Skala is a neural XC functional trained on wavefunction data that beats state-of-the-art hybrids on main-group chemistry benchmarks at semi-local computational cost.
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Using modified Hartree-Fock pseudopotentials for Cu core electrons eliminates propagated density errors, yielding accurate bandgaps and lattice constants across 50+ Cu semiconductors.
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Accurate and scalable exchange-correlation with deep learning
Skala is a neural XC functional trained on wavefunction data that beats state-of-the-art hybrids on main-group chemistry benchmarks at semi-local computational cost.
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Minimizing propagated density errors of atomic core-electron for simultaneously accurate bandgaps and lattice constants in closed-shell Copper semiconductors
Using modified Hartree-Fock pseudopotentials for Cu core electrons eliminates propagated density errors, yielding accurate bandgaps and lattice constants across 50+ Cu semiconductors.