Hostname: page-component-8448b6f56d-qsmjn Total loading time: 0 Render date: 2024-04-23T10:35:45.959Z Has data issue: false hasContentIssue false

Toward 10 meV Electron Energy-Loss Spectroscopy Resolution for Plasmonics

Published online by Cambridge University Press:  01 April 2014

Edson P. Bellido
Affiliation:
Department of Materials Science and Engineering, McMaster University, 1280 Main Street W. Hamilton ON, Canada L8S 4L7
David Rossouw
Affiliation:
Department of Materials Science and Engineering, McMaster University, 1280 Main Street W. Hamilton ON, Canada L8S 4L7
Gianluigi A. Botton*
Affiliation:
Department of Materials Science and Engineering, McMaster University, 1280 Main Street W. Hamilton ON, Canada L8S 4L7
*
*Corresponding author.gbotton@mcmaster.ca
Get access

Abstract

Energy resolution is one of the most important parameters in electron energy-loss spectroscopy. This is especially true for measurement of surface plasmon resonances, where high-energy resolution is crucial for resolving individual resonance peaks, in particular close to the zero-loss peak. In this work, we improve the energy resolution of electron energy-loss spectra of surface plasmon resonances, acquired with a monochromated beam in a scanning transmission electron microscope, by the use of the Richardson–Lucy deconvolution algorithm. We test the performance of the algorithm in a simulated spectrum and then apply it to experimental energy-loss spectra of a lithographically patterned silver nanorod. By reduction of the point spread function of the spectrum, we are able to identify low-energy surface plasmon peaks in spectra, more localized features, and higher contrast in surface plasmon energy-filtered maps. Thanks to the combination of a monochromated beam and the Richardson–Lucy algorithm, we improve the effective resolution down to 30 meV, and evidence of success up to 10 meV resolution for losses below 1 eV. We also propose, implement, and test two methods to limit the number of iterations in the algorithm. The first method is based on noise measurement and analysis, while in the second we monitor the change of slope in the deconvolved spectrum.

