Lórien MacEnulty, Matteo Giantomassi, Bernard Amadon, Gian-Marco Rignanese and David D O’Regan
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引用次数: 0
摘要
密度泛函理论(DFT)+U 系列函数的成员是以最低计算成本解决(半)局部交换相关函数固有误差的日益普遍的方法,但需要针对给定的相关系统、模拟方案和运行时参数就地计算其参数 U 和 J。自洽场(SCF)线性响应方法提供了 U 的原初获取,最近又扩展到类似地计算 J,以测量与类交换效应相关的局部误差。我们介绍了一种新的后处理器 lrUJ 工具,以及这份详细的最佳实践指南,使流行的开源 Abinit 第一性原理模拟套件的用户能够轻松使用原位哈伯德参数,并简化将其纳入相关材料模拟的过程。其他 DFT 代码的用户和开发人员可能也会对该工具的功能感兴趣,其中包括 n 度多项式回归、误差分析、Python 绘图工具、教学文档以及进一步开发的途径。在本技术介绍和指南中,我们特别强调了投影仪增强波方法、SCF 混合方案和非线性响应所带来的复杂性和潜在隐患,其中有几项可转化为其他软件包中的 DFT+U(+J) 实现。
Facilities and practices for linear response Hubbard parameters U and J in Abinit
Members of the density functional theory (DFT)+U family of functionals are increasingly prevalent methods of addressing errors intrinsic to (semi-) local exchange-correlation functionals at minimum computational cost, but require their parameters U and J to be calculated in situ for a given system of interest, simulation scheme, and runtime parameters. The self-consistent field (SCF) linear response approach offers ab initio acquisition of the U and has recently been extended to compute the J analogously, which measures localized errors related to exchange-like effects. We introduce a renovated post-processor, the lrUJ utility, together with this detailed best-practices guide, to enable users of the popular, open-source Abinit first-principles simulation suite to engage easily with in situ Hubbard parameters and streamline their incorporation into material simulations of interest. Features of this utility, which may also interest users and developers of other DFT codes, include n-degree polynomial regression, error analysis, Python plotting facilities, didactic documentation, and avenues for further developments. In this technical introduction and guide, we place particular emphasis on the intricacies and potential pitfalls introduced by the projector augmented wave method, SCF mixing schemes, and non-linear response, several of which are translatable to DFT+U(+J) implementations in other packages.