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Wen et al. J. Mater. Inf. 2025, 5, 30                                        Journal of
               DOI: 10.20517/jmi.2024.102
                                                                              Materials Informatics




               Research Article                                                              Open Access



               Accelerated discovery of high-performance small-
               molecule hole transport materials via molecular

               splicing, high-throughput screening, and machine
               learning


                                                                                  4
                                                                                                    2
                                                                                         2
                                                                    1
                                                        2,*
               Jiansen Wen 1,2,# , Shuwen Yang 1,3,4,# , Linqin Jiang , Yudong Shi , Zhihan Huang , Ping Li , Hao Xiong , Ze
                                     4
                              4
                 4
               Yu , Xushan Zhao , Bo Xu , Bo Wu 1,3,* , Baisheng Sa 1,*  , Yu Qiu 2
               1
                Multiscale Computational Materials Facility & Materials Genome Institute, School of Materials Science and Engineering, Fuzhou
               University, Fuzhou 350100, Fujian, China.
               2
                Key Laboratory of Green Perovskites Application of Fujian Province Universities, Fujian Jiangxia University, Fuzhou 350100,
               Fujian, China.
               3
                Materials Design and Manufacture Simulation Facility, School of Advanced Manufacturing, Fuzhou University, Jinjiang 362200,
               Fujian, China.
               4
                Fujian Science and Technology Innovation Laboratory for Energy Devices (21C-Lab), Contemporary Amperex Technology Co.,
               Limited (CATL), Ningde 352100, Fujian, China.
               #
                Authors contributed equally.
               * Correspondence to: Prof. Linqin Jiang, Key Laboratory of Green Perovskites Application of Fujian Province Universities, Fujian
               Jiangxia University, No. 2 Xiyuangong Road, Fuzhou 350100, Fujian, China, E-mail: linqinjiang@fjjxu.edu.cn; Prof. Bo Wu, Prof.
               Baisheng Sa, Multiscale Computational Materials Facility & Materials Genome Institute, School of Materials Science and
               Engineering, Fuzhou University, No. 2 Wulongjiang Avenue, Fuzhou 350100, Fujian, China, E-mail: wubo@fzu.edu.cn;
               bssa@fzu.edu.cn
               How to cite this article: Wen, J.; Yang, S.; Jiang, L.; Shi, Y.; Huang, Z.; Li, P.; Xiong, H.; Yu, Z.; Zhao, X.; Xu, B.; Wu, B.; Sa, B.; Qiu, Y.
               Accelerated discovery of high-performance small-molecule hole transport materials via molecular splicing, high-throughput
               screening, and machine learning. J. Mater. Inf. 2025, 5, 30. https://dx.doi.org/10.20517/jmi.2024.102
               Received: 30 Dec 2024  First Decision: 6 Feb 2025  Revised: 25 Mar 2025  Accepted: 2 Apr 2025  Published: 15 Apr 2025
               Academic Editor: Sergei Manzhos  Copy Editor: Pei-Yun Wang  Production Editor: Pei-Yun Wang

               Abstract
               As the most representative and widely utilized hole transport material (HTM), spiro-OMeTAD encounters
               challenges including limited hole mobility, high production costs, and demanding synthesis conditions. These
               issues have a notable impact on the overall performance of perovskite solar cells (PSCs) based on spiro-OMeTAD
               and hinder its large-scale commercial application. Consequently, there exists a strong demand for high-throughput
               computational design of novel small-molecule HTMs (SM-HTMs) that are cost-effective, easy to synthesize, and
               offer excellent performance. In this study, a systematic and iterative design and development process for SM-




                           © The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0
                           International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing,
                           adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as
               long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and
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