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Machine-Learning Aided Evolution Studies of Nano-composite Electrodes and Nano-particle Catalysts for Fuel Cell Applications

Published online by Cambridge University Press:  23 September 2015

David Rossouw
Affiliation:
McMaster University, Department of Materials Science and Engineering, Hamilton, ON, Canada.
Lidia E. Chinchilla
Affiliation:
McMaster University, Department of Materials Science and Engineering, Hamilton, ON, Canada.
Sagar Prabhudev
Affiliation:
McMaster University, Department of Materials Science and Engineering, Hamilton, ON, Canada.
Tyler Trefz
Affiliation:
Automobile Fuel Cell Cooperation, 9000 Glenlyon Parkway, Burnaby, BC V5J 5J8Canada
Natalia Kremliakova
Affiliation:
Automobile Fuel Cell Cooperation, 9000 Glenlyon Parkway, Burnaby, BC V5J 5J8Canada
Gianluigi A. Botton
Affiliation:
McMaster University, Department of Materials Science and Engineering, Hamilton, ON, Canada.

Abstract

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Type
Abstract
Copyright
Copyright © Microscopy Society of America 2015 

References

[2] de la Pena, F., et al, Ultramicroscopy 111 (2011). p 169.Google Scholar
[3] Prabhudev, S., et al, ACS Nano 7 (2013). p 6103.Google Scholar
[4] G-z, Zhu, et al, J. Phys. Chem. C. 118 (2014). p 22111.Google Scholar
[5] Petkov, V., et al, Nano Lett. 12 (2012). p 4289.Google Scholar
[6] D.R. acknowledges support from the Royal Society's Newton International Fellowship scheme and F. de la Pena & P. Burdet for many useful discussions on the ICA technique. S. P acknowledges support from Cory Chiang in the synthesis of Au-Pt nanoparticles. GAB is grateful for funding from NSERC under the CaRPE-FC network and to AFCC for partially supporting this work.Google Scholar