Bulletin of the American Physical Society
APS March Meeting 2021
Volume 66, Number 1
Monday–Friday, March 15–19, 2021; Virtual; Time Zone: Central Daylight Time, USA
Session B22: Emerging Trends in MD Simulations and Machine Learning I
11:30 AM–2:30 PM,
Monday, March 15, 2021
Sponsoring
Units:
DCOMP GDS DSOFT DPOLY
Chair: Rajiv Kalia, Univ of Southern California
Abstract: B22.00004 : Neural network molecular dynamics of ferroelectric domain boundary*
12:30 PM–12:42 PM
Live
Presenter:
Anikeya Aditya
(Univ of Southern California)
Authors:
Anikeya Aditya
(Univ of Southern California)
Ken-ichi Nomura
(Univ of Southern California)
Thomas Linker
(Univ of Southern California)
Rajiv K Kalia
(Univ of Southern California)
Aravind Krishnamoorthy
(Univ of Southern California)
Aiichiro Nakano
(Univ of Southern California)
Kohei Shimamura
(Kumamoto University)
Fuyuki Shimojo
(Kumamoto University)
Subodh C Tiwari
(Univ of Southern California)
Priya Vashishta
(Univ of Southern California)
polarization at ambient conditions. Formation of nanometer-size domains with opposite
polarizations separated by domain walls (DWs) essentially control the design and function of
ferroelectric devices. However, the underlying physics is not well understood and ab-initio
molecular dynamics (MD) simulation is computationally too costly to study DW structures.
Neural network MD (NNAIMD) is an emerging approach to study large-scale atomistic systems
with quantum mechanics accuracy. In this study, I will discuss the development of NNAIMD force
field to study PTO crystal, along with simulation results on complex DW dynamics using it.
*This work was supported as part of the Computational Materials Sciences Program funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, under Award Number DE-SC0014607.
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