Frontier molecular orbital weighted model based networks for revealing organic delayed fluorescence efficiency

Zhaoming He; Hai Bi; Baoyan Liang; Zhiqiang Li; Heming Zhang; Yue Wang

doi:10.1038/s41377-024-01713-w

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Frontier molecular orbital weighted model based networks for revealing organic delayed fluorescence efficiency

Original Articles

- Frontier molecular orbital weighted model based networks for revealing organic delayed fluorescence efficiency
- Light: Science & Applications Vol. 14, Issue 3, Pages: 800-810(2025)
- Affiliations：
  
  1.Jihua Laboratory, Foshan, Guangdong Province, PR China
  2.State Key Laboratory of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun, PR China
  3.Jihua Hengye Electronic Materials CO. LTD, Foshan, Guangdong Province, PR China
- Author bio：
  
  Hai Bi (bihai@jihualab.com)
  Yue Wang (yuewang@jlu.edu.cn)
- Funds：
- DOI：10.1038/s41377-024-01713-w
  CLC：
- Received：16 June 2024，
  
  Revised：06 November 2024，
  
  Accepted：2024-12-03，
  
  Published Online：10 February 2025，
  
  Published：31 March 2025
- Accepted：
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He, Z. M. et al. Frontier molecular orbital weighted model based networks for revealing organic delayed fluorescence efficiency. Light: Science & Applications, 14, 800-810 (2025).
DOI：

He, Z. M. et al. Frontier molecular orbital weighted model based networks for revealing organic delayed fluorescence efficiency. Light: Science & Applications, 14, 800-810 (2025). DOI： 10.1038/s41377-024-01713-w.

摘要

Abstract

Free of noble-metal and high in unit internal quantum efficiency of electroluminescence

organic molecules with thermally activated delayed fluorescence (TADF) features pose the potential to substitute metal-based phosphorescence materials and serve as the new-generation emitters for the mass production of organic light emitting diodes (OLEDs) display. Predicting the function of TADF emitters beyond classic chemical synthesis and material characterization experiments remains a great challenge. The advances in deep learning (DL) based artificial intelligence (AI) offer an exciting opportunity for screening high-performance TADF materials through efficiency evaluation. However

data-driven material screening approaches with the capacity to access the excited state properties of TADF emitters remain extremely difficult and largely unaddressed. Inspired by the fundamental principle that the excited state properties of TADF molecules are strongly dependent on their D-A geometric and electronic structures

we developed the Electronic Structure-Infused Network (ESIN) for TADF emitter screening. Designed with capacities of accurate prediction of the photoluminescence quantum yields (PLQYs) of TADF molecules based on elemental molecular geometry and orbital information and integrated with frontier molecular orbitals (FMOs) weight-based representation and modeling features

ESIN is a promising interpretable tool for emission efficiency evaluation and molecular design of TADF emitters.

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