Sparse Gaussian Process Regression-Based Machine Learned First-Principles Force-Fields for Saturated, Olefinic, and Aromatic Hydrocarbons

[Image: see text] Universal machine learning (ML) interatomic potentials (IAPs) for saturated, olefinic, and aromatic hydrocarbons are generated by using the Sparse Gaussian process regression algorithm. The universal potentials are obtained by combining the potentials for the previously trained alk...

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Detalles Bibliográficos
Autores principales: Ha, Miran, Hajibabaei, Amir, Pourasad, Saeed, Kim, Kwang S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9718321/
https://www.ncbi.nlm.nih.gov/pubmed/36855568
http://dx.doi.org/10.1021/acsphyschemau.1c00058

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9718321/
https://www.ncbi.nlm.nih.gov/pubmed/36855568
http://dx.doi.org/10.1021/acsphyschemau.1c00058

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