colabfit/GST_GAP_22_main

GST GAP 22主数据集是一个用于训练机器学习原子间势能模型的训练数据集，包含了在PBEsol功能下计算的准二元GeTe-Sb2Te3 (GST)化学成分的相变材料配置。该数据集被用于模拟在实际设备条件下的锗-锑-碲组成范围。The GST GAP 22 main dataset is a training dataset for a machine learning interatomic potential model, containing configurations of phase-change materials on the quasi-binary GeTe-Sb2Te3 (GST) line of chemical compositions calculated using the PBEsol functional. The dataset is used to simulate a range of germanium-antimony-tellurium compositions under realistic device conditions.