HfO2中反极性$$\boldsymbol{Pbcn}$$相意想不到的密度泛函依赖性

IF 9.4 1区 材料科学 Q1 CHEMISTRY, PHYSICAL
Di Fan, Tianyuan Zhu, Shi Liu
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引用次数: 0

摘要

HfO2的反极性Pbcn相被认为在铁电铪的相变和极化开关机制中起关键作用。本文采用密度泛函理论(DFT)和深势分子动力学(DPMD)模拟来研究铪的热力学稳定性和相变行为,特别关注了Pbcn和铁电Pca21相之间的关系。在交换相关泛函中出现了显著的相能量差异:PBE和杂化HSE06泛函表现出一致的趋势,这与PBEsol和SCAN泛函的预测不同。准谐波自由能计算结果与在相同泛函上训练深势的有限温度DPMD模拟结果吻合良好。我们进一步发现,在基于Pca21基态结构的固定力学边界条件下,所有功能函数都预测了一致的相对相稳定性、极化开关势垒和畴壁能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Unexpected density functional dependence of the antipolar $$\boldsymbol{Pbcn}$$ phase in HfO2

Unexpected density functional dependence of the antipolar $$\boldsymbol{Pbcn}$$ phase in HfO2

The antipolar Pbcn phase of HfO2 has been suggested to play a critical role in the phase transitions and polarization switching mechanisms of ferroelectric hafnia. Here, we benchmark density functional theory (DFT) and deep potential molecular dynamics (DPMD) simulations to investigate the thermodynamic stability and phase transition behavior of hafnia, with a particular focus on the relationship between the Pbcn and ferroelectric Pca21 phases. Significant discrepancies in phase energetics emerge across exchange-correlation functionals: the PBE and hybrid HSE06 functionals exhibit consistent trends, which diverge from the predictions of the PBEsol and SCAN functionals. Quasi-harmonic free energy calculations show good agreement with finite-temperature DPMD simulations using deep potentials trained on the same functional. We further find that, under fixed mechanical boundary conditions based on the Pca21 ground-state structure, all functionals predict consistent relative phase stabilities, polarization switching barriers, and domain wall energies.

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来源期刊
npj Computational Materials
npj Computational Materials Mathematics-Modeling and Simulation
CiteScore
15.30
自引率
5.20%
发文量
229
审稿时长
6 weeks
期刊介绍: npj Computational Materials is a high-quality open access journal from Nature Research that publishes research papers applying computational approaches for the design of new materials and enhancing our understanding of existing ones. The journal also welcomes papers on new computational techniques and the refinement of current approaches that support these aims, as well as experimental papers that complement computational findings. Some key features of npj Computational Materials include a 2-year impact factor of 12.241 (2021), article downloads of 1,138,590 (2021), and a fast turnaround time of 11 days from submission to the first editorial decision. The journal is indexed in various databases and services, including Chemical Abstracts Service (ACS), Astrophysics Data System (ADS), Current Contents/Physical, Chemical and Earth Sciences, Journal Citation Reports/Science Edition, SCOPUS, EI Compendex, INSPEC, Google Scholar, SCImago, DOAJ, CNKI, and Science Citation Index Expanded (SCIE), among others.
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