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The previous chapters of this book explored the integration of machine learning frameworks with the quasi-static and dynamic characterization of nanomaterials, such as graphene and high-entropy alloys (specifically from Chaps. 5 to 9 ). The development of these predictive frameworks enables large-scale characterization of material systems and subsequently leads to virtual screening.

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Materials Informatics

  • 章节

  • 发表日期：

    2025年

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  • Kritesh Kumar Gupta,
  • Sudip Dey,
  • Tanmoy Mukhopadhyay

摘要

The previous chapters of this book explored the integration of machine learning frameworks with the quasi-static and dynamic characterization of nanomaterials, such as graphene and high-entropy alloys (specifically from Chaps. 5 to 9 ). The development of these predictive frameworks enables large-scale characterization of material systems and subsequently leads to virtual screening.