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RESEARCH PAPER · Patterns · 2021

Capture the high-efficiency non-fullerene ternary organic solar cells formula by machine-learning-assisted energy-level alignment optimization

Tianyu Hao, Shifeng Leng, Yankang Yang, Wenkai Zhong, Ming Zhang, Lei Zhu, Jingnan Song, Jinqiu Xu, Guanqing Zhou, Yecheng Zou, Yongming Zhang, Feng Liu

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42 direct citing works

Capture the high-efficiency non-fullerene ternary organic solar cells formula by machine-learning-assisted energy-level alignment optimizationOriginalManipulating the Crystalline Morphology in the Nonfullerene Acceptor Mixture to Improve the Carrier Transport and Suppress the Energetic Disorder9Accelerated exploration of efficient ternary solar cells with PTB7:PC 71 BM:SMPV1 using machine-learning methods14Opportunities and challenges for machine learning to select combination of donor and acceptor materials for efficient organic solar cells25Spontaneous carrier generation and low recombination in high-efficiency non-fullerene solar cells65Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques184Performance Prediction and Experimental Optimization Assisted by Machine Learning for Organic Photovoltaics30The structure-performance correlation of bulk-heterojunction organic solar cells with multi-length-scale morphology17A study on sensitivity improvement of indirect-type X-ray detectors using a ternary-blend organic active layer1Active Discovery of Donor:Acceptor Combinations For Efficient Organic Solar Cells10Screening Efficient Tandem Organic Solar Cells with Machine Learning and Genetic Algorithms44Predicting power conversion efficiency of binary organic solar cells based on Y6 acceptor by machine learning50Interpretable Machine Learning Model for the Highly Accurate Prediction of Efficiency of Ternary Organic Solar Cells Based on Nonfullerene Acceptor using Effective Molecular Descriptors13Probing the Effect of Photovoltaic Material on Voc in Ternary Polymer Solar Cells with Non-Fullerene Acceptors by Machine Learning8Directed Message Passing Neural Network for Predicting Power Conversion Efficiency in Organic Solar Cells17Machine learning study of D:A1:A2 ternary organic solar cells17Providing a Photovoltaic Performance Enhancement Relationship from Binary to Ternary Polymer Solar Cells via Machine Learning2Extrapolative Machine Learning for Accurate Efficiency Prediction in Non‐Fullerene Ternary Organic Solar Cells: Leveraging Computable Molecular Descriptors in High‐Throughput Virtual Screening10Progress of organic photovoltaics towards 20% efficiency132Machine learning empowers efficient design of ternary organic solar cells with PM6 donor16Intrinsic Reactivity Index as Descriptor for Accurately Predicting Short-Circuit Current Density in Ternary Organic Solar Cells6Machine learning theory for acceptor molecular design of D:A1:A2 ternary organic solar cells3Strategies to overcome the efficiency-stability conundrum of organic solar cells7Artificial intelligence in the discovery and design of molecular semiconductors: a systematic review3Big data-driven optimization framework for solar cell design1

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  1. Manipulating the Crystalline Morphology in the Nonfullerene Acceptor Mixture to Improve the Carrier Transport and Suppress the Energetic Disorder

    Small Science · 2021-11-05

    Ming Zhang, Lei Zhu, Chaoqun Qiu, Tianyu Hao, Yufeng Jiang, Shifeng Leng, Jiajun Chen, Guanqing Zhou, Zichun Zhou, Yecheng Zou, Xuan Su, Zhiwen Shi, Haiming Zhu, Yongming Zhang, Thomas P. Russell, Xiaozhang Zhu, Feng Liu

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  2. Accelerated exploration of efficient ternary solar cells with PTB7:PC 71 BM:SMPV1 using machine-learning methods

    Physical Chemistry Chemical Physics · 2022-01-01

    Chaorong Guo, Zhennan Li, Kuo Wang, Xunchen Zhou, Di Huang, Jiaojiao Liang, Ling Zhao

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  3. Opportunities and challenges for machine learning to select combination of donor and acceptor materials for efficient organic solar cells

    Journal of Materials Chemistry C · 2022-01-01

    Prateek Malhotra, Kanupriya Khandelwal, Subhayan Biswas, Fang‐Chung Chen, Ganesh Datt Sharma

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  4. Spontaneous carrier generation and low recombination in high-efficiency non-fullerene solar cells

    Energy & Environmental Science · 2022-01-01

    Guanqing Zhou, Ming Zhang, Jinqiu Xu, Yankang Yang, Tianyu Hao, Lei Zhu, Libo Zhou, Haiming Zhu, Yecheng Zou, Gang Wei, Yongming Zhang, Feng Liu

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  5. Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques

    Energies · 2022-01-14

    Laith Abualigah, Raed Abu Zitar, Khaled Hatem Almotairi, Ahmad MohdAziz Hussein, Mohamed Abd Elaziz, Mohammad Reza Nikoo, Amir H. Gandomi

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  6. Performance Prediction and Experimental Optimization Assisted by Machine Learning for Organic Photovoltaics

    Advanced Intelligent Systems · 2022-03-19

    Zhi‐Wen Zhao, Yun Geng, Alessandro Troisi, Haibo Ma

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  7. The structure-performance correlation of bulk-heterojunction organic solar cells with multi-length-scale morphology

