Deep learning of experimental electrochemistry for battery cathodes across diverse compositions

IF 38.6 1区 材料科学 Q1 CHEMISTRY, PHYSICAL Joule Pub Date : 2024-06-19 DOI:10.1016/j.joule.2024.03.010
Peichen Zhong , Bowen Deng , Tanjin He , Zhengyan Lun , Gerbrand Ceder
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Abstract

Artificial intelligence (AI) has emerged as a tool for discovering and optimizing novel battery materials. However, the adoption of AI in battery cathode representation and discovery is still limited due to the complexity of optimizing multiple performance properties and the scarcity of high-fidelity data. We present a machine learning model (DRXNet) for battery informatics and demonstrate the application in the discovery and optimization of disordered rocksalt (DRX) cathode materials. We have compiled the electrochemistry data of DRX cathodes over the past 5 years, resulting in a dataset of more than 19,000 discharge voltage profiles on diverse chemistries spanning 14 different metal species. Learning from this extensive dataset, our DRXNet model can capture critical features in the cycling curves of DRX cathodes under various conditions. Our approach offers a data-driven solution to facilitate the rapid identification of novel cathode materials, accelerating the development of next-generation batteries for carbon neutralization.

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对不同成分电池阴极的实验电化学进行深度学习
人工智能(AI)已成为发现和优化新型电池材料的工具。然而,由于优化多种性能特性的复杂性和高保真数据的稀缺性,人工智能在电池阴极表征和发现方面的应用仍然有限。我们介绍了一种用于电池信息学的机器学习模型(DRXNet),并演示了该模型在发现和优化无序岩盐(DRX)阴极材料中的应用。我们汇编了过去 5 年中 DRX 阴极的电化学数据,形成了一个包含 19,000 多条放电电压曲线的数据集,这些曲线涉及 14 种不同的金属。通过学习这个广泛的数据集,我们的 DRXNet 模型可以捕捉 DRX 阴极在各种条件下循环曲线的关键特征。我们的方法提供了一种数据驱动型解决方案,有助于快速识别新型阴极材料,从而加速下一代碳中和电池的开发。
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来源期刊
Joule
Joule Energy-General Energy
CiteScore
53.10
自引率
2.00%
发文量
198
期刊介绍: Joule is a sister journal to Cell that focuses on research, analysis, and ideas related to sustainable energy. It aims to address the global challenge of the need for more sustainable energy solutions. Joule is a forward-looking journal that bridges disciplines and scales of energy research. It connects researchers and analysts working on scientific, technical, economic, policy, and social challenges related to sustainable energy. The journal covers a wide range of energy research, from fundamental laboratory studies on energy conversion and storage to global-level analysis. Joule aims to highlight and amplify the implications, challenges, and opportunities of novel energy research for different groups in the field.
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