What features are used to train the model? Do we need to add extra features?


I have a question about the input features used in ICET.

When we are building the training models, according to the example on ICET mannual, we basically just use lattice structures as input features, and mixing energy as output to train the model. I’m not sure if this is enough, since in many of the papers, people add hundreds of features, like atomic information, physical properties of the elementary substance, etc.

Do you think we need to add extra features? And if so, how can we achieve this in ICET? (Is it adding them to the properties dictionary in StructureContainer?)

Thank you so much.