铁电性
领域(数学分析)
物理
材料科学
数学
数学分析
量子力学
电介质
作者
Ri He,Hua Wang,Fucai Liu,Shi Liu,Houfang Liu,Zhicheng Zhong
出处
期刊:Physical review
[American Physical Society]
日期:2023-07-19
卷期号:108 (2)
被引量:3
标识
DOI:10.1103/physrevb.108.024305
摘要
The switching dynamics of ferroelectric materials is a crucial intrinsic property which directly affects the operation and performance of ferroelectric devices. In conventional ferroelectric materials, the typical ferroelectric switching mechanism is governed by a universal process of domain wall motion. However, recent experiments indicate that Van der Waals ferroelectric CuInP2S6 possesses anomalous polarization switching dynamics under an electric field. It is important to understand the switching dynamics, but it remains theoretically unexplored in CuInP2S6 due to the lack of description of its order-disorder phase transition characteristics by density functional theory. Here, we employ a machine-learning potential trained from the first principles density functional theory dataset to conduct the large-scale atomistic simulations of temperature-driven order-disorder ferroelectric phase transition in CuInP2S6. Most importantly, it is found that the electric field-driven polarization switching in CuInP2S6 is mediated by single Cu dipole flip, rather than conventional domain wall motion mechanism. This intrinsic unconventional switching behavior can be attributed to the competition between the energy barrier of domain wall motion and single dipole flip.
科研通智能强力驱动
Strongly Powered by AbleSci AI