Training Data: Assessing a structure agnostic machine learning framework with experimental screening of magnetic materials
收藏DataCite Commons2025-12-15 更新2026-02-09 收录
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https://figshare.com/articles/dataset/Training_Data_Assessing_a_structure_agnostic_machine_learning_framework_with_experimental_screening_of_magnetic_materials/30885887/1
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资源简介：
Dataset in CSV format supporting this article in Physical Review Materials: https://doi.org/10.1103/kjrr-ypd9The set consists of 3826 rows, each corresponding to a crystalline inorganic material. Each row contains the material's composition, identifier in the Magnetic Materials Database (https://doi.org/10.1103/PhysRevMaterials.4.114408), DFT-computed saturation polarization value, and fold identifier used during leave-one-cluster-out cross validation in the present work.
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figshare
创建时间：
2025-12-15
