DFTB Simulation of Charged Clusters Using Machine Learning Charge Inference

Paul Guibourg, Léo Dontot, Pierre-Matthieu Anglade, Benoit Gervais

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DOI: 10.1021/acs.jctc.4c00107
Published: 2024-05-01
Container: Journal of Chemical Theory and Computation
Publisher: American Chemical Society (ACS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1021/acs.jctc.4c00107,
  title = {DFTB Simulation of Charged Clusters Using Machine Learning Charge Inference},
  author = {Paul Guibourg and Léo Dontot and Pierre-Matthieu Anglade and Benoit Gervais},
  year = {2024},
  journal = {Journal of Chemical Theory and Computation},
  doi = {10.1021/acs.jctc.4c00107},
  url = {https://doi.org/10.1021/acs.jctc.4c00107}
}

RIS

TY  - JOUR
TI  - DFTB Simulation of Charged Clusters Using Machine Learning Charge Inference
AU  - Paul Guibourg
AU  - Léo Dontot
AU  - Pierre-Matthieu Anglade
AU  - Benoit Gervais
PY  - 2024
JO  - Journal of Chemical Theory and Computation
DO  - 10.1021/acs.jctc.4c00107
UR  - https://doi.org/10.1021/acs.jctc.4c00107
ER  -

APA

Guibourg, P., Dontot, L., Anglade, P., & Gervais, B. (2024). DFTB Simulation of Charged Clusters Using Machine Learning Charge Inference. Journal of Chemical Theory and Computation. https://doi.org/10.1021/acs.jctc.4c00107

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crossref · retrieved 2026-09-25T09:28:56.345Z