AI-guided design of efficient perovskite solar cells operationally stable at 100°C

• 成果类型: Article
• 署名作者: Guo, Jiahao; Li, Bowei; Zhang, Zeyu; Liu, Fang; Li, Congyi; Wang, Yao; Wang, Shaowei; Chang, Guoqing; Fan, Junyi; Zhang, Taiyang; Lou, Yongbing; Wang, Shengnan; Cao, Xingzhong; Chen, Yuetian; Wang, Yanming; Miao, Yanfeng; Zhao, Yixin
• 署名单位: Shanghai Jiao Tong University; Shanghai Jiao Tong University; Shanghai Jiao Tong University; Shanghai Institute of Technology; Southeast University - China; Chinese Academy of Sciences; Nanjing Institute of Geology & Paleontology, CAS; Institute of High Energy Physics, CAS
• 刊物名称: SCIENCE
• ISSN/ISSBN: 0036-8075; 1095-9203
• DOI: 10.1126/science.aef1620
• 发表日期: 2026-05-14
• 页码: 724-728
• 关键词: semiconductors

摘要

Operationally stable perovskite solar cells (PSCs) have been sought after and debated since first being demonstrated. Here, we report a four-agent collaborative artificial intelligence (AI) to guide rational design of light absorbers, ultraviolet-resistant hole transport materials, and robust heterointerfaces for stable perovskite photovoltaics. Validated through thermodynamically driven single-crystal growth and thin-film experimental characterizations, the multiagent framework identified a highly stable formamidinium-cesium lead iodide perovskite, FA(0.92)Cs(0.08)PbI(3). AI-driven insights further enabled the design of a customized hole transport molecule, (4 '-(3,6-dimethoxy-9H-carbazol-9-yl)-[1,1 '-biphenyl]-4-yl)phosphonic acid, with superior ultraviolet resilience, alongside dual-side metal oxide layer incorporation into the device configuration. The designed PSC can retain 97% of initial efficiency after 1000 hours of continuous operation at 100 degrees C. This success demonstrates an accessible and promising full-chain AI route to accelerate the application of PSCs.