    Science China Chemistry · 2022-06-28

    Tianyu Hao, Wenkai Zhong, Shifeng Leng, Rui Zeng, Ming Zhang, Lei Zhu, Yankang Yang, Jingnan Song, Jinqiu Xu, Guanqing Zhou, Yecheng Zou, Yongming Zhang, Feng Liu

    Read original paper ↗ ·

  8. A study on sensitivity improvement of indirect-type X-ray detectors using a ternary-blend organic active layer

    Organic Electronics · 2022-10-01

    Jehoon Lee, Hailiang Liu, Jungwon Kang

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  9. Active Discovery of Donor:Acceptor Combinations For Efficient Organic Solar Cells

    ACS Applied Materials & Interfaces · 2022-12-02

    Prateek Malhotra, Juan C. Verduzco, Subhayan Biswas, Ganesh Datt Sharma

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  10. Screening Efficient Tandem Organic Solar Cells with Machine Learning and Genetic Algorithms

    The Journal of Physical Chemistry C · 2023-03-28

    Brianna L. Greenstein, Geoffrey Hutchison

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  11. Predicting power conversion efficiency of binary organic solar cells based on Y6 acceptor by machine learning

    Journal of Energy Chemistry · 2023-03-31

    Qiming Zhao, Yuqing Shan, Chongchen Xiang, Jinglun Wang, Yingping Zou, Guangjun Zhang, Wanqiang Liu

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  12. Interpretable Machine Learning Model for the Highly Accurate Prediction of Efficiency of Ternary Organic Solar Cells Based on Nonfullerene Acceptor using Effective Molecular Descriptors

    Solar RRL · 2023-05-26

    Min‐Hsuan Lee

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  13. Probing the Effect of Photovoltaic Material on Voc in Ternary Polymer Solar Cells with Non-Fullerene Acceptors by Machine Learning

    Polymers · 2023-07-05

    Di Huang, Zhennan Li, Kuo Wang, Haixin Zhou, Xiaojie Zhao, Xinyu Peng, Rui Zhang, Jipeng Wu, Jiaojiao Liang, Ling Zhao

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  14. Directed Message Passing Neural Network for Predicting Power Conversion Efficiency in Organic Solar Cells

    ACS Applied Materials & Interfaces · 2023-07-25

    Prateek Malhotra, Subhayan Biswas, Ganesh Datt Sharma

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  15. Machine learning study of D:A1:A2 ternary organic solar cells

    Organic Electronics · 2023-12-29

    Jinhong Li, Cai‐Rong Zhang, Meiling Zhang, Xiaomeng Liu, Ji-Jun Gong, Yuhong Chen, Zi‐Jiang Liu, Youzhi Wu, Hongshan Chen

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  16. Providing a Photovoltaic Performance Enhancement Relationship from Binary to Ternary Polymer Solar Cells via Machine Learning

    Polymers · 2024-05-24

    Jingyue Cao, Zheng Xu

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  17. Extrapolative Machine Learning for Accurate Efficiency Prediction in Non‐Fullerene Ternary Organic Solar Cells: Leveraging Computable Molecular Descriptors in High‐Throughput Virtual Screening

    Solar RRL · 2024-05-28

    Jian‐Ming Liao, Hui‐Hsu Gavin Tsai

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  18. Progress of organic photovoltaics towards 20% efficiency

    Nature Reviews Electrical Engineering · 2024-08-21

    Lei Zhu, Ming Zhang, Zichun Zhou, Wenkai Zhong, Tianyu Hao, Shengjie Xu, Rui Zeng, Jiaxing Zhuang, Xiaonan Xue, Jing Hao, Yongming Zhang, Feng Liu

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  19. Machine learning empowers efficient design of ternary organic solar cells with PM6 donor

    Journal of Energy Chemistry · 2024-09-07

    Kiran A. Nirmal, Tukaram Dattatray Dongale, Santosh Shashikant Sutar, Atul C. Khot, Tae Geun Kim

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  20. Intrinsic Reactivity Index as Descriptor for Accurately Predicting Short-Circuit Current Density in Ternary Organic Solar Cells

    ACS Applied Energy Materials · 2025-01-01

    Min‐Hsuan Lee, Yu‐Tang Hsiao, Chuang-Yi Liao, Yi‐Ming Chang

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  21. Machine learning theory for acceptor molecular design of D:A1:A2 ternary organic solar cells

    Physics Letters A · 2025-06-21

    Jinhong Li, Cai‐Rong Zhang, Ji-Jun Gong, Xiaomeng Liu, Zi‐Jiang Liu, Yuhong Chen, Youzhi Wu, Hongshan Chen

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  22. Strategies to overcome the efficiency-stability conundrum of organic solar cells

    Materials Science and Engineering R Reports · 2025-11-14

    Xianzhao Liu, Yu Guo, Yunjie Dou, Senji Li, Ziming Chen, Philip C. Y. Chow

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  23. Artificial intelligence in the discovery and design of molecular semiconductors: a systematic review

    Digital Discovery · 2026-01-01

    Malin Zollner, Yashar Moshfeghi, Tahereh Nematiaram

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  24. Big data-driven optimization framework for solar cell design

    Energy Conversion and Management · 2026-02-09

    Nur Amilya Zainul Asri, Mohammad Shaheer Akhtar, Seung Beop Lee

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