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Modeling ion-solid interactions for imaging applications

Published online by Cambridge University Press:  09 April 2014

D.C. Joy
Affiliation:
Department of Biochemistry, Cellular and Molecular Biology Department of Materials Science and Engineering, University of Tennessee;djoy@utk.edu
J.R. Michael
Affiliation:
Sandia National Laboratories;jrmicha@sandia.gov
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Abstract

Ion beams are now widely used to thin, shape, or cut materials on the submicrometer scale. This is possible because ions can sputter (i.e., physically remove) material from the target. Ions can also be used to image materials because the incident beam generates ion-induced secondary electrons (iSE). In both cases, the nature of the target material and the choice of the ion employed and its initial energy will determine not only how quickly the beam can thin a specimen, but also the resolution and contrast of the iSE image that is generated. Clearly, there is a need to be able to predict parameters, such as the nature, information content, and spatial resolution of the iSE image. These and other related questions have been investigated using Monte Carlo simulations. We show how the parameters defining quantities, such as depth of penetration and the energy deposited by the incident beam, or the signal yield and resolution of the iSE image, can be predicted using this approach and how these results make it possible to interpret data and optimize operating conditions.

Type
Research Article
Copyright
Copyright © Materials Research Society 2014 

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References

Levi-Setti, R., in Electron Beam Interactions with Solids, Johari, O., Ed. (SEM Inc., Chicago, 1983), p. 1.Google Scholar
Giannuzzi, L.A., Stevie, F.A., Eds. Introduction to Focused Ion Beams: Instrumentation, Theory, Techniques and Practice (Springer, New York, 2005).CrossRefGoogle Scholar
Bethe, H.A., Phys. Rev. 59, 940 (1941).Google Scholar
Joy, D.C., Monte Carlo Modeling for Electron Microscopy (Oxford University Press, New York, 1995).CrossRefGoogle Scholar
Dapor, M., Nucl. Instrum. Methods Phys. Res. B 269, 1668 (2011).CrossRefGoogle Scholar
Lin, Y., Joy, D.C., Surf. Interface Anal. 37, 895 (2005).CrossRefGoogle Scholar
Ramachandra, R., Griffin, B.J., Joy, D.C., Ultramicroscopy 109, 747 (2009).CrossRefGoogle Scholar
National Institute of Science and Technology (NIST), Physical Measurements Laboratory (2012); http://physics.nist.gov/PhysRefData/Star/Text/ASTAR.html.Google Scholar
Seiler, H., in Electron Beam Interactions with Solids, Kaiser, D.F., Niedrig, H., Newbury, D.E., Shimizu, R., Eds. (SEM Inc., Chicago, 1984), p. 33.Google Scholar
Salow, H., Z. Phys. 41, 434 (1940).Google Scholar
Joy, D.C., A database of iSE yields for various ion beams and materials; http://www.engr.utk.edu/∼mse/single_pages/research.html#.Google Scholar
Ishitani, T., Yamanak, T., Inai, K., Ohya, K., Vacuum 84, 1018 (2010).CrossRefGoogle Scholar
Sakai, Y., Yamada, T., Suzuki, T., and Ichinokawa, T., J. Anal. At. Spectrom. 14, 419 (1999).CrossRefGoogle Scholar
Sakai, Y., Yamada, T., Suzuki, T., Ichinokawa, T., Appl. Surf. Sci. 144145, 96 (1999).CrossRefGoogle Scholar
Giannuzzi, L.A., Utlaut, M., Ultramicroscopy 11, 1564 (2011).CrossRefGoogle Scholar
Giannuzzi, L.A., Michael, J.R., Microsc. Microanal. 19, 344 (2013).CrossRefGoogle Scholar
Michael, J.R., Microsc. Microanal. 17, 386 (2011).CrossRefGoogle Scholar