结晶
钙钛矿(结构)
卤化物
溶剂
吞吐量
光伏系统
工艺工程
材料科学
制作
纳米技术
机器人
铅(地质)
化学工程
计算机科学
化学
无机化学
工程类
人工智能
有机化学
电气工程
病理
地质学
地貌学
替代医学
无线
电信
医学
作者
Ening Gu,Xiaofeng Tang,Stefan Langner,Patrick Duchstein,Yicheng Zhao,Ievgen Levchuk,Violetta Kalancha,Tobias Stubhan,Jens Hauch,Hans Joachim Egelhaaf,Dirk Zahn,Andres Osvet,Christoph J. Brabec
出处
期刊:Joule
[Elsevier]
日期:2020-07-14
卷期号:4 (8): 1806-1822
被引量:86
标识
DOI:10.1016/j.joule.2020.06.013
摘要
Solution-based processing of photovoltaic materials has important advantages, including lower overall costs and easier upscaling of fabrication, where the solvents play an essential role. Antisolvent crystallization technique is often applied to achieve high-quality perovskite materials. However, the basic chemistry of the solvent-antisolvent crystallization is still not well understood. Besides, common antisolvents are toxic, and their number is limited. In this work, a novel robot-based method was used to screen the efficient antisolvents for different solvent-perovskite systems. 336 combinations of perovskite-solvent-antisolvent could be prepared and characterized by the integrated robotic platform in 2 days. In addition, we provided a detailed working mechanism of the solvent-antisolvent crystallization approach. Furthermore, hundreds of potential antisolvents were proposed based on high-throughput screening and simulation. Verification tests match well with theory, and all reported antisolvents used for photovoltaic device optimizations are within our predicted range of the Hansen space, indicating that the predictions are reliable.
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