This archive contains files that accompany the article "Predicting electronic screening for fast Koopmans spectral functional calculations" (Schubert et al., 2024). To understand the context of these calculations, please refer to that work.
acenes/
input and output koopmans files for calculations examining the correlation between the self-Hartree energy of orbitals and their screening parameter
convergence_analysis/
input and output koopmans files for optimising the hyperparameters of the machine learning model
manuscript_figures/
python scripts for generating the figures contained in the manuscript, alongside the figures themselves.
orbital_figures/
png images of the maximally localised Wannier functions of the CsSnI3 and water systems extracted from .xsf Quantum ESPRESSO files
single_CsSnI3_calculation/ and single_water_cls_calculation/
koopmans input and outputs for example calculations on water and CsSnI3.
The koopmans package takes input files in human-readable JSON format. The code produces files in various different formats, including...
.kwf files containing the workflow data. These files are in human-readable JSON format, and are best parsed using the koopmans package (as the data will be converted into python objects of the appropriate classes) but can also be parsed by a generic json reader..bib bibtex files.log, .dat, .cpi, .cpo, .txt, ...).pkl), readable via python's pickle packageOther files in this repository include images in .png and .pdf formats.
The results were produced using v1.0.0 of the koopmans package. This is open-source and accessible on GitHub.
Creative Commons Attribution 4.0 International