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<p>Multi-resonance thermally activated delayed fluorescence (MR-TADF) materials are leading candidates for next-generation OLEDs, yet their discovery has remained slow due to intuition-driven design and limited scalable strategies for broad chemical spaces. Here, we report a scalable integrated framework that combines in silico exploration via combinatorial tree search with experimental validation, enabling end-to-end discovery of MR-TADF emitter cores. Using this strategy, we generated an unprecedented chemical library of 21.8 million candidates, overcoming data limitations and enabling systematic molecular exploration. Screening via TD-DFT identified 140 deep-blue MR-TADF candidates, among which the top 10—selected using a figure of merit—included several state-of-the-art emitters. Notably, the most promising unreported molecule was experimentally validated, yielding narrowband emission (FWHM 14 nm) and a high external quantum efficiency of 35%. This work demonstrates how large-scale computational design can accelerate the discovery of high-performance materials and establish a scalable pathway for data-driven molecular development.</p>

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Scalable integrated framework for discovering high-performance MR-TADF emitters via combinatorial tree search

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月6日

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  • Yongkyu Lee,
  • Uisung Lee,
  • Jihoon Kang,
  • Jangho Moon,
  • Jonggeol Na,
  • Jun Yeob Lee,
  • Won Bo Lee

摘要

Multi-resonance thermally activated delayed fluorescence (MR-TADF) materials are leading candidates for next-generation OLEDs, yet their discovery has remained slow due to intuition-driven design and limited scalable strategies for broad chemical spaces. Here, we report a scalable integrated framework that combines in silico exploration via combinatorial tree search with experimental validation, enabling end-to-end discovery of MR-TADF emitter cores. Using this strategy, we generated an unprecedented chemical library of 21.8 million candidates, overcoming data limitations and enabling systematic molecular exploration. Screening via TD-DFT identified 140 deep-blue MR-TADF candidates, among which the top 10—selected using a figure of merit—included several state-of-the-art emitters. Notably, the most promising unreported molecule was experimentally validated, yielding narrowband emission (FWHM 14 nm) and a high external quantum efficiency of 35%. This work demonstrates how large-scale computational design can accelerate the discovery of high-performance materials and establish a scalable pathway for data-driven molecular development.