ACCDB: A Collection of Chemistry DataBases for Broad Computational Purposes

Abstract

The importance of databases of reliable and accurate data in chemistry has substantially increased in the past two decades. Their main usage is to parametrize electronic structure theory methods, and to assess their capabilities and accuracy for a broad set of chemical problems. The collection we present here -ACCDB- includes data from 16 different research groups, for a total of 44,931 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, Minnesota2015B, 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 expandable software tools for its manipulation is also presented here for the first time, as well as a case study where ACCDB is used for benchmarking commercial CPUs for chemistry calculations. To be published in J. Comput. Chem.

References in corpus (7)

• By-passing the Kohn-Sham equations with machine learning
• Assessment of W1 and W2 theories for the computation of electron affinities, ionization potentials, heats of formation, and proton affinities
• How accurate is density functional theory at predicting dipole moments? An assessment using a new database of 200 benchmark values
• Performance of ab initio and density functional methods for conformational equilibria of CnH2n+2 alkane isomers (n=2-8)
• Benchmark thermochemistry of the C_nH_{2n+2} alkane isomers (n=2--8) and performance of DFT and composite ab initio methods for dispersion-driven isomeric equilibria
• Density Functional Theory is Not Straying from the Path toward the Exact Functional
• Benchmark all-electron ab initio quantum Monte Carlo calculations for small molecules

Cited by in corpus (8)

• Accurate prediction of the properties of materials using the CAM-B3LYP Density Functional
• On the Computation of Dipole Moments: A Recommendation on the Choice of the Basis Set and the Level of Theory
• Canonical and DLPNO-based G4(MP2)XK-inspired composite wavefunction methods parametrized against large and chemically diverse training sets: Are they more accurate and/or robust than double hybrid DFT?
• NENCI-2021 Part I: A Large Benchmark Database of Non-Equilibrium Non-Covalent Interactions Emphasizing Close Intermolecular Contacts
• Exploring Avenues Beyond Revised DSD Functionals: II. Random-Phase Approximation and scaled MP3 corrections
• Canonical and DLPNO-based composite wavefunction methods parametrized against large and chemically diverse training sets. 2. Correlation consistent basis sets, core-valence correlation, and F12 alternatives
• Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
• Can G4-like Composite Ab Initio Methods Accurately Predict Vibrational Harmonic Frequencies?