Meta-Generalized-Gradient Approximation made Magnetic
Jacques K. Desmarais, Alessandro Erba, Giovanni Vignale, Stefano, Pittalis

TL;DR
This paper introduces a new meta-GGA density functional approximation that better handles magnetic states, improving the reliability of density functional theory calculations for magnetic materials.
Contribution
The paper presents a novel meta-GGA functional that satisfies key criteria for magnetic states, addressing limitations of previous functionals like SCAN.
Findings
Improved accuracy for ferromagnetic, antiferromagnetic, and non-collinear magnetic states.
Implementation available in the Crystal software package.
Enhanced reliability of DFT calculations for magnetic materials.
Abstract
The Jacob's ladder of density functional theory (DFT) proposes the compelling view that by extending the form of successful approximations -- being guided by exact conditions and selected (least empirical) norms -- upper rungs will do better than the lower, thus allowing to balance accuracy and computational effort. Meta-generalized-gradient-approximations (MGGAs) belong to the last rung of the semi-local approximations before hybridization with non-local wave function theories. Among the MGGAs, the Strongly Constrained and Appropriately Normed Approximation (SCAN) greatly improves upon GGAs from the lower rung. But the over magnetized solutions of SCAN make GGAs more reliable for magnetism. Here, we provide a solution that satisfies the most pressing {\em desiderata} for density functional approximations for ferromagnetic, antiferromagnetic and non-collinear states. The approach is…
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Taxonomy
TopicsInertial Sensor and Navigation · Magnetic Properties and Applications · Model Reduction and Neural Networks
