Chu Wang, Lin Liu, Wei Sun, Juanjuan Wang, Qing-Kai Li, Kai Feng, Bin Liao, Wei-Hai Fang, Xuebo Chen
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Designing Ir(III) complex-based photofunctional materials for OLEDs and photocatalysis presents significant challenges. In article 2402317, Bin Liao, Xuebo Chen, and co-workers propose a three-step, data-driven workflow that leverages machine learning, time-dependent density functional theory (TDDFT), and complete active space perturbation theory (CASPT2) coupled with complete active space self-consistent field (CASSCF) methods. By incorporating critical excited-state descriptors, a promising uracil-based Ir(III) complex is identified from the self-constructed database.
期刊介绍：
Advanced Optical Materials, part of the esteemed Advanced portfolio, is a unique materials science journal concentrating on all facets of light-matter interactions. For over a decade, it has been the preferred optical materials journal for significant discoveries in photonics, plasmonics, metamaterials, and more. The Advanced portfolio from Wiley is a collection of globally respected, high-impact journals that disseminate the best science from established and emerging researchers, aiding them in fulfilling their mission and amplifying the reach of their scientific discoveries.
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