SCAN+rVV10: A promising van der Waals density functional
Haowei Peng, Zeng-Hui Yang, Jianwei Sun, and John P. Perdew

TL;DR
The paper introduces SCAN+rVV10, a new van der Waals density functional that combines SCAN meta-GGA with rVV10 non-local correlation, achieving high accuracy for diverse materials with minimal empirical parameters.
Contribution
It develops a hybrid functional pairing SCAN with rVV10 to effectively incorporate long-range vdW interactions with minimal empiricism.
Findings
Accurately predicts inter-layer binding energies and lattice constants for layered materials.
Outperforms existing methods in geometric and energetic accuracy.
Effective for molecules, solids, and surface adsorption studies.
Abstract
The newly developed "strongly constrained and appropriately normed" (SCAN) meta-generalized-gradient approximation (meta-GGA) can generally improve over the non-empirical Perdew-Burke-Ernzerhof (PBE) GGA not only for strong chemical bonding, but also for the intermediate-range van der Waals (vdW) interaction. However, the long-range vdW interaction is still missing. To remedy this, we propose here pairing SCAN with the non-local correlation part from the rVV10 vdW density functional, with only two empirical parameters. The resulting SCAN+rVV10 yields excellent geometric and energetic results not only for molecular systems, but also for solids and layered-structure materials, as well as the adsorption of benzene on coinage metal surfaces. Especially, SCAN+rVV10 outperforms all current methods with comparable computational efficiencies, accurately reproducing the three most fundamental…
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Taxonomy
TopicsAdvanced Thermoelectric Materials and Devices · Thermal properties of materials · Machine Learning in Materials Science