Type
EDGE Special Issue
Copyright
© Microscopy Society of America 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aguiar, J.A., Reed, B.W., Ramasse, Q.M., Erni, R. & Browning, N.D. (2013). Quantifying the low-energy limit and spectral resolution in valence electron energy loss spectroscopy. Ultramicroscopy 124, 130138.CrossRefGoogle ScholarPubMed
Batson, P.E., Dellby, N. & Krivanek, O.L. (2002). Sub-Ångstrom resolution using aberration corrected electron optics. Nature 418(6898), 617620.CrossRefGoogle ScholarPubMed
Bosman, M., Ye, E., Tan, S.F., Nijhuis, C.A., Yang, J.K.W., Marty, R., Mlayah, A., Arbouet, A., Girards, C. & Han, M.Y. (2013). Surface plasmon damping quantified with an electron nanoprobe. Sci Rep 3, 1312.CrossRefGoogle ScholarPubMed
Duan, H., Fernández-Domínguez, A.I., Bosman, M., Maier, S.A. & Yang, J.K.W. (2012). Nanoplasmonics: Classical down to the nanometer scale. Nano Lett 12(3), 16831689.CrossRefGoogle Scholar
Eccles, J.W.L., Bangert, U., Bromfield, M., Christian, P., Harvey, A.J. & Thomas, P. (2010). UV-vis plasmon studies of metal nanoparticles. J Phys Conf Ser 241, 012090.CrossRefGoogle Scholar
Egerton, R.F. (2003). New techniques in electron energy-loss spectroscopy and energy-filtered imaging. Micron 34(3–5), 127139.CrossRefGoogle ScholarPubMed
Egerton, R.F. (2007). Limits to the spatial, energy and momentum resolution of electron energy-loss spectroscopy. Ultramicroscopy 107(8), 575586.CrossRefGoogle Scholar
Egerton, R.F., Qian, H. & Malac, M. (2006). Improving the energy resolution of X-ray and electron energy-loss spectra. Micron 37(4), 310315.CrossRefGoogle ScholarPubMed
García de Abajo, F.J. (2010). Optical excitations in electron microscopy. Rev Mod Phys 82(1), 209275.CrossRefGoogle Scholar
Gloter, A., Douiri, A., Tencé, M. & Colliex, C. (2003). Improving energy resolution of EELS spectra: An alternative to the monochromator solution. Ultramicroscopy 96(3–4), 385400.CrossRefGoogle Scholar
Hohenester, U. & Trügler, A. (2012). MNPBEM a Matlab toolbox for the simulation of plasmonic nanoparticles. Comput Physics Commun 183(2), 370381.CrossRefGoogle Scholar
Ishizuka, K., Kimoto, K. & Bando, Y. (2003). Improving energy resolution of EELS spectra by deconvolution using maximum-entropy and Richardson-Lucy algorithms. Microsc Microanal 2(9), 832833.CrossRefGoogle Scholar
Kimoto, K., Ishizuka, K., Mizoguchi, T., Tanaka, I. & Matsui, Y. (2003). The study of Al-L 23 ELNES with resolution-enhancement software and first-principles calculation. J Electron Microsc 52(3), 299303.CrossRefGoogle Scholar
Koh, A.L., McComb, D.W., Maier, S.A., Low, H.Y. & Yang, J.K.W. (2010). Sub-10 nm patterning of gold nanostructures on silicon-nitride membranes for plasmon mapping with electron energy-loss spectroscopy. J Vacuum Sci Technol 28(6), C6O45C6O49.CrossRefGoogle Scholar
Krivanek, L. & Kundmann, M.K. (1995). Spatial resolution in EFTEM elemental maps. J Microsc 180, 277287.CrossRefGoogle Scholar
Krivanek, O., Dellby, N. & Lupini, A.R. (1999). Towards sub-Å electron beams. Ultramicroscopy 78(1–4), 111.CrossRefGoogle Scholar
Krivanek, O.L., Lovejoy, T.C., Dellby, N. & Carpenter, R.W. (2013). Monochromated STEM with a 30 meV-wide, atom-sized electron probe. Microscopy 62(1), 321.CrossRefGoogle ScholarPubMed
Kuzuo, R. & Tanaka, M. (1993). Resolution enhancement of electron energy-loss spectra using the maximum entropy method. J Electron Microsc 243, 240243.Google Scholar
Lazar, S., Botton, G.A. & Zandbergen, H.W. (2006). Enhancement of resolution in core-loss and low-loss spectroscopy in a monochromated microscope. Ultramicroscopy 106(11–12), 10911103.CrossRefGoogle Scholar
Lucy, L.H. (1974). An iterative technique for the rectification of observed distributions. Astronomical J 79(6), 745754.CrossRefGoogle Scholar
Maier, S.A., Brongersma, M.L. & Atwater, H.A. (2001). Electromagnetic energy transport along arrays of closely spaced metal rods as an analogue to plasmonic devices. Appl Phys Lett 78(1), 16.CrossRefGoogle Scholar
Nelayah, J., Kociak, M., Stéphan, O., García de Abajo, F.J., Tencé, M., Henrard, L., Taverna, D., Pastoriza-Santos, I., Liz-Marzán, L.M. & Colliex, C. (2007). Mapping surface plasmons on a single metallic nanoparticle. Nat Phys 3(5), 348353.CrossRefGoogle Scholar
Overwijk, M. & Reefman, D. (2000). Maximum-entropy deconvolution applied to electron energy-loss spectroscopy. Micron 31(4), 325331.CrossRefGoogle Scholar
Palik, E. (1985). Handbook of Optical Constants of Solids . Academic Press, Inc., New York.Google Scholar
Prasad, S. (2002). Statistical-information-based performance criteria for Richardson-Lucy image deblurring. J Opt Soc Am A Opt Image Sci Vis 19(7), 12861296.CrossRefGoogle ScholarPubMed
Richarson, W.H. (1972). Bayesian-based iterative method of image restoration. J Opt Soc Am 62(1), 5559.CrossRefGoogle Scholar
Rossouw, D. & Botton, G.A. (2013). Plasmonic response of bent silver nanowires for nanophotonic subwavelength waveguiding. Phys Rev Lett 110(6), 066801.CrossRefGoogle ScholarPubMed
Shepp, L.A. & Vardi, Y. (1982). Maximum likelihood reconstruction for emission tomography. IEEE Trans Med Imaging 1(2), 113122.CrossRefGoogle ScholarPubMed
Snyder, D.L., Hammoud, A.M. & White, R.L. (1993). Image recovery from data acquired with a charge-coupled-device camera. J Opt Soc Am 10(5), 10141023.CrossRefGoogle ScholarPubMed
van Kempen, G.M.P., van Vliet, L.J., Verveer, P.J. & van der Voort, H.T.M. (1997). A quantitative comparison of image restoration methods for confocal microscopy. J Microsc 185, 354365.CrossRefGoogle Scholar
Wang, F., Egerton, R. & Malac, M. (2009). Fourier-ratio deconvolution techniques for electron energy-loss spectroscopy (EELS). Ultramicroscopy 109(10), 12451249.CrossRefGoogle ScholarPubMed
Zuo, J.M. (2000). Electron detection characteristics of a slow-scan CCD camera, imaging plates and film, and electron image restoration. Microsc Res Tech 49(3), 245268.3.0.CO;2-O>CrossRefGoogle ScholarPubMed
Supplementary material: PDF

Bellido Supplementary Material

Supplementary Material

Download Bellido Supplementary Material(PDF)
PDF 9.6 MB