Hostname: page-component-7479d7b7d-pfhbr Total loading time: 0 Render date: 2024-07-12T01:23:41.882Z Has data issue: false hasContentIssue false
  • English
  • Français

Microanalysis of Porous Materials

Published online by Cambridge University Press:  01 December 2004

Loïc Sorbier ,
Elisabeth Rosenberg  and
Claude Merlet
Loïc Sorbier
Affiliation:
Direction Physique et Analyse, Institut Français du Pétrole, BP3, 69390 Vernaison, France
Elisabeth Rosenberg
Affiliation:
Direction Ingénierie de Réservoir, Institut Français du Pétrole, 1 et 4 avenue de Bois Préau, 92852 Rueil-Malmaison Cedex, France
Claude Merlet
Affiliation:
ISTEEM, Centre National de la Recherche Scientifique, Université de Montpellier II, place E. Bataillon, 34095 Montpellier Cedex 5, France
Get access

Abstract

A signal loss is generally reported in electron probe microanalysis (EPMA) of porous, highly divided materials like heterogeneous catalysts. The hypothesis generally proposed to explain this signal loss refers to porosity, roughness, energy losses at interfaces, or charging effects. In this work we investigate by Monte Carlo simulation all these physical effects and compare the simulated results with measurements obtained on a mesoporous alumina. A program using the PENELOPE package and taking into account these four physical phenomena has been written. Simulation results show clearly that neither porosity nor roughness, nor specific energy losses at interfaces, nor charging effects are responsible for the observed signal loss. Measurements performed with analysis of carbon and oxygen lead to a correct total of concentration. The signal loss is thus explained by a composition effect due to a carbon contamination brought by the sample preparation and to a lesser extent by a stoichiometry of the porous alumina different from a massive alumina. For this kind of high specific surface porous sample, a little surface contamination layer becomes an important volume contamination that can produce large quantification errors if the contaminant is not analyzed.

Keywords

microanalysisquantitativecatalystMonte Carloroughporousinsulating
Type
Research Article
Information
Microscopy and Microanalysis , Volume 10 , Issue 6 , December 2004 , pp. 745 - 752
Copyright
© 2004 Microscopy Society of America

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

REFERENCES

Abo-Namous, S.A. (1989). On the peak-to-background ratio in microprobe analysis of porous materials. In Microbeam Analysis, Russell, P. (Ed.), pp. 239–241. San Francisco: San Francisco Press.
Acosta, E., Llovet, X., Coleoni, E., Riveros, J.A., & Salvat, F. (1998). Monte Carlo simulation of X-ray emission by kilovolt electron bombardment. J Appl Phys 83, 6038–6048.Google Scholar
Bielajew, A. (1988). Electron transport in E and B fields. In Monte Carlo Transport of Electrons and Photons, Jenkins, T.M., Nelson, R. & Rindi, A. (Eds.), pp. 421–434. New York, London: Plenum Press.
Busch, P. & Förster, U. (1997). Influence of the topography of zinc coated sheet on the results of electron probe microanalysis. Fresenius J Anal Chem 358, 155–159.Google Scholar
Cazaux, J. (1996). Electron probe microanalysis of insulating materials: Quantification problems and some possible solutions. X-Ray Spectrom 25, 265–280.Google Scholar
Egerton, R. (1986). Electron Energy Loss Spectroscopy in the Electron Microscope. New York: Plenum Press.
Gauvin, R. & Lifshin, E. (2000). Simulation of X-ray emission from rough surfaces. Mikrochimica Acta 132, 201–204.Google Scholar
Ichinokawa, T., Kobayashi, H., & Nakajima, M. (1969). Density effect of X-ray emission from porous specimens in quantitative electron probe microanalysis. Jpn J Appl Phys 8, 1563–1568.Google Scholar
Jbara, O., Fakhfakh, S., Belhaj, M., Cazaux, J., Rau, E.I., Filipov, M., & Andrianov, M.V. (2002). Nucl Instrum Methods Phys Res B 194, 302–310.
Jbara, O., Portron, B., Mouze, D., & Cazaux, J. (1997). Electron probe microanalysis of insulating oxides: Monte Carlo simulations. X-Ray Spectrom 26, 291–302.Google Scholar
Kotera, M. & Suga, H. (1988). A simulation of keV electron scatterings in a charged-up specimen. J Appl Phys 63, 261–268.Google Scholar
Lakis, R., Lyman, C., & Goldstein, J. (1992). Electron-probe microanalysis of porous materials. In Proceedings of the 50th Annual Meeting of the Electron Microscopy Society of America, Bailey, G., Bentley, J. & Small, J. (Eds.), pp. 1660–1661. San Francisco: San Francisco Press.
Odof, S. (2000). Microanalyse X des isolants: Simulations de Monte-Carlo. Doctoral Thesis, Université Reims Champagne-Ardennes.
Salvat, F., Fernández-Varea, J.M., Baró, J., & Sempau, J. (1996). PENELOPE, an algorithm and computer code for Monte Carlo simulation of electron–photon showers. Informes Técnicos Ciemat 799, 1–135.Google Scholar
Sohlberg, K., Pennycook, S., & Pantelides, S. (1999). Hydrogen and the structure of the transition aluminas. J Am Chem Soc 121, 7493–7499.Google Scholar
Sorbier, L. (2001). Apport de la simulation dans l'optimisation de l'analyse quantitative par microsonde électronique de catalyseurs hétérogènes. Doctoral Thesis, Université Montpellier II.
Sorbier, L., Rosenberg, E., & Merlet, C. (2001). Monte Carlo simulations on rough and porous alumina. In Advanced Monte Carlo for Radiation Physics, Particle Transport Simulation and Applications, Kling, A., Barão, F., Nakagawa, M., Távora, L. & Vaz, P. (Eds.), pp. 389–394. Berlin, Heidelberg: Springer-Verlag.
Sorbier, L., Rosenberg, E., Merlet, C., & Llovet, X. (2000). EPMA of porous media: A Monte Carlo approach. Mikrochimica Acta 132, 189–199.Google Scholar
Tretyakov, V.V., Romanov, S.G., Fokin, A.V., & Alperovitch, V.I. (1998). EPMA of the composition of opal-based nanostructured materials. Mikrochimica Acta, Suppl. 15, 211–217.Google Scholar