Abstract
Accurately predicting the spin splitting energy of chemical species is important for understanding their reactivity and magnetic properties, but it is very challenging, especially for molecules containing transition metals. One impediment to progress is the scarcity of accurate benchmark data. Here we report a set of calculations designed to yield reliable benchmarks for simple transition-metal complexes that can be used to test density functional methods that are affordable for large systems of more practical interest. Various wave function methods are tested against experiment for Fe2+, Fe3+, and Co3+, including CASSCF, CASPT2, CASPT3, MRCISD, MRCISD+Q, ACPF, AQCC, CCSD(T), and CASPT2/CCSD(T) and also a new method called CASPT2.5, which is performed by taking the average of the CASPT2 and CASPT3 energies. We find that MRCISD+Q, ACPF, and AQCC require smaller active spaces for good accuracy than are required by CASPT2 and CASPT3, and this aspect may be important for calculations on larger molecules; here we find that CASPT2.5 extrapolated to a complete basis set is the most suitable method - in terms of computational cost and in terms of accuracy on monatomic systems - and therefore we chose this method for molecular benchmarks. Then Kohn-Sham density functional calculations with 60 exchange-correlation functionals are tested for FeF2, FeCl2, and CoF2. We find that MN15-L, M06-SX, and revM06 have very good agreement with CASPT2.5 benchmarks in terms of both the spin splitting energy and the optimized geometry for each spin state. In addition, we recommend def2-TZVP as the most suitable basis set to perform density functional calculations for molecular spin splitting energies; extra polarization functions in the basis set do not help to increase the accuracy of the spin splitting energy in KS calculations.
Original language | English (US) |
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Pages (from-to) | 4416-4428 |
Number of pages | 13 |
Journal | Journal of Chemical Theory and Computation |
Volume | 16 |
Issue number | 7 |
DOIs | |
State | Published - Jul 14 2020 |
Bibliographical note
Funding Information:We thank Zoltan Varga, Jie J. Bao, and Chen Zhou for help with calculations and useful discussions. We also thank Xu Cai for help with software installation. We thank Pragya Verma for helpful feedback on the manuscript. This work was supported as part of the Nanoporous Materials Genome Center by the U.S. Department of Energy Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences under award DE-FG02-17ER16362 as part of the Computational Chemical Sciences Program.
Funding Information:
We thank Zoltan Varga, Jie J. Bao, and Chen Zhou for help with calculations and useful discussions. We also thank Xu Cai for help with software installation. We thank Pragya Verma for helpful feedback on the manuscript. This work was supported as part of the Nanoporous Materials Genome Center by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences under award DE-FG02-17ER16362 as part of the Computational Chemical Sciences Program.
Publisher Copyright:
Copyright © 2020 American Chemical Society.
PubMed: MeSH publication types
- Journal Article