Machine Learning and Quantum Calculation for Predicting Yield in Cu-Catalyzed P–H Reactions

The paper discussed the use of machine learning (ML) and quantum chemistry calculations to predict the transition state and yield of copper-catalyzed P–H insertion reactions. By analyzing a dataset of 120 experimental data points, the transition state was determined using density functional theory (...

Descripción completa

Detalles Bibliográficos
Autores principales: Ma, Youfu, Zhang, Xianwei, Zhu, Lin, Feng, Xiaowei, Kowah, Jamal A. H., Jiang, Jun, Wang, Lisheng, Jiang, Lihe, Liu, Xu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10458182/
https://www.ncbi.nlm.nih.gov/pubmed/37630247
http://dx.doi.org/10.3390/molecules28165995

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10458182/
https://www.ncbi.nlm.nih.gov/pubmed/37630247
http://dx.doi.org/10.3390/molecules28165995

Ejemplares similares