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A general protocol for phosphorescent platinum(II) complexes: generation, high throughput virtual screening and highly accurate predictions

Shuai Wang, ChiYung Yam, LiHong Hu, Faan-Fung Hung, Shuguang Chen, Chi-Ming Che, GuanHua Chen

Shuai Wang, ChiYung Yam, LiHong Hu, Faan-Fung Hung, Shuguang Chen, Chi-Ming Che, GuanHua Chen. A general protocol for phosphorescent platinum(II) complexes: generation, high throughput virtual screening and highly accurate predictions[J]. Materials Futures, 2025, 4(2): 025601. DOI: 10.1088/2752-5724/adb320
引用本文: Shuai Wang, ChiYung Yam, LiHong Hu, Faan-Fung Hung, Shuguang Chen, Chi-Ming Che, GuanHua Chen. A general protocol for phosphorescent platinum(II) complexes: generation, high throughput virtual screening and highly accurate predictions[J]. Materials Futures, 2025, 4(2): 025601. DOI: 10.1088/2752-5724/adb320
Shuai Wang, ChiYung Yam, LiHong Hu, Faan-Fung Hung, Shuguang Chen, Chi-Ming Che, GuanHua Chen. A general protocol for phosphorescent platinum(II) complexes: generation, high throughput virtual screening and highly accurate predictions[J]. Materials Futures, 2025, 4(2): 025601. DOI: 10.1088/2752-5724/adb320
Citation: Shuai Wang, ChiYung Yam, LiHong Hu, Faan-Fung Hung, Shuguang Chen, Chi-Ming Che, GuanHua Chen. A general protocol for phosphorescent platinum(II) complexes: generation, high throughput virtual screening and highly accurate predictions[J]. Materials Futures, 2025, 4(2): 025601. DOI: 10.1088/2752-5724/adb320

A general protocol for phosphorescent platinum(II) complexes: generation, high throughput virtual screening and highly accurate predictions

基金项目: 

This work is financially supported by the RGC General Research Fund under Grant No. 17309620, Hong Kong Quantum AI Lab Limited and Air @ InnoHK of Hong Kong Government. C Y Y acknowledges the support from National Natural Science Foundation of China (Grant Nos. 22073007 and 22473022) and Shenzhen Basic Research Key Project Fund (Grant No. JCYJ20220818103200001). L H H thanks financial support from National Natural Science Foundation of China (No. 22273010) and Department of Science and Technology of Jilin Province (20210402075GH). C-M C and F-F H acknowledge Guangdong Major Project of Basic and Applied Basic Research (Grant No. 2019B030302009).

A general protocol for phosphorescent platinum(II) complexes: generation, high throughput virtual screening and highly accurate predictions

Funds: 

This work is financially supported by the RGC General Research Fund under Grant No. 17309620, Hong Kong Quantum AI Lab Limited and Air @ InnoHK of Hong Kong Government. C Y Y acknowledges the support from National Natural Science Foundation of China (Grant Nos. 22073007 and 22473022) and Shenzhen Basic Research Key Project Fund (Grant No. JCYJ20220818103200001). L H H thanks financial support from National Natural Science Foundation of China (No. 22273010) and Department of Science and Technology of Jilin Province (20210402075GH). C-M C and F-F H acknowledge Guangdong Major Project of Basic and Applied Basic Research (Grant No. 2019B030302009).

More Information
    Corresponding author:

    ChiYung Yam,E-mail:yamcy@uestc.edu.cn

    Chi-Ming Che,E-mail:cmche@hku.hk

    GuanHua Chen,E-mail:ghc@everest.hku.hk

  • 摘要: The utilization of phosphorescent metal complexes as emissive dopants for organic light-emitting diodes (OLEDs) has been the subject of intense research. Cyclometalated Pt(II) complexes are particularly popular triplet emitters due to their color-tunable emissions. To make them viable for practical applications as OLED emitters, it is essential to develop Pt(II) complexes with high radiative decay rate constants (kr) and photoluminescence quantum yields (PLQY). To this end, an efficient and accurate prediction tool is highly desirable. In this work, we propose a general yet powerful protocol achieving metal complex generation, high throughput virtual screening (HTVS), and fast predictions with high accuracy. More than 3600 potential structures are generated in a synthesis-friendly manner. Moreover, three HTVS-machine learning (ML) models are established using different algorithms with carefully designed features that are suitable for metal complexes. Specifically, 30 potential candidates are filtered out by HTVS-ML models with a three-tier screening rule and put into accurate predictions with experimental calibration Δ-learning method. The highly accurate prediction approach further reduces the stress of experiments and inspires greater confidence in identifying the most promising complexes as excellent emitters. As a result, 12 promising complexes (kr > 105 s-1 and PLQY > 0.6) with the same superior core structures are confirmed from over 3600 Pt-complexes. Experiments revealed that two very close complexes have excellent emission properties and are consistent with the prediction results, providing strong evidence for the efficacy of the proposed protocol. We expect this protocol will become a valuable tool, expediting the rational design and rapid development of novel OLED materials with desired properties.
    Abstract: The utilization of phosphorescent metal complexes as emissive dopants for organic light-emitting diodes (OLEDs) has been the subject of intense research. Cyclometalated Pt(II) complexes are particularly popular triplet emitters due to their color-tunable emissions. To make them viable for practical applications as OLED emitters, it is essential to develop Pt(II) complexes with high radiative decay rate constants (kr) and photoluminescence quantum yields (PLQY). To this end, an efficient and accurate prediction tool is highly desirable. In this work, we propose a general yet powerful protocol achieving metal complex generation, high throughput virtual screening (HTVS), and fast predictions with high accuracy. More than 3600 potential structures are generated in a synthesis-friendly manner. Moreover, three HTVS-machine learning (ML) models are established using different algorithms with carefully designed features that are suitable for metal complexes. Specifically, 30 potential candidates are filtered out by HTVS-ML models with a three-tier screening rule and put into accurate predictions with experimental calibration Δ-learning method. The highly accurate prediction approach further reduces the stress of experiments and inspires greater confidence in identifying the most promising complexes as excellent emitters. As a result, 12 promising complexes (kr > 105 s-1 and PLQY > 0.6) with the same superior core structures are confirmed from over 3600 Pt-complexes. Experiments revealed that two very close complexes have excellent emission properties and are consistent with the prediction results, providing strong evidence for the efficacy of the proposed protocol. We expect this protocol will become a valuable tool, expediting the rational design and rapid development of novel OLED materials with desired properties.
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出版历程
  • 收稿日期:  2024-09-29
  • 修回日期:  2024-12-25
  • 录用日期:  2025-01-15
  • 网络出版日期:  2025-02-06
  • 发布日期:  2025-04-03

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