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Multi-Dimensional Machine Learning Aided Analysis of a Nickel-Based Superalloy

Published online by Cambridge University Press:  23 September 2015

David Rossouw
Affiliation:
Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge, CB3 0FS, UK.
Robert Krakow
Affiliation:
Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge, CB3 0FS, UK.
Zineb Saghi
Affiliation:
Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge, CB3 0FS, UK.
Catriona S M Yeoh
Affiliation:
Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge, CB3 0FS, UK.
Pierre Burdet
Affiliation:
Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge, CB3 0FS, UK.
Rowan K Leary
Affiliation:
Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge, CB3 0FS, UK.
Paul A Midgley
Affiliation:
Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge, CB3 0FS, UK.

Abstract

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Type
Abstract
Copyright
Copyright © Microscopy Society of America 2015 

References

References:

[1] Von Harrach, H. S., et al. J. Phys. Conf. Ser. 241 (2010). p. 012015.Google Scholar
[2] de la Pena, F., et al., Ultramicroscopy 111 (2011). p. 169.Google Scholar
[3] Burdet, P., et al., Acta Mater. 61 (2013). p. 3090.Google Scholar
[4] Midgley, P. A & Thomas, J. M., Angew. Chem. Int. Ed. Engl 53 (2014). p. 2.Google Scholar
[6] Viskari, L. & Stiller, K., Ultramicroscopy 111 (2011). p. 652.CrossRefGoogle Scholar
[7] Special thanks to Giorgio Divitini and Lech Staniewicz for preparation of the FIB prepared needle. D.R. acknowledges support from the Royal Society's Newton International Fellowship scheme..Google Scholar