Physics-Guided Machine Learning for the Analysis of Low SNR STEM-EDXS Data
Microscopy and Microanalysis(2022)
Abstract
Journal Article Physics-Guided Machine Learning for the Analysis of Low SNR STEM-EDXS Data Get access Adrien Teurtrie, Adrien Teurtrie Electron Spectrometry and Microscopy Laboratory, Institute of Physics, EPFL, LausanneCurrent address : Unité Matériaux et Transformations, UMET, UMR-CNRS 8207, Université de Lille, France Search for other works by this author on: Oxford Academic Google Scholar Nathanaël Perraudin, Nathanaël Perraudin Swiss Data Science Center, EPFL and ETH Zürich, Lausanne and Zürich Search for other works by this author on: Oxford Academic Google Scholar Thomas Holvoet, Thomas Holvoet Swiss Data Science Center, EPFL and ETH Zürich, Lausanne and ZürichGhent University, Ghent Search for other works by this author on: Oxford Academic Google Scholar Hui Chen, Hui Chen Electron Spectrometry and Microscopy Laboratory, Institute of Physics, EPFL, Lausanne Search for other works by this author on: Oxford Academic Google Scholar Duncan T L Alexander, Duncan T L Alexander Electron Spectrometry and Microscopy Laboratory, Institute of Physics, EPFL, Lausanne Search for other works by this author on: Oxford Academic Google Scholar Guillaume Obozinski, Guillaume Obozinski Swiss Data Science Center, EPFL and ETH Zürich, Lausanne and Zürich Search for other works by this author on: Oxford Academic Google Scholar Cécile Hébert Cécile Hébert Electron Spectrometry and Microscopy Laboratory, Institute of Physics, EPFL, Lausanne Corresponding author: cecile.hebert@epfl.ch Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 28, Issue S1, 1 August 2022, Pages 2978–2979, https://doi.org/10.1017/S1431927622011163 Published: 01 August 2022
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Key words
Materials Discovery,Ambient Pressure Photoelectron Spectroscopy,Scanning Electron Microscopy,Environmental Scanning Electron Microscopy,Surface Science
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