• Corpus ID: 239885685

Calibrating DFT formation enthalpy calculations by multi-fidelity machine learning

@inproceedings{Gong2021CalibratingDF,
  title={Calibrating DFT formation enthalpy calculations by multi-fidelity machine learning},
  author={Sheng Gong and Shuo Wang and Tian Xie and Woo Hyun Chae and Runze Liu and Jeffrey C. Grossman},
  year={2021}
}
Machine learning materials properties measured by experiments is valuable yet difficult due to the limited amount of experimental data. In this work, we use a multi-fidelity random forest model to learn the experimental formation enthalpy of materials with prediction accuracy higher than the empirically corrected PBE functional (PBEfe) and meta-GGA functional (SCAN), and it outperforms the hotly studied deep neural-network based representation learning and transfer learning. We then use the… 

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