钙钛矿(结构)
材料科学
紫外线
碘化物
氧化物
合理设计
光电子学
纳米技术
图层(电子)
金属
计算机科学
化学工程
传输层
多孔性
紫外线
卤化物
发光二极管
作者
Jiahao Guo,B R Li,Zeyu Zhang,F Liu,C. Li,Yao Wang,Shaowei Wang,Guoqing Chang,Junyi Fan,Taiyang Zhang,Yongbing Lou,Shengnan Wang,Xingzhong Cao,Yuetian Chen,Yanming Wang,Yanfeng Miao,Y ZHAO
出处
期刊:Science
[American Association for the Advancement of Science]
日期:2026-05-14
卷期号:392 (6799): 724-728
标识
DOI:10.1126/science.aef1620
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°C. This success demonstrates an accessible and promising full-chain AI route to accelerate the application of PSCs.
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