The importance of databases of reliable and accurate data in computational chemistry and chemical catalysis has drastically increased in recent years. Their usage spans from parametrization and evaluation of electronic structure theory methods, to design of new catalysts, or prediction new reactions. The collection we present here—called ACCDB—includes a total of almost 45,000 unique reference data points, all at a level of theory significantly higher than DFT, and covering most of the periodic table. It is composed of five databases taken from literature (GMTKN, MGCDB84, Minnesota2015, DP284, and W4-17), two newly developed reaction energy databases (W4-17-RE, and MN-RE), and a new collection of databases containing transition metals. A set of accompanying software tools was also developed and made available for its manipulation.<br/><br/>In addition to ACCDB, we performed a detailed statistical analysis based on the performance of more than 200 DFT exchange–correlation functional approximations, with the goal of extracting a representative subset. The reduced-size, statistically-significamt subset—called ACCDB:RSR20—retains the same across-the-board coverage of molecules and properties of ACCDB, in a more manageable size. This reduced set is obtained using advanced clustering techniques only, and is designed to be less biased than other small databases available for method development. As such, RSR20 is catered towards method development, with immediate applications to parametrizations of new DFT functionals.

ACCDB: A collection of chemistry databases for broad computational purposes, and its reduction to statistically significant subsets

2019 Spring National Meeting

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