Combining machine learning and quantum chemical calculations for high-throughput virtual screening of thermally activated delayed fluorescence molecular materials: the impact of selection strategy and structural mutations

In view of the theoretical importance and huge application potential of Thermally Activated Delayed Fluorescence (TADF) materials, it is of great significance to conduct High-Throughput Virtual Screening (HTVS) on compound libraries to find TADF candidate molecules. This research focuses on the comp...

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Detalles Bibliográficos
Autores principales: Tu, Chunyun, Huang, Weijiang, Liang, Sheng, Wang, Kui, Tian, Qin, Yan, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2022
Materias:
Chemistry
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9619240/
https://www.ncbi.nlm.nih.gov/pubmed/36349007
http://dx.doi.org/10.1039/d2ra05643g

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9619240/
https://www.ncbi.nlm.nih.gov/pubmed/36349007
http://dx.doi.org/10.1039/d2ra05643g

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