发表机构
Chalmers University of Technology; Donostia International Physics Center (DIPC)（查尔姆斯理工大学; 圣塞巴斯蒂安国际物理中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究将范围分离杂化范德华密度泛函AHBR从Quantum Espresso移植到VASP，实现稳健的基于应力的晶胞优化，并验证其在分子、固体及复杂软物质结构预测中的高精度应用。
AI 中文摘要
复杂物质，通常部分柔软且可塑，是材料系统的普遍形式。因此，我们通常必须首先借助密度泛函理论（DFT）预测原子结构，然后才能利用它来表征（预期的）性质。最近提出的一种范围分离杂化（RSH）范德华密度泛函（vdW-DF），即“vdW-DF2-ahbr”（缩写为AHBR）[PRX 12, 041003 (2022)]，在从分子到固体的结合能和结构预测方面展现出高精度潜力。然而，根据我们的经验，目前在Quantum Espresso（QE）中的实现不支持基于应力的RSH晶胞优化的稳健性。在此，我们记录并展示了实现基于AHBR的实用复杂物质发现的工作：我们将AHBR交换关联泛函移植到Vienna Ab Initio Simulation Package（VASP）中，在该软件中，基于应力的DFT优化对于RSH也已稳定。我们通过比较高精度的AHBR-QE和AHBR-VASP对非共价分子相互作用以及简单体相结构的结构和内聚性的预测来测试该实现。我们还展示并测试了新的AHBR-VASP实现用于预测和理解畸变岩盐金属一氧化物中的（原子和反铁磁）结构。最后，我们通过预测C2N共价有机框架（COF）体系[Nat. Commun. 6, 6486 (2015)]中的层堆叠基序，展示了其在复杂软物质发现中的应用。
英文摘要
Complex matter, often partly soft and pliable, is the generic form of material systems. We must therefore generally call on density functional theory (DFT) to first predict the atomic structure before we can use it to also characterize (expected) properties. A recent range-separated hybrid (RSH) van Waals density functional (vdW-DF), `vdW-DF2-ahbr' (abbreviated AHBR) [PRX 12, 041003 (2022)], shows promise as a high-accuracy predictor of both binding energies and structure, from molecules to solids. However, the present implementation in Quantum Espresso (QE) does not, in our experience, support robust stress-based unit-cell optimization of RSHs. Here we document and illustrate work enabling practical AHBR-based complex-matter discovery: We port the AHBR XC functional to the Vienna Ab Initio Simulation Package (VASP) where use of stress-based DFT optimization is already stable also for RSHs. We test the implementation by comparing high-accuracy AHBR-QE and AHBR-VASP predictions of non-covalent molecular interactions and for structure and cohesion of simple bulk structures. We also illustrate and test the use of the new AHBR-VASP implementation to predict and understand (atomic and anti-ferromagnetic) structure in distorted-rocksalt metal monoxides. Finally, we illustrate use for complex-soft-matter discovery by predicting motifs for layer stacking in the C2N covalent-organic framework (COF) system [Nat. Commun. 6, 6486 (2015)].
Comments10 figures, Six tables
