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Predicting Ligand-Dissociation Energies of 3d Coordination Complexes with Auxiliary-Field Quantum Monte Carlo

Benjamin Rudshteyn, Dilek Coskun, John L. Weber, Evan J. Arthur, Shiwei Zhang, David R. Reichman, Richard A. Friesner, James Shee

2020Journal of Chemical Theory and Computation47 citationsDOIOpen Access PDF

Abstract

Transition-metal complexes are ubiquitous in biology and chemical catalysis, yet they remain difficult to accurately describe with ab initio methods because of the presence of a large degree of dynamic electron correlation, and, in some cases, strong static correlation which results from a manifold of low-lying states. Progress has been hindered by a scarcity of high-quality gas-phase experimental data, while exact ab initio predictions are usually computationally unaffordable because of the large size of the relevant complexes. In this work, we present a data set of 34 tetrahedral, square planar, and octahedral 3d metal-containing complexes with gas-phase ligand-dissociation energies that have reported uncertainties of ≤2 kcal/mol. We perform all-electron phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) calculations utilizing multideterminant trial wave functions selected by a black box procedure. We compare the results with those from the density functional theory (DFT) with the B3LYP, B97, M06, PBE0, ωB97X-V, and DSD-PBEP86/2013 functionals and a localized orbital variant of the coupled cluster theory with single, double, and perturbative triple excitations (DLPNO-CCSD(T)). We find mean averaged errors of 1.07 ± 0.27 kcal/mol for our most sophisticated ph-AFQMC approach versus 2.81 kcal/mol for DLPNO-CCSD(T) and 1.49–3.78 kcal/mol for DFT. We find maximum errors of 2.96 ± 1.71 kcal/mol for our best ph-AFQMC method versus 9.15 kcal/mol for DLPNO-CCSD(T) and 5.98–13.69 kcal/mol for DFT. The reasonable performance of a number of DFT functionals is in stark contrast to the much poorer accuracy previously demonstrated for diatomic species, suggesting a moderation in electron correlation because of ligand coordination in most cases. However, the unpredictably large errors for a small subset of cases with both DFT and DLPNO-CCSD(T) methods leave cause for concern, especially in light of the unreliability of common multireference indicators. In contrast, the robust and, in principle, systematically improvable results of ph-AFQMC for these realistic complexes establish the method as a useful tool for elucidating the electronic structure of transition-metal-containing complexes and predicting their gas-phase properties.

Topics & Concepts

Monte Carlo methodDissociation (chemistry)Quantum Monte CarloField (mathematics)Statistical physicsQuantumChemical physicsPhysicsComputational chemistryComputer scienceChemistryPhysical chemistryQuantum mechanicsMathematicsPure mathematicsStatisticsAdvanced Chemical Physics StudiesCatalysis and Oxidation ReactionsCatalytic Processes in Materials Science