DFTpy
Python-based orbital-free DFT code for large-scale materials simulations. Million-atom systems are approachable via highly efficient parallelization and algorithms (e.g., PME and novel OF-DFT solvers).
What can you do with DFTpy
Run orbital-free DFT (OF-DFT) simulations using a plane-wave expansion of the electron density
Prototype new OF-DFT functionals, solvers, and workflows quickly in pure Python
Drive very large systems (million-atom scale approaches with the right kernels and decomposition)
Use and test Local Pseudopotentials (LPPs) compatible with DFTpy
Explore time-dependent OF-DFT and spin-unrestricted options
Integrate with the broader Q-MS software set and Python’s scientific ecosystem
DFTpy developers
Feel free to contact the developers:
On-line
DFTpy is actively developed by the following groups:
Learn about it
External site
Official site: dftpy.rutgers.edu
How do I find out more about DFTpy?
or send an email to dftpy_forum@email.rutgers.edu
Publications
Shao, X., Jiang, K., Mi, W., Genova, A., & Pavanello, M. (2021). DFTpy: An efficient and object‐oriented platform for orbital‐free DFT simulations. Wiley Interdisciplinary Reviews: Computational Molecular Science, 11(1), e1482. (https://doi.org/10.1002/wcms.1482)
Jiang, K., & Pavanello, M. (2021). Time-dependent orbital-free density functional theory: Background and Pauli kernel approximations. Physical Review B, 103(24), 245102. (https://doi.org/10.1103/PhysRevB.103.245102)
Jiang, K., Shao, X., & Pavanello, M. (2021). Nonlocal and nonadiabatic Pauli potential for time-dependent orbital-free density functional theory. Physical Review B, 104, 235110. (https://doi.org/10.1103/PhysRevB.104.235110)
Shao, X., Mi, W., & Pavanello, M. (2021). Efficient DFT Solver for Nanoscale Simulations and Beyond. The Journal of Physical Chemistry Letters, 12(17), 4134-4139. (https://doi.org/10.1021/acs.jpclett.1c00716)
Shao, X., Jiang, K., Mi, W., Genova, A., & Pavanello, M. (2021). DFTpy: An efficient and object-oriented platform for orbital-free DFT simulations. Wiley Interdisciplinary Reviews: Computational Molecular Science, 11(1), e1482. (https://doi.org/10.1002/wcms.1482)
