Collaboratory for Advanced Computing and Simulations, University of Southern California, Los Angeles, California90089-0242, United States of America.
Department of Physics, Kumamoto University, Kumamoto860-8555, Japan.
J Phys Chem Lett. 2022 Dec 8;13(48):11335-11345. doi: 10.1021/acs.jpclett.2c03029. Epub 2022 Dec 1.
Mechanical controllability of recently discovered topological defects (., skyrmions) in ferroelectric materials is of interest for the development of ultralow-power mechano-electronics that are protected against thermal noise. However, fundamental understanding is hindered by the "multiscale quantum challenge" to describe topological switching encompassing large spatiotemporal scales with quantum mechanical accuracy. Here, we overcome this challenge by developing a machine-learning-based multiscale simulation framework─a hybrid neural network quantum molecular dynamics (NNQMD) and molecular mechanics (MM) method. For nanostructures composed of SrTiO and PbTiO, we find how the symmetry of mechanical loading essentially controls polar topological switching. We find under uniaxial compression a squishing-to-annihilation pathway versus formation of a topological composite named skyrmionium under isotropic compression. The distinct pathways are explained in terms of the underlying materials' elasticity and symmetry, as well as the Landau-Lifshitz-Kittel scaling law. Such rational control of ferroelectric topologies will likely facilitate exploration of the rich ferroelectric "topotronics" design space.
最近发现的铁电材料中拓扑缺陷（例如，斯格明子）的机械可控性引起了人们的兴趣，因为它有望开发出超低功耗的机械电子设备，而且这些设备能够免受热噪声的影响。然而，由于需要用量子力学精度来描述涵盖大时空尺度的拓扑转变，因此存在“多尺度量子挑战”，这阻碍了对其的基本理解。在这里，我们通过开发基于机器学习的多尺度模拟框架——混合神经网络量子分子动力学（NNQMD）和分子力学（MM）方法来克服这一挑战。对于由 SrTiO 和 PbTiO 组成的纳米结构，我们发现机械加载的对称性如何从根本上控制着极性拓扑转变。我们发现，在单轴压缩下，会沿着压扁-湮灭的路径进行转变，而在各向同性压缩下，则会形成一种名为 skyrmionium 的拓扑复合材料。通过考虑材料的弹性和对称性以及 Landau-Lifshitz-Kittel 标度律，可以解释这些不同的转变途径。这种对铁电拓扑结构的合理控制，可能会促进对丰富的铁电“拓扑电子学”设计空间的探索。
