Development of interatomic potential for Al–Tb alloys using a deep neural network learning method-Reference-Cited by-同舟云学术

Development of interatomic potential for Al–Tb alloys using a deep neural network learning method

Published:2020 Issue:33 Volume:22 Page:18467-18479
ISSN:1463-9076
Container-title:Physical Chemistry Chemical Physics
language:en
Short-container-title:Phys. Chem. Chem. Phys.

Author:

Tang L.¹²³⁴⁵^ORCID,Yang Z. J.¹²³⁴⁵,Wen T. Q.⁶⁷⁸⁹,Ho K. M.⁶⁷⁸⁹¹⁰,Kramer M. J.⁶⁷⁸⁹,Wang C. Z.⁶⁷⁸⁹¹⁰^ORCID

Affiliation:

1. Department of Applied Physics

2. College of Science

3. Zhejiang University of Technology

4. Hangzhou

5. China

6. Ames Laboratory-USDOE

7. Iowa State University

8. Ames

9. USA

10. Department of Physics and Astronomy

Abstract

The developed deep neural network (DNN) potential can describe the structural properties of the Al₉₀Tb₁₀ liquid and the formation energies of Al–Tb crystals with the accuracy of ab initio calculations.

Funder

Natural Science Foundation of Zhejiang Province

National Natural Science Foundation of China

U.S. Department of Energy

Publisher

Royal Society of Chemistry (RSC)

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://pubs.rsc.org/en/content/articlepdf/2020/CP/D0CP01689F

Reference45 articles.

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4. Unique metallic glass formability and ultra-high tensile strength in AlNiFeGd alloys

5. Metallic Glasses

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