Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-29T06:53:50.587Z Has data issue: false hasContentIssue false
  • English
  • Français

A Machine Learning pipeline to track the dynamics of a population of nanoparticles during in situ Environmental Transmission Electron Microscopy in gases

Published online by Cambridge University Press:  30 July 2021

Khuram Faraz ,
Thomas Grenier ,
Christophe Ducottet  and
Thierry Epicier
Khuram Faraz
Affiliation:
Université de Lyon, Université Jean Monnet, Saint-Etienne, Saint-Etienne, France
Thomas Grenier
Affiliation:
Université de Lyon, Institut National des Sciences Appliquées de Lyon, Lyon, France
Christophe Ducottet
Affiliation:
Université de Lyon, Université Jean Monnet, Saint-Etienne, Saint-Etienne, France
Thierry Epicier
Affiliation:
Centre National de la Recherche Scientifique, Villeurbanne Cedex, France

Abstract

An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
New Frontiers in In-Situ Electron Microscopy in Liquids and Gases (L&G EM FIG Sponsored)
Information
Microscopy and Microanalysis , Volume 27 , Supplement S1 , August 2021 , pp. 2236 - 2237
Check for updates
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

References

Zhou, Y. et al. , Nano Today, 20 (2018) 101-120.CrossRefGoogle Scholar
Hansen, T.W., et al. , Accounts of Chemical Research, 46 8 (2013) 1720-1730.CrossRefGoogle Scholar
Martin, T.E. et al. , ChemCatChem, 7 (2015) 3705-3711.CrossRefGoogle Scholar
Horwath, J.P. et al. , npj Computational Materials 6 (2020) 108.CrossRefGoogle Scholar
Yao, L., et al. , ACS Cent. Sci. 6 (2020) 1421-1430.CrossRefGoogle Scholar
Epicier, T., et al. , Catalysis Today, 334, 15 (2019), 68-78.Google Scholar
Ronneberger, O. et al. , Lect. Notes Comput. Sci. 9351 (2015) 234–241.CrossRefGoogle Scholar
Treacy, M.M.J., Rice, S.B., J. Microsc. 156 (1989) 211–234.CrossRefGoogle Scholar
Xu, Y. et al. , IET Computer Vision 13 4 (2019) 355-368.Google Scholar
Milan, A. et al. , IEEE Trans Pattern Analysis & Machine Intelligence, 38 10 (2016) 2054-2068.CrossRefGoogle Scholar
The authors thank the support of the French National Research Agency (ANR) through the cooperative project ‘3DCLEAN’ n° 15-CE09-0009-01 and of the EUR SLEIGHT https://manutech-sleight.com/). CLYM (www.clym.fr) is acknowledged for the access to the ETEM and IFPEN (Solaize, F) for providing samples.Google Scholar