The density-functional toolkit, or short DFTK is a library of Julia routines for experimentation with plane-wave-based density-functional theory (DFT), as implemented in much larger production codes such as Abinit, Quantum Espresso and VASP. The main aim at the moment is to provide a platform to facilitate numerical analysis of algorithms and techniques related to DFT. For this we want to leverage as much of the existing developments in plane-wave DFT and the related ecosystems of Julia python or C codes as possible.
The library is at an early stage and the supported feature set is still limited. An overview:
- Methods and models:
- Periodic Hamiltonians, such as reduced Hartree-Fock, Gross-Pitaevskii, density-functional theory, analytic potentials
- All LDA and GGA functionals from libxc supported.
- Godecker pseudopotentials (GTH, HGH)
- Exploit Brillouin zone symmetry for k-Point sampling
- Fermi-Dirac or Methfessel-Paxton smearing to treat metals
- Self-consistent field approaches: Damping, Kerker mixing, Anderson mixing (Pulay DIIS), all solvers from NLsolve.jl
- Direct minimization
- Ground-state properties and post-processing:
- Total energy / free energy computation
- Density of states (DOS) and local density of states (LDOS)
- Band structures
- Full access to all intermediate quantities (e.g. density, Bloch wave)
- Support for arbitrary floating point types, including
Float32(single precision) or
Double64(from DoubleFloats.jl). For DFT this is currently restricted to LDA (with Slater exchange and VWN correlation).
Note: DFTK has only been compared against standard packages for a small number of test cases and might still contain bugs.
The package is not yet registered in the General registry of Julia. Instead you can obtain it from the MolSim registry, which contains a bunch of packages related to performing molecular simulations in Julia. Note that at least Julia 1.2 is required.
MolSim to your installed registries. For this use
] registry add https://github.com/JuliaMolSim/MolSim.git
for a Julia command line. Afterwards you can install DFTK like any other package in Julia:
] add DFTK
or if you like the bleeding edge:
] add DFTK#master
Some parts of the code require a working Python installation with the libraries
The examples require
matplotlib as well.
Check out which version of python is used by the
You can do this for example with the Julia commands
using PyCall PyCall.python
Then use the corresponding package manager (usually
to install aforementioned libraries, for example
pip install scipy spglib matplotlib pymatgen
conda install -c conda-forge scipy spglib matplotlib pymatgen
You can then run the code in the
Despite the current focus on numerics, the intention is to keep the project rather general, so that this platform is useful for general research in materials science.
Feel free to contact us (@mfherbst and @antoine-levitt) directly, open issues or submit pull requests. Any contribution or discussion is welcome!