Low-cost machine learning prediction of excited state properties of iridium-centered phosphors

Prediction of the excited state properties of photoactive iridium complexes challenges ab initio methods such as time-dependent density functional theory (TDDFT) both from the perspective of accuracy and of computational cost, complicating high-throughput virtual screening (HTVS). We instead leverag...

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Detalles Bibliográficos
Autores principales: Terrones, Gianmarco G., Duan, Chenru, Nandy, Aditya, Kulik, Heather J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2023
Materias:
Chemistry
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9906783/
https://www.ncbi.nlm.nih.gov/pubmed/36794185
http://dx.doi.org/10.1039/d2sc06150c

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9906783/
https://www.ncbi.nlm.nih.gov/pubmed/36794185
http://dx.doi.org/10.1039/d2sc06150c

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