Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-29T05:20:39.589Z Has data issue: false hasContentIssue false

Evaluation of Sensitivity of Multivariate Statistical Analysis on STEM Spectrum-Imaging Datasets and its Improvement

Published online by Cambridge University Press:  27 August 2014

M. Watanabe
Affiliation:
Dept of Materials Science and Engineering, Lehigh University, Bethlehem. PA 18015
K. Ishizuka
Affiliation:
HREM Research Inc., Higashimatsuyama, Saitama, 355-0055, Japan

Abstract

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Abstract
Copyright
Copyright © Microscopy Society of America 2014 

References

[1] Pennycook, S.J., Nellist, P.D. ed. Scanning Transmission Electron Microscopy: Imaging andAnalysis, Springer, NY, (2011).Google Scholar
[2] Jolliffe, I.T. Principal Component Analysis, 2nd ed., Springer, New York (2002).Google Scholar
[3] Malinowski, E.R. Factor Analysis in Chemistry, 3rd ed., Wiley, New York (2002).Google Scholar
[4] Watanabe, M, et al., Microscopy and Analysis, 23, Issue 7 (2009), 5-7.Google Scholar
[5] Lichtert, S., Verbeeck, J. Ultramicrosc., 125 (2013), 35-42.Google Scholar
[6] Fiori, C.E., et al., NIST/NIH Desk Top Spectrum Analyzer, public domain software available from the National Institute of Standards and Technology Gaithersburg, MD.Google Scholar
[7] The author wishes to acknowledge financial support from the NSF through grants DMR-0804528 and DMR-1040229.Google Scholar