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Description The data set was generated from ab-initio molecular dynamics simulations and was used to study the adsorption and desorption dynamics of nitrogen atoms on top of amorphous solid water (ASW) [1]. The data set contains structures with 3 to 378 atoms which result in 28,715 structures in total. The atomization energies and atomic forces are calculated at the PBEh-3c/def2-mSVP level of theory [2]. For more details, see Ref. 1. Format The data is stored in python compressed array format (.npz) with the atomization energy in kcal/mol and atomic forces in kcal/mol/Ang. The data set contains five numpy arrays import numpy as np data = np.load('N-ASW.npz') data['R'] # Cartesian coordinates of nuclei (Ang.) data['E'] # Total energy (kcal/mol) data['F'] # Atomic forces (kcal/mol/Ang.) data['N'] # Number of atoms in each structure data['Z'] # Nuclear charges References [1] Molpeceres G.; Zaverkin V.; and Kästner J. Neural-Network Assisted Study of Nitrogen Atom Dynamics on Amorphous Solid Water. I. Adsorption & Desorption. Mon. Not. R. Astron. Soc. 2020, submitted [2] Grimme S.; Brandenburg J. G.; Bannwarth C.; Hansen A. Consistent structures and interactions by density functional theory with small atomic orbital basis sets. J. Chem. Phys. 2015, 143, 054107.
Astrochemistry, Machine Learning, Molecular Dynamics, Density Functional Theory
Astrochemistry, Machine Learning, Molecular Dynamics, Density Functional Theory
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