrared imaging and quantitative energy-dispersive electron probe X-ray microanalysis techniques. Anal. Chem. 82(14), 6193–6202.

Kosarova, V., Hradil, D., Hradilova, J., Cermakova, Z., Nemec, I. &Schreiner, M. (2016) The efficiency of micro-Raman spectroscopy in

the analysis of complicated mixtures in modern paints: Munch’s andKupka’s paintings under study. Spectrochim. Acta A Mol. Biomol. Spec-trosc. 156, 36–46.

Krejci, R., Strom, J., de Reus, M. & Sahle, W. (2005) Single particle analysisof the accumulation mode aerosol over the northeast Amazonian trop-ical rain forest, Surinam, South America. Atmos. Chem. Phys. 5(12),3331–3344.

Lanni, E.J., Masyuko, R.N., Driscoll, C.M., Dunham, S.J.B., Shrout, J.D.,Bohn, P.W. & Sweedler, J.V. (2014) Correlated imaging with C60-SIMSand confocal Raman microscopy: visualization of cell-scale molecu-lar distributions in bacterial biofilms. Anal. Chem. 86(21), 10885–10891.

Laskin, A., Cowin, J.P. & Iedema, M.J. (2006) Analysis of individual envi-ronmental particles using modern methods of electron microscopy andX-ray microanalysis. J. Electron Spectrosc. Relat. Phenomena 150(2–3),260–274.

Lohninger, H. & Ofner, J. (2014) Multisensor hyperspectral imaging as aversatile tool for image-based chemical structure determination. Spec-trosc. Eur. 26(5), 6–10.

Nelson, M.P., Zugates, C.T., Treado, P.J., Casuccio, G.S., Exline, D.L. &Schlaegle, S.F. (2001) Combining Raman chemical imaging and scan-ning electron microscopy to characterize ambient fine particulate mat-ter. Aerosol Sci. Technol. 34(1), 108–117.

Ofner, J., Kamilli, K.A., Eitenberger, E., Friedbacher, G., Lendl, B., Held, A.& Lohninger, H. (2015) Chemometric analysis of multisensor hyper-spectral images of precipitated atmospheric particulate matter. Anal.Chem. 87(18), 9413–9420.

Ramoji, A., Galler, K., Glaser, U., Henkel, T., Mayer, G., Dellith, J. &Neugebauer, U. (2016) Characterization of different substrates forRaman spectroscopic imaging of eukaryotic cells. J. Raman Spectrosc.47(7), 773–786.

Ryu, J. & Ro, C. (2009) Attenuated total reflectance FT-IR imagingand quantitative energy dispersive-electron probe X-ray microanalysistechniques for single particle analysis of atmospheric aerosol particles.Anal. Chem. 81(16), 6695–6707.

Sobanska, S., Falgayrac, G., Rimetz-Planchon, J., Perdrix, E., Bremard,C. & Barbillat, J. (2014) Resolving the internal structure of individ-ual atmospheric aerosol particle by the combination of Atomic ForceMicroscopy, ESEM-EDX, Raman and ToF-SIMS imaging. Microchem. J.114, 89–98.

De Wolf, I. (1996) Micro-Raman spectroscopy to study local mechanicalstress in silicon integrated circuits. Semicond. Sci. Technol. 11(2), 139–154.


Documents

CGA PDF Banner - static.ifp.tuwien.ac.at