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...
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Royal Society of Chemistry
2024
|
| Online Access: | https://hdl.handle.net/1721.1/156915 |