Reinforcement Learning in Crystal Structure Prediction

Zamaraeva, Elena ORCID: 0000-0002-7948-2641, Collins, Christopher M ORCID: 0000-0002-0101-4426, Antypov, Dmytro ORCID: 0000-0003-1893-7785, Gusev, Vladimir V ORCID: 0000-0002-2815-607X, Savani, Rahul ORCID: 0000-0003-1262-7831, Dyer, Matthew Stephen ORCID: 0000-0002-4923-3003, Darling, George ORCID: 0000-0001-9329-9993, Potapov, Igor, Rosseinsky, Matthew J ORCID: 0000-0002-1910-2483 and Spirakis, Paul G ORCID: 0000-0001-5396-3749 (2023) Reinforcement Learning in Crystal Structure Prediction Digital Discovery, 2 (6). pp. 1831-1840. ISSN 2635-098X, 2635-098X

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Abstract

Crystal Structure Prediction (CSP) is a fundamental computational problem in materials science. Basin-hopping is a prominent CSP method that combines global Monte Carlo sampling to search over candidate trial structures...

Item Type:	Article
Uncontrolled Keywords:	46 Information and Computing Sciences, 3403 Macromolecular and Materials Chemistry, 34 Chemical Sciences, 4611 Machine Learning
Divisions:	Faculty of Science & Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User:	Symplectic Admin
Date Deposited:	02 Oct 2023 08:17
Last Modified:	23 May 2026 07:54
DOI:	10.1039/d3dd00063j
Open Access URL:	https://pubs.rsc.org/en/content/articlepdf/2023/dd...
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3173229
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