聚合物的结构感知机器学习:用于预测统计集群属性的层次图形网络

Julian Kimmig1,2,3, Yannik Köster1,2, Timo Koswig1,2

  • 1Laboratory of Organic and Macromolecular Chemistry (IOMC), Friedrich Schiller University Jena, Jena, Germany.

概括

本研究介绍了聚合物科学的结构感知图形卷积网络 (GCN),通过考虑分子层次和质量分布来提高机器学习效率. 新的框架准确地预测了聚合物特性,例如玻璃过渡温度.

相关概念视频

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