The density-functional toolkit, DFTK for short, is a library of Julia routines for playing with plane-wave density-functional theory (DFT) algorithms. In its basic formulation it solves periodic Kohn-Sham equations. The unique feature of the code is its emphasis on simplicity and flexibility with the goal of facilitating methodological development and interdisciplinary collaboration. In about 7k lines of pure Julia code we support a sizeable set of features. Our performance is of the same order of magnitude as much larger production codes such as Abinit, Quantum Espresso and VASP. DFTK's source code is publicly available on github.
We will organise a summer school centred around the DFTK code and modern approaches to density-functional theory from 29 to 31 August 2022 at Sorbonne Université, Paris. For more details and registration info see the school's website.
- Methods and models:
- Standard DFT models (LDA, GGA, meta-GGA): Any functional from the libxc library
- Flexibility to build your own Kohn-Sham model: Anything from analytic potentials, linear Cohen-Bergstresser models, Gross-Pitaevskii equations, anyonic models, etc.
- Analytic potentials or Godecker norm-conserving pseudopotentials (GTH, HGH)
- Brillouin zone symmetry for $k$-point sampling using spglib
- Standard smearing functions (including Methfessel-Paxton and Marzari-Vanderbilt cold smearing)
- Collinear spin polarization for magnetic systems
- Self-consistent field approaches including Kerker mixing, LDOS mixing, adaptive damping
- Direct minimization, Newton solver
- Multi-level threading ($k$-points eigenvectors, FFTs, linear algebra)
- MPI-based distributed parallelism (distribution over $k$-points)
- 1D / 2D / 3D systems
- External magnetic fields
- Treat systems of 1000 electrons
- Ground-state properties and post-processing:
- Total energy
- Forces, stresses
- Density of states (DOS), local density of states (LDOS)
- Band structures
- Easy access to all intermediate quantities (e.g. density, Bloch waves)
- Support for arbitrary floating point types, including
Float32(single precision) or
- Runs out of the box on Linux, macOS and Windows
- Third-party integrations:
- Temperature and metallic systems
- Creating supercells with pymatgen
- Creating slabs with ASE
- Collinear spin and magnetic systems
- Geometry optimization
- Monitoring self-consistent field calculations
- Saving SCF results on disk and SCF checkpoints
- Polarizability by linear response
- Gross-Pitaevskii equation in one dimension
- Gross-Pitaevskii equation with external magnetic field
- Cohen-Bergstresser model
- Arbitrary floating-point types
- Polarizability using automatic differentiation
- Custom solvers
- Custom potential
- Wannierization using Wannier90
- Practical error bounds for the forces
- Graphene band structure
These and more examples can be found in the
examples directory of the main code.
In the documentation we use very rough convergence parameters to be able to automatically generate this documentation very quickly. Therefore results are far from converged. Tighter thresholds and larger grids should be used for more realistic results.
If you have a great example you think would fit here, please open a pull request!