Name: SN2_JCTC_2019 Extended ID: SN2_JCTC_2019__Unke-Meuwly__DS_3tspv1150ejj_0 Description: The SN2 dataset was generated as a partner benchmark dataset, along with the 'solvated protein fragments' dataset, for measuring the performance of machine learning models, in particular PhysNet, at describing chemical reactions, long-range interactions, and condensed phase systems. SN2 probes chemical reactions of methyl halides with halide anions, i.e. X- + CH3Y -> CH3X + Y-, and contains structures, for all possible combinations of X,Y = F, Cl, Br, I. The dataset also includes various structures for several smaller molecules that can be formed in fragmentation reactions, such as CH3X, HX, CHX or CH2X- as well as geometries for H2, CH2, CH3+ and XY interhalogen compounds. In total, the dataset provides reference energies, forces, and dipole moments for 452709 structurescalculated at the DSD-BLYP-D3(BJ)/def2-TZVP level of theory using ORCA 4.0.1. Authors: Oliver T. Unke Markus Meuwly DOI: 10.60732/31df6835 Calculated Property Types: atomic_forces cauchy_stress energy Elements: Br (8.51%) C (16.64%) Cl (8.51%) F (8.51%) H (49.31%) I (8.51%) Methods: DFT-DSD-BLYP+D3(BJ) Software: ORCA 4.0.1 Number of Configurations: 394,653 Number of Atoms: 2,194,070 Publication Link: https://doi.org/10.1021/acs.jctc.9b00181 Data Source Link: https://doi.org/10.5281/zenodo.2605341