biostudies-literatureMehta NArtificial Intelligence and Smart Materials Research FundIsrael Science FoundationMinerva Foundation9332-9338https://www.ebi.ac.uk/biostudies/studies/S-EPMC9575149biostudies-literatureUnknown13(40)Following earlier work [Mehta, N.; Martin, J. M. L. <i>J. Chem. Theory Comput.</i>2022, 10.1021/acs.jctc.2c00426] that showed how the slow basis set convergence of the double hybrid density functional theory can be obviated by the use of F12 explicit correlation in the GLPT2 step (second order Görling-Levy perturbation theory), we demonstrate here for the very large and chemically diverse GMTKN55 benchmark suite that the CPU time scaling of this step can be reduced (asymptotically linearized) using the localized pair natural orbital (PNO-L) approximation at negligible cost in accuracy.The journal of physical chemistry lettersReduced-Scaling Double Hybrid Density Functional Theory with Rapid Basis Set Convergence through Localized Pair Natural Orbital F12.PMC95751491969/202020/05Mehta NMartin JMLfalseReduced-Scaling Double Hybrid Density Functional Theory with Rapid Basis Set Convergence through Localized Pair Natural Orbital F12.Following earlier work [Mehta, N.; Martin, J. M. L. <i>J. Chem. Theory Comput.</i>2022, 10.1021/acs.jctc.2c00426] that showed how the slow basis set convergence of the double hybrid density functional theory can be obviated by the use of F12 explicit correlation in the GLPT2 step (second order Görling-Levy perturbation theory), we demonstrate here for the very large and chemically diverse GMTKN55 benchmark suite that the CPU time scaling of this step can be reduced (asymptotically linearized) using the localized pair natural orbital (PNO-L) approximation at negligible cost in accuracy.2022-01-01T00:00:00Z2022 Oct2025-04-04T22:43:50.397Z2025-04-04T22:43:50.397ZS-EPMC95751493617885210.1021/acs.jpclett.2c02620