Support Information for Machine-learning nonadiabatic couplings enable reactive photochemical reaction dynamics

Figshare 2026 Dataset Open access

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Authors: Leticia Adao Gomes, Steven Lopez, Sean P. Larmore
DOI: 10.6084/m9.figshare.31543393
Cited by: 0

Abstract

These folders contain information for each reaction: Dataset: training, validation, and test set for each modelCompiled_ModelsML-NAMD - Contains subdirectories depending on the number of trajectories. For example, for DBH has 500-NAMD and 5000-NAMD. Inside the subdirectories are .json files containing the trajectories data.

Fields of Study & Subjects

Machine Learning in Materials Science Advanced Chemical Physics Studies Spectroscopy and Quantum Chemical Studies

Publication details

Journal / source
Figshare
Publication date
11 March 2026
Language
EN
Document type
Dataset