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<p>The rapid rise of generative artificial intelligence is reshaping materials discovery by offering new ways to propose crystal structures and, in some cases, even predict desired properties. This review provides a comprehensive survey of recent advancements in generative models specifically for inorganic crystalline materials. We outline architectures, representations, conditioning mechanisms, data sources, metrics, and applications, and organize existing models into a unified taxonomy.</p>

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Generative AI for crystal structures: a review

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月6日

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  • Pierre-Paul De Breuck,
  • Hai-Chen Wang,
  • Gian-Marco Rignanese,
  • Silvana Botti,
  • Miguel A. L. Marques

摘要

The rapid rise of generative artificial intelligence is reshaping materials discovery by offering new ways to propose crystal structures and, in some cases, even predict desired properties. This review provides a comprehensive survey of recent advancements in generative models specifically for inorganic crystalline materials. We outline architectures, representations, conditioning mechanisms, data sources, metrics, and applications, and organize existing models into a unified taxonomy.