Heat capacity predictor for porous materials
For installation follow this instructions:
$ git clone https://github.com/seyedmohamadmoosavi/cp_app.git
$ cd tools-cp-porousmat
$ pip install -e .
We rely on:
- xgboost and sklearn for machine learning
- phonopy for phonon calculations and processing
- ase, pymatgen, and matminer for featurisation
See the jupyter notebooks in the examples folder.
- The ACT PrISMa Project and ACT programme Accelerating CCS Technologies
- Swiss National Science Foundation (SNSF)
- European Commission
Please consider citing our work:
- Moosavi, S.M., Novotny, B.Á., Ongari, D. et al. A data-science approach to predict the heat capacity of nanoporous materials. Nat. Mater. 21, 1419–1425 (2022). https://doi.org/10.1038/s41563-022-01374-3