通过人工智能加速钙钛矿材料的发现和相关能源的应用

Jiechun Liang, Tingting Wu2, Zi Wang, Y. Yu, Linfeng Hu, Huamei Li, Xiaohong Zhang, Xi Zhu, Yu Zhao
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引用次数: 12

摘要

钙钛矿是一种很有前途的材料,应用于新能源设备,从太阳能电池到电池电极。在传统的实验室实验条件下,新能源装置的性能提升缓慢且有限。近年来,人工智能(AI)在材料性能预测和新功能材料探索方面受到了广泛关注。随着人工智能时代的到来,钙钛矿的研究方法得到了升级,从而使能源行业受益。本文综述了人工智能在钙钛矿发现与合成中的应用及其对新能源研究的积极影响。首先,我们列出了人工智能在钙钛矿研究中的优势,以及人工智能在钙钛矿发现中的应用步骤,包括数据可用性、训练算法的选择和结果的解释。其次,我们在云实验室中介绍了一种新的高效合成方法,并解释了该平台如何帮助钙钛矿的发现。我们回顾了钙钛矿在能源应用中的使用,并说明由于在开发过程中使用人工智能,这些领域的能源生产效率可以显着提高。本文综述了人工智能在钙钛矿研究和新能源生产中的应用前景。
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Accelerating perovskite materials discovery and correlated energy applications through artificial intelligence
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.
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