Bulletin of the American Physical Society
2024 APS March Meeting
Monday–Friday, March 4–8, 2024; Minneapolis & Virtual
Session K60: Machine Learning of Molecules and Materials: Materials I
3:00 PM–6:00 PM,
Tuesday, March 5, 2024
Room: 207AB
Sponsoring
Unit:
DCOMP
Chair: Xuecheng Shao, Rutgers University - Newark
Abstract: K60.00011 : Anharmonicity in cubic boron arsenide: a machine-learning based force-field study
5:48 PM–6:00 PM
Presenter:
Martin Callsen
(Institute of Atomic and Molecular Sciences, Academia Sinica)
Authors:
Martin Callsen
(Institute of Atomic and Molecular Sciences, Academia Sinica)
Mei-Yin Chou
(Institute of Atomic and Molecular Sciences, Academia Sinica)
In this talk we are going to present our machine-learning based force-field calculations for the dynamics and thermal transport of c-BAs. The forcefield is based on the well-known lattice dynamics expansion of the total energy. With this particular choice we can obtain the higher-order force-constant tensors directly and gain further insight into the role of anharmonicity in c-BAs.
[1] L. Lindsay et al., Phys. Rev. Lett. 111, 025901 (2013)
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