Exploring the absolute yield curve of secondary electrons using machine learning methods-Reference-Cited by-同舟云学术

Exploring the absolute yield curve of secondary electrons using machine learning methods

Published:2023 Issue:26 Volume:25 Page:17238-17256
ISSN:1463-9076
Container-title:Physical Chemistry Chemical Physics
language:en
Short-container-title:Phys. Chem. Chem. Phys.

Author:

Mehnaz ¹,Da Bo²,Ding Z. J.¹³^ORCID

Affiliation:

1. Department of Physics, University of Science and Technology of China, Hefei, Anhui 230026, People's Republic of China

2. Center for Basic Research on Materials, National Institute for Materials Science, Tsukuba, Ibaraki 305-0044, Japan

3. Hefei National Research Center for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei, Anhui 230026, People's Republic of China

Abstract

Knowledge of absolute secondary electron yield (δ) is important for various applications of electron emission materials.

Publisher

Royal Society of Chemistry (RSC)

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://pubs.rsc.org/en/content/articlepdf/2023/CP/D3CP01443F

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