aiida-dftbplus

Run DFTB+ from AiiDA: the plugin writes dftb_in.hsd, submits the job, brings every output file back and stores the input parameters as queryable database attributes.

One calculation in, one calculation out — no workflows, no error recovery.

Install

pip install aiida-dftbplus
verdi quicksetup          # if you do not have a profile yet

DFTB+ itself comes separately (e.g. conda install -c conda-forge dftbplus). Register it once:

verdi code create core.code.installed \
    --label dftb+ --computer localhost \
    --default-calc-job-plugin dftbplus \
    --filepath-executable $(which dftb+)

Run something

verdi daemon start
cd examples
./example_01.py --code dftb+@localhost --skf-dir /path/to/skf/

Describe the input

Write the HSD as a nested dictionary — every setting stays queryable:

from aiida import engine, orm
from aiida.plugins import CalculationFactory, DataFactory

DftbParameters = DataFactory("dftbplus")

parameters = DftbParameters({
    "Geometry": {"GenFormat": {"_raw": open("geometry.gen").read()}},
    "Hamiltonian": {"DFTB": {
        "SCC": True,
        "MaxSCCIterations": 100,
        "SCCTolerance": 1e-5,
        "_raw_1": 'SlaterKosterFiles = Type2FileNames {\n'
                  '  Prefix = "/opt/skf/mio-1-1/"\n'
                  '  Separator = "-"\n  Suffix = ".skf"\n}',
    }},
    "Analysis": {"CalculateForces": True},
})

engine.submit(CalculationFactory("dftbplus"), code=code, parameters=parameters)

Anything the dictionary form does not cover goes through verbatim under a _raw* key, so nothing in DFTB+ is out of reach. Dictionaries are validated before submission — print(DftbParameters.schema.schema) lists the blocks.

Already have a file? Hand it over instead:

inputs["dftb_input"] = DataFactory("core.singlefile")(file="dftb_in.hsd")

Exactly one of parameters or dftb_input is required.

Slater-Koster files

Two options, and the choice matters for speed:

• use_remote_skf_path=True — the files already sit on the machine, keep the absolute path in the HSD and upload nothing. Best for a full parameter set.

• skf_files (a FolderData) — ship the files with the job, but only the pairs the run reads. A full set is copied into every working directory and turns a one-second job into a several-minute one; a two-element material needs four files:

  skf_files = orm.FolderData()
  for name in (f"{a}-{b}.skf" for a in ["O", "S"] for b in ["O", "S"]):
      skf_files.put_object_from_file(str(skf_dir / name), name)
  

Get the results

verdi process list -a
verdi calcjob res <PK>        # parsed scalars: energies, Fermi level, forces
verdi calcjob outputls <PK>   # every retrieved file
verdi process report <PK>     # why it failed, if it did

output_parameters carries total_energy_H, total_energy_eV, fermi_energy_eV, scc_converged, n_scc_iterations, forces_eV_Ang and max_force_eV_Ang. Failures come back as exit codes: 300 output missing, 310 DFTB+ error, 320 SCC not converged, 330 geometry not converged.

Inspect the stored input nodes with the bundled verdi commands:

verdi data dftbplus list
verdi data dftbplus hsd <PK>    # render the node as the dftb_in.hsd it produces

Documentation

Full documentation — getting started, tutorials, how-to guides, architecture and API reference — at quantum-arise-acad.github.io/aiida-dftbplus.

Start here:

• Prerequisites — the four things you need before anything runs
• Slater–Koster parameter sets — which files, where to get them, how to point the plugin at them
• Your first calculation
• Architecture — for maintainers

Build it locally with pip install -e . --group docs && make -C docs.

License

MIT — see LICENSE.

Contact

sitouamu510@gmail.com