Machine Learning HPDC datasets

This dataset contains 1 000 industrial heats of high-pressure die-cast (HPDC) Al-Si-based alloys, compiled to support the accompanying CALPHAD-oriented manuscript on machine-learning-driven optimisation of hardness (HB) and electrical conductivity (%IACS). Each record couples the melt chemistry, key thermodynamic descriptors and measured properties, enabling supervised learning, feature-importance analysis and inverse alloy design.本数据集包含1000炉次高压压铸（high-pressure die-cast, HPDC）铝硅基合金的工业生产数据，为配套的面向相图计算（CALPHAD）的机器学习驱动的布氏硬度（HB）与导电率（%IACS）优化研究论文提供支撑。每条记录均整合了熔体成分、关键热力学表征参数与实测性能数据，可用于监督学习、特征重要性分析以及合金逆向设计相关研究。