There are two core goals in exchange-correlation functional design: accuracy and efficiency. Whilst modern semi-local functionals have greatly improved accuracy, this has often been at the cost of efficiency. In a recent publication [1] Bartók and Yates propose a regularised SCAN (rSCAN) that resolves these numerical problems for the SCAN functional [2] at the expense of breaking exact constraints and reducing accuracy. We present the r2SCAN functional [3] that restores exact constraint adherence while preserving regularisation. The r2SCAN functional combines the accuracy of SCAN with the numerical efficiency of rSCAN and presents a powerful tool for bringing high accuracy DFT to numerically sensitive and large-scale problems.

Accurate and numerically efficient r2SCAN meta-generalized gradient approximation

ACS Fall 2021

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