Size-Consistent Adiabatic Connection Functionals via Orbital-Based Matrix Interpolation
- 8 January 2026
- journal article
- Published by American Chemical Society (ACS) in Journal of Chemical Theory and Computation
- Vol. 22 (2) , 940-951
Abstract
We introduce a size-consistent and orbital-invariant formalism for constructing correlation functionals based on the adiabatic connection for density functional theory (DFT). By constructing correlation energy matrices for the weak and strong correlation limits in the space of occupied orbitals, our method, which we call orbital-based size-consistent matrix interpolation (OSMI), avoids previous difficulties in the construction of size-consistent adiabatic connection functionals. We design a simple, nonempirical adiabatic connection and a one-parameter strong-interaction limit functional, and we show that the resulting method reproduces the correlation energy of the uniform electron gas over a wide range of densities. When applied to subsets of the GMTKN55 thermochemistry database, OSMI is more accurate on average than MP2 and nonempirical density functionals. Most notably, OSMI provides excellent predictions of the barrier heights we tested, with average errors of less than 2 kcal mol-1. Finally, we find that OSMI improves the trade-off between fractional spin and fractional charge errors for bond dissociation curves compared to DFT and MP2. The fact that OSMI provides a good description of molecular systems and the uniform electron gas, while also maintaining low self-interaction error and size-consistency, suggests that it could provide a framework for studying heterogeneous chemical systems.Keywords
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This publication has 85 references indexed in Scilit:
- ACCDB: A collection of chemistry databases for broad computational purposesJournal of Computational Chemistry, 2018
- Local and global interpolations along the adiabatic connection of DFT: a study at different correlation regimesTheoretical Chemistry Accounts, 2018
- Local hybrid functionals: Theory, implementation, and performance of an emerging new tool in quantum chemistry and beyondWIREs Computational Molecular Science, 2018
- PySCF: the Python‐based simulations of chemistry frameworkWIREs Computational Molecular Science, 2017
- Correlation energy from random phase approximations: A reduced density matrices perspectiveInternational Journal of Quantum Chemistry, 2017
- Libcint: An efficient general integral library for Gaussian basis functionsJournal of Computational Chemistry, 2015
- Comparison of second-order orbital-dependent DFT correlation functionalsInternational Journal of Quantum Chemistry, 2008
- The role of databases in support of computational chemistry calculationsJournal of Computational Chemistry, 1996
- DFT ionization formulas and aDFT perturbation theory for exchange and correlation, through adiabatic connectionInternational Journal of Quantum Chemistry, 1995
- The exchange-correlation energy of a metallic surfaceSolid State Communications, 1975