面向铁电开关建模的扩展主动学习：对‘金标准’的需求

中文摘要 AI 辅助

为了对纤锌矿结构材料中的铁电开关进行建模，本文考虑了四种经济高效的密度泛函理论（DFT）方法（PBE、PBEsol、r2SCAN和r2SCAN-rVV10），并将其与基于随机相位近似（RPA）的各种从头计算方法进行比较，包括带单激发修正的RPA（RPAR+S）以及二阶Møller-Plesset微扰理论（MP2）。其目的是确定从头计算方法能否作为评估DFT可靠性的“金标准”，从而为诸如机器学习原子间势（MLIP）训练等详尽任务确定最优的DFT方法，这些MLIP用于对任意成分和结构的材料（如Al1-xScxN和Zn1-xMgxO）进行大规模模拟，并以AlN、Al0.5Sc0.5N、ZnO和Zn0.5Mg0.5O作为模型材料。主动学习（AL）的应用现已普遍，其中MLIP模拟的结果被用于增强DFT训练数据集，但未来的扩展主动学习（EAL）方法也将需要系统地对照金标准评估DFT方法。本文发现，从头计算结果的变异性超过了稳健金标准所需的范围，但DFT和从头计算方法似乎一致认为RPAR+S和r2SCAN-rVV10是启动EAL的最优方法选择。研究发现，电子关联能主要由与高电子密度阴离子相关的共价键效应主导，但范德华色散力在铁电建模中过于显著，不容忽视。

英文摘要

For the purpose of modelling ferroelectric switching in wurtzite-structured materials, four cost-effective density-functional theory (DFT) methods (PBE, PBEsol, r2SCAN, and r2SCAN-rVV10) are considered and compared to various ab initio approaches based on the random-phase approximation (RPA), including RPA with singles corrections (RPAR+S), as well as second-order Møller-Plesset perturbation theory (MP2). The purpose is to determine whether an ab initio approach could act as a 'gold standard' for estimating the reliability of DFT, thus determining an optimal DFT method for use in exhaustive tasks such as the training of machine-learning interatomic potentials (MLIP) for large-scale simulations of materials of arbitrary composition and structure such as Al1-xScxN and Zn1-xMgxO, using AlN, Al0.5Sc0.5N, ZnO, and Zn0.5Mg0.5O as model materials. Applications of active learning (AL) are now common, in which results from MLIP simulations are used to enhance the DFT training data set, but future extended active learning (EAL) methods will also need to systematically assess the DFT methodology against a gold standard. Herein, the variability of the ab initio results is found to exceed that required for a robust gold standard, but the DFT and ab initio approaches appear to converge on RPAR+S and r2SCAN-rVV10 as optimal method choices to initiate EAL. The electron correlation energy is found to be dominated by covalent binding effects associated with the high-electron-density anions involved, but the van der Waals dispersion force is seen to be too significant to ignore in ferroelectric modelling.

发表机构

• International Centre for Quantum and Molecular Structures and the School of Physics, Shanghai University（上海大学量子与分子结构国际中心及物理学院）
• University of Technology Sydney（悉尼科技大学）
• The University of Queensland（昆士兰大学）
• Griffith University（格里菲斯大学）
• Materials Genome Institute, International Centre for Quantum and Molecular Structures, Shanghai University（上海大学量子与分子结构国际中心材料基因组研究院）

机构由 AI 辅助整理，请以论文原文为准。

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9 pages, 3 figures, 3 tables