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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
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

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Type
New Frontiers in In-Situ Electron Microscopy in Liquids and Gases (L&G EM FIG Sponsored)
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

References

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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