Kothakonda Manish, Kaplan Aaron D, Isaacs Eric B, Bartel Christopher J, Furness James W, Ning Jinliang, Wolverton Chris, Perdew John P, Sun Jianwei
Department of Physics and Engineering Physics, Tulane University, New Orleans, Louisiana70118, United States.
Department of Physics, Temple University, Philadelphia, Pennsylvania19122, United States.
ACS Mater Au. 2022 Nov 9;3(2):102-111. doi: 10.1021/acsmaterialsau.2c00059. eCollection 2023 Mar 8.
A central aim of materials discovery is an accurate and numerically reliable description of thermodynamic properties, such as the enthalpies of formation and decomposition. The rSCAN revision of the strongly constrained and appropriately normed (SCAN) meta-generalized gradient approximation (meta-GGA) balances numerical stability with high general accuracy. To assess the rSCAN description of solid-state thermodynamics, we evaluate the formation and decomposition enthalpies, equilibrium volumes, and fundamental band gaps of more than 1000 solids using rSCAN, SCAN, and PBE, as well as two dispersion-corrected variants, SCAN+rVV10 and rSCAN+rVV10. We show that rSCAN achieves accuracy comparable to SCAN and often improves upon SCAN's already excellent accuracy. Although SCAN+rVV10 is often observed to worsen the formation enthalpies of SCAN and makes no substantial correction to SCAN's cell volume predictions, rSCAN+rVV10 predicts marginally less accurate formation enthalpies than rSCAN, and slightly more accurate cell volumes than rSCAN. The average absolute errors in predicted formation enthalpies are found to decrease by a factor of 1.5 to 2.5 from the GGA level to the meta-GGA level. Smaller decreases in error are observed for decomposition enthalpies. For formation enthalpies rSCAN improves over SCAN for intermetallic systems. For a few classes of systems-transition metals, intermetallics, weakly bound solids, and enthalpies of decomposition into compounds-GGAs are comparable to meta-GGAs. In total, rSCAN and rSCAN+rVV10 can be recommended as stable, general-purpose meta-GGAs for materials discovery.
材料发现的一个核心目标是对热力学性质进行准确且数值可靠的描述,例如形成焓和分解焓。强约束且适当归一化(SCAN)的元广义梯度近似(meta - GGA)的rSCAN修正平衡了数值稳定性和较高的普遍准确性。为了评估rSCAN对固态热力学的描述,我们使用rSCAN、SCAN和PBE以及两种色散校正变体SCAN + rVV10和rSCAN + rVV10,评估了1000多种固体的形成焓、分解焓、平衡体积和基本带隙。我们表明,rSCAN实现了与SCAN相当的准确性,并且常常在SCAN已经出色的准确性基础上有所提高。虽然通常观察到SCAN + rVV10会使SCAN的形成焓变差,并且对SCAN的晶胞体积预测没有实质性校正,但rSCAN + rVV10预测的形成焓准确性略低于rSCAN,而晶胞体积比rSCAN略准确。发现预测形成焓的平均绝对误差从广义梯度近似(GGA)水平到元广义梯度近似(meta - GGA)水平降低了1.5至2.5倍。分解焓的误差降低幅度较小。对于形成焓,rSCAN在金属间化合物体系方面比SCAN有所改进。对于几类体系——过渡金属、金属间化合物、弱结合固体以及分解为化合物的焓——广义梯度近似(GGAs)与元广义梯度近似(meta - GGAs)相当。总体而言,rSCAN和rSCAN + rVV10可被推荐为用于材料发现的稳定通用元广义梯度近似。