Trained Potentials for Article "Computationally Efficient Machine-Learned Model for GST Phase Change Materials via Direct and Indirect Learning"

We provide 8 files here to get started using our trained potentials:

1) *.yaml files for each trained potential. These are the outputs of the PACE training process.

2) *.yace files for each trained potential. These are read by LAMMPS to use the trained potential. They can be obtained from the *.yaml files using the command line command: "pace_yaml2yace *.yaml".

3) GST_config.data   --   a starting configuration of GST to be read by LAMMPS. This configuration contains 504 atoms at density 5.85 g/cm^3.

4) sample.inp   --   a sample LAMMPS input file using the trained potentials. This currently uses "ACE-Indir2.yace" to run the starting configuration "GST_config.data" for 10 ps at 1200 K. When run, it outputs a log file "test.log" and a dump file "test.dump". The choice of trained potential can be changed in the "pair_coeff" section.

我们提供以下8个文件，以便您使用训练得到的原子间势函数开展相关工作：
1) 适配各训练势函数的*.yaml格式文件，此类文件为PACE训练流程的输出产物。
2) 适配各训练势函数的*.yace格式文件，此类文件可被LAMMPS读取以调用训练势函数。您可通过命令行指令"pace_yaml2yace *.yaml"从*.yaml格式文件生成此类文件。
3) GST_config.data：供LAMMPS读取的GST初始构型文件。该构型包含504个原子，密度为5.85 g/cm³。
4) sample.inp：使用训练势函数的LAMMPS示例输入文件。当前该文件调用"ACE-Indir2.yace"，对"GST_config.data"初始构型在1200 K下运行10 ps的模拟。运行后将输出日志文件test.log与轨迹dump文件test.dump。可通过修改pair_coeff段更换所使用的训练势函数。