Reinforcement Learning in Crystal Structure Prediction

Zamaraeva, Elena, Collins, Christopher M ORCID: 0000-0002-0101-4426, Antypov, Dmytro ORCID: 0000-0003-1893-7785, Gusev, Vladimir V, 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.

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Official URL: http://dx.doi.org/10.1039/d3dd00063j

Abstract

<jats:p>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...</jats:p>

Item Type:	Article
Uncontrolled Keywords:	Rare Diseases, Orphan Drug
Divisions:	Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User:	Symplectic Admin
Date Deposited:	02 Oct 2023 08:17
Last Modified:	25 Apr 2024 17:38
DOI:	10.1039/d3dd00063j
Open Access URL:	https://pubs.rsc.org/en/content/articlepdf/2023/dd...
Related URLs:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3173229