Combining Machine Learning Potential and Structure Prediction for Accelerated Materials Design and Discovery-Reference-Cited by-同舟云学术

Combining Machine Learning Potential and Structure Prediction for Accelerated Materials Design and Discovery

Published:2020-09-21 Issue:20 Volume:11 Page:8710-8720
ISSN:1948-7185
Container-title:The Journal of Physical Chemistry Letters
language:en
Short-container-title:J. Phys. Chem. Lett.

Author:

Tong Qunchao¹²,Gao Pengyue¹^ORCID,Liu Hanyu¹³⁴^ORCID,Xie Yu¹³^ORCID,Lv Jian¹²^ORCID,Wang Yanchao¹²^ORCID,Zhao Jijun⁵^ORCID

Affiliation:

1. International Center for Computational Method & Software, College of Physics, Jilin University, Changchun 130012, China

2. State Key Laboratory of Superhard Materials, College of Physics, Jilin University, Changchun 130012, China

3. Key Laboratory of Physics and Technology for Advanced Batteries (Ministry of Education), Jilin University, Changchun 130012, China

4. International Center of Future Science, Jilin University, Changchun 130012, China

5. Key Laboratory of Materials Modification by Laser, Ion and Electron Beams, (Dalian University of Technology), Ministry of Education, Dalian 116024, China

Funder

Ministry of Education of the People's Republic of China

Ministry of Science and Technology of the People's Republic of China

China Postdoctoral Science Foundation

People's Government of Jilin Province

Jilin University

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

General Materials Science,Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpclett.0c02357

Reference114 articles.

1. Perspective: Crystal structure prediction at high pressures

2. Structure prediction drives materials discovery

3. Optimization by Simulated Annealing

4. Global Optimization by Basin-Hopping and the Lowest Energy Structures of Lennard-Jones Clusters Containing up to 110 Atoms

5. Minima hopping: An efficient search method for the global minimum of the potential energy surface of complex molecular systems

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