56 citations · 297 across the 15 of their papers we have counts for
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physics.chem-ph2021★ 35 cited
Machine learning the derivative discontinuity of density-functional theory
Johannes Gedeon, Jonathan Schmidt, Matthew J. P. Hodgson +3
Machine learning is a powerful tool to design accurate, highly non-local, exchange-correlation functionals for density functional theory. So far, most of those machine learned func…
cond-mat.mtrl-sci2021★ 2 cited
Exact expressions for the height of the interatomic step in the exchange-correlation potential from the derivative discontinuity of the energy
M. J. P. Hodgson
Popular approximations to the exchange-correlation (xc) energy of density functional theory do not yield the spatial `step' structures in the exact xc potential which are necessary…