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一个新的机器学习基准,应用于粉末X射线衍射

Sergio Rincón^1,2, Gabriel González², Mario A Macías¹

¹Crystallography and Chemistry of Materials, CrisQuimMat, Department of Chemistry, Universidad de los Andes, Bogotá, 111711, Colombia.

Scientific data

|July 10, 2025

概括

研究人员开发了模拟粉末X射线衍射开放数据库 (SIMPOD),这是一个用于预测晶体参数的公共数据集. 这种多样化的数据集有助于机器学习模型的开发,用于分析粉末X射线衍射数据.

科学领域:

晶体学晶体学是指结晶学.
材料科学材料科学材料科学
机器学习机器学习

背景情况:

从粉末X射线衍射 (PXRD) 进行晶体参数预测是机器学习越来越感兴趣的领域.
现有的PXRD数据集通常是私有的,缺乏结构多样性,阻碍了模型开发.

研究的目的:

从PXRD.引入一个新的,公开的,结构多样化的数据集,用于PXRD.的晶体参数预测.
促进用于PXRD数据分析的机器学习和计算机视觉模型的开发.

主要方法:

从晶体学开放数据库 (COD) 中为467,861个晶体结构生成模拟粉末X射线衍射 (PXRD) 模式.
创建了单维衍射图和二维辐射图像.

主要成果:

建立了模拟粉末X射线衍射开放数据库 (SIMPOD),这是一个大规模的公共基准数据集.
SIMPOD包含467,861个晶体结构及其相应的模拟PXRD模式.

结论:

在PXRD分析中,SIMPOD解决了对公共和多样化的数据集的需求.
该数据集预计将加速使用PXRD进行材料分析的先进模型的开发.

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