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<p>Li-ion and Na-ion battery materials have experienced rapid growth over the past decades and have become emblematic of the clean energy industry. Driven by advances in computational methods and data-driven research, this review provides an overview of key developments in physical modeling, data mining, and machine learning. In particular, it highlights how to understand the complex interplay of various types of disorder, accurately predict ionic conductivity, and develop specialized databases and machine learning frameworks.</p> Graphical abstract <p></p>

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Specialized modeling, database, and AI for Li-ion and Na-ion battery materials

  • 期刊论文

  • 发表日期：

    2025年9月5日

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  • Benjamin Cahill,
  • Lin Wang,
  • Bin Ouyang

摘要

Li-ion and Na-ion battery materials have experienced rapid growth over the past decades and have become emblematic of the clean energy industry. Driven by advances in computational methods and data-driven research, this review provides an overview of key developments in physical modeling, data mining, and machine learning. In particular, it highlights how to understand the complex interplay of various types of disorder, accurately predict ionic conductivity, and develop specialized databases and machine learning frameworks.

Graphical abstract