Abstract 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 …
MJP Hodgson, E Kraisler, A Schild… - The journal of physical …, 2017 - ACS Publications
Accurate density functional calculations hinge on reliable approximations to the unknown exchange-correlation (xc) potential. The most popular approximations usually lack features …
W Jing, M Liu, J Wen, L Ning, M Yin, CK Duan - Physical Review B, 2021 - APS
Titanium sapphire is one of the most important laser crystals suitable for widely tunable and ultrashort pulsed lasers with high gain and high power outputs, but its performance is limited …
J Carmona-Espíndola, JL Gázquez… - Journal of Chemical …, 2018 - ACS Publications
We develop and validate a nonempirical generalized gradient approximation (GGA) exchange (X) density functional that performs as well as the SCAN (strongly constrained and …
Accurately describing excited states within Kohn–Sham (KS) density functional theory (DFT), particularly those which induce ionization and charge transfer, remains a great challenge …
Many approximations within density-functional theory spuriously predict that a many- electron system can dissociate into fractionally charged fragments. Here, we revisit the case …
There are several approximations to the exchange-correlation functional in density- functional theory, which accurately predict total energy-related properties of many-electron …
A widely used approximation to the exchange-correlation functional in density functional theory is the local density approximation (LDA), typically derived from the properties of the …
M De Vetta, I Corral - Computational and Theoretical Chemistry, 2019 - Elsevier
The pentafluorophenyl (PFP) moiety is an important and versatile substituent in the chemistry of BODIPYs, porphyrins and corroles. The widespread use of PFP meso …