Application of Semiempirical Methods to Transition Metal Complexes: Fast Results but Hard-to-Predict Accuracy.

Yury Minenkov, Dmitry I. Sharapa, Luigi Cavallo

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

A series of semiempirical PM6* and PM7 methods has been tested in reproducing of relative conformational energies of 27 realistic-size complexes of 16 different transition metals (TMs). An analysis of relative energies derived from single-point energy evaluations on density functional theory (DFT) optimized conformers revealed pronounced deviations between semiempirical and DFT methods indicating fundamental difference in potential energy surfaces (PES). To identify the origin of the deviation, we compared fully optimized PM7 and respective DFT conformers. For many complexes, differences in PM7 and DFT conformational energies have been confirmed often manifesting themselves in false coordination of some atoms (H, O) to TMs and chemical transformations/distortion of coordination center geometry in PM7 structures. Despite geometry optimization with fixed coordination center geometry leads to some improvements in conformational energies, the resulting accuracy is still too low to recommend explored semiempirical methods for out-of-the-box conformational search/sampling: careful testing is always needed.
Original languageEnglish (US)
Pages (from-to)3428-3439
Number of pages12
JournalJournal of Chemical Theory and Computation
Volume14
Issue number7
DOIs
StatePublished - May 22 2018

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: We gratefully acknowledge Prof. Frank Jensen, Department of Chemistry, Aarhus University, Denmark, Prof. J. J. P. Stewart, Stewart Computational Chemistry, Colorado Springs, USA and Dr. Alexander M. Genaev, N. N. Vorozhtsov Institute of Organic Chemistry, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia for helpful discussions. The research reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST). For computer time, this research used the resources of the Supercomputing Laboratory at King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia. Y.M. gratefully acknowledges support from the Government of the Russian Federation (Agreement № 074-02-2018-286).

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