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arXiv 2305.08321cond-mat.mtrl-sci
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基于第一性原理的CuInP2S6非常规铁电畴翻转动力学

Unconventional ferroelectric domain switching dynamics in CuInP2S6 from first principles

Ri He, Hua Wang, Fucai Liu, Shi Liu, Houfang Liu, Zhicheng Zhong

AI总结:

本文利用第一性原理数据集训练的机器学习势进行大规模原子模拟,发现范德华铁电CuInP2S6的极化翻转由单个Cu偶极子翻转介导而非传统畴壁运动,揭示了其非常规翻转动力学机制。

摘要:

铁电材料的翻转动力学是一项关键的内禀特性,直接影响铁电器件的运行和性能。在传统铁电材料中,典型的铁电翻转机制由普遍的畴壁运动过程主导。然而,最近的实验表明,范德华铁电CuInP2S6在电场下具有反常的极化翻转动力学。理解其翻转动力学很重要,但由于密度泛函理论缺乏对其有序-无序相变特征的描述,CuInP2S6在理论上仍未被探索。在此,我们采用由第一性原理密度泛函理论数据集训练的机器学习势,对CuInP2S6中温度驱动的有序-无序铁电相变进行大规模原子模拟。最重要的是,我们发现CuInP2S6中电场驱动的极化翻转由单个Cu偶极子翻转介导,而非传统的畴壁运动机制。这种内禀的非常规翻转行为可归因于畴壁运动与单个偶极子翻转之间的能垒竞争。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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