钙钛矿(结构)
计算机科学
人工智能
数据科学
能量(信号处理)
纳米技术
高效能源利用
材料科学
机器学习
工程类
电气工程
物理
化学工程
量子力学
作者
Jiechun Liang,Tingting Wu,Ziwei Wang,Yunduo Yu,Linfeng Hu,Huamei Li,Xiaohong Zhang,Xi Zhu,Yu Zhao
出处
期刊:Energy materials
[OAE Publishing Inc.]
日期:2022-01-01
卷期号:2 (3): 200016-200016
被引量:54
标识
DOI:10.20517/energymater.2022.14
摘要
Perovskites are promising materials applied in new energy devices, from solar cells to battery electrodes. Under traditional experimental conditions in laboratories, the performance improvement of new energy devices is slow and limited. Artificial intelligence (AI) has recently drawn much attention in material properties prediction and new functional materials exploration. With the advent of the AI era, the methods of studying perovskites have been upgraded, thereby benefiting the energy industry. In this review, we summarize the application of AI in perovskite discovery and synthesis and its positive influence on new energy research. First, we list the advantages of AI in perovskite research and the steps of AI application in perovskite discovery, including data availability, the selection of training algorithms, and the interpretation of results. Second, we introduce a new synthesis method with high efficiency in cloud labs and explain how this platform can assist perovskite discovery. We review the use of perovskites in energy applications and illustrate that the efficiency of energy production in these fields can be significantly boosted due to the use of AI in the development process. This review aims to provide the future application prospects of AI in perovskite research and new energy generation.
科研通智能强力驱动
Strongly Powered by AbleSci AI