Dataset

mbGDML_maldonado_2023



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Name mbGDML_maldonado_2023
Extended ID mbGDML_maldonado_2023_Maldonado__DS_e94my2wrh074_0
Description Configurations of water, acetonitrile and methanol, simulated with ASE and modeled using a variety of software and methods: GAP, SchNet, GDML, ORCA and mbGDML. Forces and potential energy included; metadata includes kinetic energy and velocities.
Authors Alex M. Maldonado
Elements H (60.76%)
O (14.76%)
C (18.57%)
N (5.91%)
Number of Data Objects 24,511
Number of Configurations 24,543
Number of Atoms 712,134
Links https://doi.org/10.26434/chemrxiv-2023-wdd1r
https://doi.org/10.5281/zenodo.7112197
Configuration Sets by Name mbGDML  — Configurations from the mbGDML set predicted using mbgDML
GAP — Configurations from the mbGDML set predicted using GAP
SchNet — Configurations from the mbGDML set predicted using SchNet
GFN2 — Configurations from the mbGDML set predicted using XTB at GFN2 level of theory
ORCA — Configurations from the mbGDML set predicted using ORCA
Configuration Sets by ID CS_5qkxmtkuwrv4_0
CS_tjmv0thx9ckt_0
CS_s5e17m3qqhc3_0
CS_4o5nvkvf2880_0
CS_3scrgs9ecuz3_0
Data Objects Too many to display
ColabFit ID DS_e94my2wrh074_0
Files colabfitspec.json

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