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Automatic Clustering of Excited-State Trajectories: Application to Photoexcited Dynamics
[Image: see text] We introduce automatic clustering as a computationally efficient tool for classifying and interpreting trajectories from simulations of photo-excited dynamics. Trajectories are treated as time-series data, with the features for clustering selected by variance mapping of normalized...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
American Chemical Society
2023
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536988/ https://www.ncbi.nlm.nih.gov/pubmed/37703098 http://dx.doi.org/10.1021/acs.jctc.3c00776 |