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Combining phonon accuracy with high transferability in Gaussian approximation potential models
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George, Janine, Hautier, Geoffroy, Bartók, Albert P., Csányi, Gábor and Deringer, Volker L. (2020) Combining phonon accuracy with high transferability in Gaussian approximation potential models. The Journal of Chemical Physics, 153 (4). 044104. doi:10.1063/5.0013826 ISSN 0021-9606.
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WRAP-phonon-accuracy-high-transferability-Gaussian-approximation-potential-Bartok-2020.pdf - Accepted Version - Requires a PDF viewer. Download (2753Kb) | Preview |
Official URL: http://dx.doi.org/10.1063/5.0013826
Abstract
Machine learning driven interatomic potentials, including Gaussian approximation potential (GAP) models, are emerging tools for atomistic simulations. Here, we address the methodological question of how one can fit GAP models that accurately predict vibrational properties in specific regions of configuration space while retaining flexibility and transferability to others. We use an adaptive regularization of the GAP fit that scales with the absolute force magnitude on any given atom, thereby exploring the Bayesian interpretation of GAP regularization as an "expected error" and its impact on the prediction of physical properties for a material of interest. The approach enables excellent predictions of phonon modes (to within 0.1 THz-0.2 THz) for structurally diverse silicon allotropes, and it can be coupled with existing fitting databases for high transferability across different regions of configuration space, which we demonstrate for liquid and amorphous silicon. These findings and workflows are expected to be useful for GAP-driven materials modeling more generally.
Item Type: | Journal Article | ||||||||||||||||||
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Subjects: | Q Science > QA Mathematics Q Science > QC Physics Q Science > QD Chemistry T Technology > TA Engineering (General). Civil engineering (General) |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering Faculty of Science, Engineering and Medicine > Science > Physics |
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SWORD Depositor: | Library Publications Router | ||||||||||||||||||
Library of Congress Subject Headings (LCSH): | Gaussian processes, Phonons, Atomic structure, Vibrational spectra, Configuration space, Materials -- Mathematical models, Materials science -- Computer simulation | ||||||||||||||||||
Journal or Publication Title: | The Journal of Chemical Physics | ||||||||||||||||||
Publisher: | American Institute of Physics | ||||||||||||||||||
ISSN: | 0021-9606 | ||||||||||||||||||
Official Date: | 2020 | ||||||||||||||||||
Dates: |
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Volume: | 153 | ||||||||||||||||||
Number: | 4 | ||||||||||||||||||
Article Number: | 044104 | ||||||||||||||||||
DOI: | 10.1063/5.0013826 | ||||||||||||||||||
Status: | Peer Reviewed | ||||||||||||||||||
Publication Status: | Published | ||||||||||||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||||||||||||
Date of first compliant deposit: | 2 October 2020 | ||||||||||||||||||
Date of first compliant Open Access: | 2 October 2020 | ||||||||||||||||||
RIOXX Funder/Project Grant: |
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