Testing the r$^2$SCAN density functional for the thermodynamic stability of solids with and without a van der Waals correction
Abstract
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 bandgaps of more than 1,000 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. Whereas 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.
Keywords
Cite
@article{arxiv.2208.02841,
title = {Testing the r$^2$SCAN density functional for the thermodynamic stability of solids with and without a van der Waals correction},
author = {Manish Kothakonda and Aaron D. Kaplan and Eric B. Isaacs and Christopher J. Bartel and James W. Furness and Jinliang Ning and Chris Wolverton and John P. Perdew and Jianwei Sun},
journal= {arXiv preprint arXiv:2208.02841},
year = {2022}
}