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...
Հիմնական հեղինակներ: | Terrones, Gianmarco G, Duan, Chenru, Nandy, Aditya, Kulik, Heather J |
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Այլ հեղինակներ: | Massachusetts Institute of Technology. Department of Chemistry |
Ձևաչափ: | Հոդված |
Լեզու: | English |
Հրապարակվել է: |
Royal Society of Chemistry
2024
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Առցանց հասանելիություն: | https://hdl.handle.net/1721.1/156915 |
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