Demo: Reproduce the experimental results of the paper

You can train DeepH models using the existing dataset to reproduce the results of this paper.

Firstly, download the processed dataset for graphene (graphene_dataset.zip), MoS₂ (MoS2_dataset.zip), twisted bilayer graphene (TBG_dataset.zip) or twisted bilayer bismuthene (TBB_dataset.zip). Uncompress the ZIP file.

Secondly, edit corresponding config files in the DeepH-pack/ini/. raw_dir should be set to the path of the downloaded dataset. graph_dir and save_dir should be set to the path to save your graph file and results file during the training. For grahene, twisted bilayer graphene and twisted bilayer bismuthene, a single MPNN model is used for each dataset. For MoS₂, four MPNN models are used. Run

deeph-train --config ${config_path}

with ${config_path} replaced by the path of config file for training.

After completing the training, you can find the trained model in save_dir, which can be used to make prediction on new structures by run

deeph-inference --config ${inference_config_path}

with ${inference_config_path} replaced by the path of config file for inference. Please note that the DFT results in this dataset were calculated using OpenMX. This means that if you want to use a model trained on this dataset to calculate properties, you need to use the overlap calculated using OpenMX. The orbital information required for overlap calculations can be found in the paper.