Installation¶

Prerequisites¶

Before installing aiida-impuritysupercellconv make sure you have:

Python 3.8 or newer
A working AiiDA installation (v2.0+) with a configured profile
A running AiiDA daemon (verdi daemon start)
Quantum ESPRESSO ≥ 7.1 configured as an AiiDA code (for DFT calculations)
Pseudopotential families installed (the default protocol uses SSSP/1.3/PBE/efficiency)

Install pseudopotentials with aiida-pseudo:

pip install aiida-pseudo
aiida-pseudo install sssp -v 1.3 -x PBE -p efficiency

Installing aiida-impuritysupercellconv¶

From PyPI (recommended)¶

pip install aiida-impuritysupercellconv

From source¶

git clone https://github.com/positivemuon/aiida-impuritysupercellconv.git
cd aiida-impuritysupercellconv
pip install -e .

Verify the workflow is registered:

verdi plugin list aiida.workflows | grep impuritysupercellconv

You should see impuritysupercellconv listed.

Optional: MLIP force calculations (experimental)¶

Experimental feature

Support for Machine Learning Interatomic Potential (MLIP) force calculations via aiida-pythonjob and ASE calculators is experimental. The API may change in future releases. Use it for rapid screening only; always validate supercell convergence with DFT.

To use MLIP-based force calculations you need the following additional packages:

pip install aiida-pythonjob
pip install mace-torch        # or another ASE-compatible MLIP

Verify the pythonjob plugin is registered:

verdi plugin list aiida.calculations | grep pythonjob

Verifying the installation¶

Run a quick sanity check to confirm everything is in order:

python -c "from aiida_impuritysupercellconv.workflows.impuritysupercellconv import IsolatedImpurityWorkChain; print('OK')"

Dependencies¶

Package	Version	Purpose
`aiida-core`	≥ 2.0	workflow engine
`aiida-quantumespresso`	≥ 4.2	DFT calculations
`aiida-pseudo`	any	pseudopotential families
`pymatgen`	≥ 2022.10.22	structure manipulation
`pymatgen-analysis-defects`	any	Voronoi interstitial site generation
`ase`	any	structure I/O and unit conversion
`numpy`	any	numerical arrays
`scipy`	any	exponential curve fitting
`aiida-pythonjob` (optional)	any	MLIP force calculations