遇见数据集

Dataset - SciVisContest - Materials Discovery Challenge - version 2025

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Zenodo2025-04-10 更新2026-05-26 收录
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This the updated version of the dataset that is made available for the SciVisContest Materials Discovery Challenge. The data provided for this challenge was generated for the specific use case of developing a new Al-based alloy suitable for additive manufacturing by blending different available aluminum metal scrap such as automotive Al-Si piston alloys and other alloys from different sectors. Different alloy designs were initially generated based on mixing ratios between available scrap alloys. The CALPHAD method was used to perform equilibrium and non-equilibrium calculations to predict relevant thermo-physical and mechanical variables such as the content of volatile elements like Mg and Zn, phase formation and their fractions, solidification intervals, thermo-physical parameters, yield strength and hot crack sensitivity for each alloy composition.

提供机构:
Zenodo
创建时间:
2024-11-14
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