Solphin

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solphin helps characterise candidate photovoltaic materials from first-principles calculations. It combines detailed-balance analysis with the photovoltaic figure of merit of A. Crovetto, the Spectroscopic Limited Maximum Efficiency (SLME), the Blank et al. maximum efficiency and optical absorption plots to build a full picture of a material's theoretical photovoltaic performance. From an initial crystal structure, solphin generates the VASP or CASTEP input files for each required calculation, and reads the results of either code.

Documentation, including workflow tutorials for both codes and the Python API reference, can be found at solphin.readthedocs.io.

Installation

Solphin is distributed on PyPI, and can be installed with the following command:

pip install solphin

Python 3.11 or newer is required.

To work on solphin itself, or to run the tutorial notebooks from the repository, install from a checkout instead:

git clone https://github.com/SMTG-Bham/solphin
cd solphin
pip install -e .

See the installation docs for the optional extras, the conda development environment and VASP pseudopotential setup.

Quick start

The detailed-balance analysis needs nothing beyond the package itself, so it is the quickest way to check an install. This computes the Shockley-Queisser limit for a 1.39 eV absorber (the Cu₂GeS₃ band gap used in the tutorials) under the bundled AM1.5G spectrum, then draws the three-panel detailed-balance figure:

import matplotlib.pyplot as plt

import solphin.db_fom as db_fom
import solphin.db_plots as db_plots

E_gap = 1.39   # band gap in eV
Tcell = 300.0  # cell temperature in K

spectrum = db_fom.load_spectrum("AM1.5")
photon_spectrum = db_fom.convert_spectrum(spectrum)

print(f"Jsc = {db_fom.jsc(E_gap, photon_spectrum, Tcell):.1f} A m^-2")
print(f"Voc = {db_fom.voc(E_gap, photon_spectrum, Tcell):.3f} V")
print(f"SQ efficiency limit = {100 * db_fom.max_eff(E_gap, photon_spectrum, Tcell):.1f} %")

db_plots.plot_db_combined(spectrum=photon_spectrum, Egap=E_gap, Tcell=Tcell, spectrum_type="AM1.5")
plt.savefig("detailed_balance.png", dpi=150, bbox_inches="tight")

The full workflow, from generating VASP or CASTEP inputs for a crystal structure to reading the finished calculations back into band gap, effective mass, absorption, SLME and figure-of-merit analyses, is walked through in a series of tutorial notebooks, alongside the API reference.

Contributing and support

Bug reports, feature requests and questions about using the code all go through the issue tracker. For a bug, please include the smallest snippet that reproduces it, the full traceback and your solphin version (python -c "import solphin; print(solphin.__version__)").

If you would like to contribute code or documentation, CONTRIBUTING.md covers the development environment, the style and docstring conventions, how to run the tests and how to build the documentation. This project follows the Contributor Covenant code of conduct.

Citation

If you use solphin in your work, please cite the following:

• Cox, P. U.; Russell, P. P.; Crovetto, A.; Squires, A. G.; Slocombe, L.; Scanlon, D. O. Solphin: Photovoltaic efficiency analysis for bulk materials using Python. 2026; https://arxiv.org/abs/2610.10028.
• Crovetto, A., 2024. A phenomenological figure of merit for photovoltaic materials. Journal of Physics: Energy, 6 (2), p.025009.
• Alex M. Ganose, Adam J. Jackson, David O. Scanlon. sumo: Command-line tools for plotting and analysis of periodic ab initio calculations. Journal of Open Source Software, 2018 3 (28), 717, doi:10.21105/joss.00717.

Acknowledgements

The developers Philippa U. Cox, Peter P. Russell and Louie Slocombe would like to thank Alexander G. Squires, Andrea Crovetto and David O. Scanlon for their guidance on this project, Brooke Busbee for her work on the branding and Jacob Baggott for his assistance.

License

solphin is released under the MIT License.