Ropers, Jakob, Mosca, Marco M, Anosova, Olga, Kurlin, Vitaliy 
ORCID: 0000-0001-5328-5351 and Cooper, Andrew I
(2022)
Fast Predictions of Lattice Energies by Continuous Isometry Invariants of Crystal Structures.
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Abstract
Crystal Structure Prediction (CSP) aims to discover solid crystalline materials by optimizing periodic arrangements of atoms, ions or molecules. CSP takes weeks of supercomputer time because of slow energy minimizations for millions of simulated crystals. The lattice energy is a key physical property, which hints at thermodynamic stability of a crystal but has no simple analytic expression. Past machine learning approaches to predict the lattice energy used slow crystal descriptors depending on manually chosen parameters. The new area of Periodic Geometry offers much faster isometry invariants that are also continuous under perturbations of atoms. Our experiments on simulated crystals confirm that a small distance between the new invariants guarantees a small difference of energies. We compare several kernel methods for invariant-based predictions of energy and achieve the mean absolute error of less than 5 kJ/mole or 0.05 eV/atom on a dataset of 5679 crystals.
| Item Type: | Conference or Workshop Item (Unspecified) |
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| Uncontrolled Keywords: | 7 Affordable and Clean Energy |
| Divisions: | Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Population Health Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 28 Mar 2023 08:27 |
| Last Modified: | 14 Mar 2024 17:32 |
| DOI: | 10.1007/978-3-031-12285-9_11 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3169273 |
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