PACMOF2 | Thang D. Pham

PACMOF2 provides fast, accurate machine-learning models for assigning partial atomic charges in metal–organic frameworks (MOFs) and other porous materials — a prerequisite for reliable gas-adsorption simulations. The models reproduce high-fidelity DDEC6 charges at a tiny fraction of the cost, and this release extends coverage to ionic MOFs with extra-framework ions, a class that previous charge-assignment methods handled poorly (Pham et al., 2024).

Stack: Python, scikit-learn / PyTorch, RASPA, DFT reference data.
Code: github.com/snurr-group/pacmof2

References

2024

Predicting Partial Atomic Charges in Metal–Organic Frameworks: An Extension to Ionic MOFs

Thang D. Pham, Faramarz Joodaki, Filip Formalik, and 1 more author

The Journal of Physical Chemistry C, 2024

DOI Bib HTML

@article{pham_predicting_2024,
  title = {Predicting Partial Atomic Charges in Metal--Organic Frameworks: An Extension to Ionic MOFs},
  author = {Pham, Thang D. and Joodaki, Faramarz and Formalik, Filip and Snurr, Randall Q.},
  journal = {The Journal of Physical Chemistry C},
  volume = {128},
  number = {40},
  pages = {17165--17174},
  year = {2024},
  publisher = {American Chemical Society},
  doi = {10.1021/acs.jpcc.4c04879},
}