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Explicitly correlated coupled cluster method for accurate treatment of open-shell molecules with hundreds of atoms

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Neese,  Frank
Research Department Neese, Max-Planck-Institut für Kohlenforschung, Max Planck Society;

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Citation

Kumar, A., Neese, F., & Valeev, E. F. (2020). Explicitly correlated coupled cluster method for accurate treatment of open-shell molecules with hundreds of atoms. The Journal of Chemical Physics, 153(9): 094105. doi:10.1063/5.0012753.


Cite as: https://hdl.handle.net/21.11116/0000-0007-4DA2-C
Abstract
We present a near-linear scaling formulation of the explicitly correlated coupled-cluster singles and doubles with the perturbative triples method [CCSD(T)F͞12] for high-spin states of open-shell species. The approach is based on the conventional open-shell CCSD formalism [M. Saitow et al., J. Chem. Phys. 146, 164105 (2017)] utilizing the domain local pair-natural orbitals (DLPNO) framework. The use of spin-independent set of pair-natural orbitals ensures exact agreement with the closed-shell formalism reported previously, with only marginally impact on the cost (e.g., the open-shell formalism is only 1.5 times slower than the closed-shell counterpart for the C160H322 n-alkane, with the measured size complexity of ≈1.2). Evaluation of coupled-cluster energies near the complete-basis-set (CBS) limit for open-shell systems with more than 550 atoms and 5000 basis functions is feasible on a single multi-core computer in less than 3 days. The aug-cc-pVTZ DLPNO-CCSD(T)F͞12 contribution to the heat of formation for the 50 largest molecules among the 348 core combustion species benchmark set [J. Klippenstein et al., J. Phys. Chem. A 121, 6580–6602 (2017)] had root-mean-square deviation (RMSD) from the extrapolated CBS CCSD(T) reference values of 0.3 kcal/mol. For a more challenging set of 50 reactions involving small closed- and open-shell molecules [G. Knizia et al., J. Chem. Phys. 130, 054104 (2009)], the aug-cc-pVQ(+d)Z DLPNO-CCSD(T)F͞12 yielded a RMSD of ∼0.4 kcal/mol with respect to the CBS CCSD(T) estimate.