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All Mixed Up: Using Machine Learning to Address Heterogeneity in (Natural) Materials

Published online by Cambridge University Press:  01 August 2018

J. F. Einsle ,
Ben Martineau ,
Iris Buisman ,
Zoja Vukmanovic ,
Duncan Johnstone ,
Alex Eggeman ,
Paul A. Midgley  and
Richard J. Harrison
J. F. Einsle
Affiliation:
Department of Earth Sciences, University of Cambridge, Cambridge, UK Department of Materials Science and Metallurgy, University of Cambridge, Cambridge, UK
Ben Martineau
Affiliation:
Department of Materials Science and Metallurgy, University of Cambridge, Cambridge, UK
Iris Buisman
Affiliation:
Department of Earth Sciences, University of Cambridge, Cambridge, UK
Zoja Vukmanovic
Affiliation:
Department of Earth Sciences, University of Cambridge, Cambridge, UK
Duncan Johnstone
Affiliation:
Department of Materials Science and Metallurgy, University of Cambridge, Cambridge, UK
Alex Eggeman
Affiliation:
School of Materials, University of Manchester, Manchester, UK
Paul A. Midgley
Affiliation:
Department of Materials Science and Metallurgy, University of Cambridge, Cambridge, UK
Richard J. Harrison
Affiliation:
Department of Earth Sciences, University of Cambridge, Cambridge, UK

Abstract

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Type
Abstract
Information
Microscopy and Microanalysis , Volume 24 , Supplement S1: Proceedings of Microscopy & Microanalysis 2018 , August 2018 , pp. 562 - 563
Copyright
© Microscopy Society of America 2018 

References

[1] Saghi, Z., et al, Nano Letters 11 2011) p. 4666.Google Scholar
[2] Eggeman, A. S., Krakow, R. Midgley, P. A. Nature Communications 6 2015) p. 1.Google Scholar
[3] J.F.E., P.A.M. and R.J.H. would like to acknowledge funding under ERC Advanced grant 320750-Nanopaleomagnetism. S.M.C. and P.A.M. would also like to acknowledge funding under ERC Advanced grant 291522-3DIMAGE. S.M.C. acknowledges the Henslow Research Fellowship and Girton College, Cambridge. A.S.E. and B.H.M. acknowledge financial support from the Royal Society.Google Scholar