Geometries for Minnesota Database 2019



Minnesota Database 2019 comprises of a diverse set of chemical data that can be used for benchmarking electronic structure calculations and/or optimizing density functionals or wave function methods. The reference values of the data have been published [P. Verma et al., J. Phys. Chem. A 123, 2966-2990 (2019);], and the present compendium provides the molecular geometries, basis set information, and settings that we have used for calculations to compare to the reference data. There are 56 subdatabases in Database 2019, and the data include a variety of atomic and molecular properties, including atomization energies, reaction energies, bond dissociation energies, isomerization energies, noncovalent complexation energies, proton affinities, electron affinities, ionization potentials, barrier heights, thermochemistry of hydrocarbons, absolute atomic energies, vertical and adiabatic electronic excitation energies, and geometries of molecules; both main-group and transition-metal-containing systems are present.

Minnesota Database 2019 is subdivided into a primary set with 31 databases and an auxiliary set with 25 databases. The Minnesota Database 2019 zip file in DRUM contains two folders – one of the folders has Gaussian input files in .txt format and another folder has basis set files in .gbs format. There are 64 .txt files that arise due to 30 databases in the primary set, 24 databases in the auxiliary set, and 10 files for subdatabase S66x8. The S6x6 database in the primary set and the S492 database in the auxiliary set were merged into S66x8, which gives a total of 10 text files – eight of the text files correspond to eight intermonomer distances of the complexes and two of the text files correspond to the monomers itself and are labeled as A and B.

Funding information
Sponsorship: This research 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.
Date made available2019
PublisherData Repository for the University of Minnesota

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