Supporting data for "Ab initio thermodynamic model of Cu2ZnSnS4"

The paper "Ab initio thermodynamic model of Cu2ZnSnS4" uses first-principles calculations to study the stability of Cu2ZnSnS4 (CZTS), a promising material for photovoltaics. CZTS is difficult to produce at high quality using existing processing methods, and so there is a shortage of the thermochemical data which might be used to improve this process. This cycle can be broken by predicting the properties from first-principles. The initial calculations were quite "computationally expensive", using national-scale computing facilities to model the vibrations of a range of crystals within density functional theory (DFT), using a licensed quantum chemistry code. The following thermodynamic modelling process however can be carried out on a desktop computer and uses open-source software. The code for this post-processing is provided along with the required data, and can be used to a) reproduce the plots in the paper b) examine the model used and c) extend the model or apply the data to another system.

This dataset contains the supporting data and Python 2.7 code for the published article, "Ab initio thermodynamic model of Cu2ZnSnS4".

This release covers the content of the initial publication in J. Mater. Chem. A (2014), with some minor bug fixes and data released by Jonathan Scragg. Re-released to make use of GitHub's new DOI integration with Zenodo.

photovoltaics, kesterite, CZTS, thermodynamics, ab initio, DFT, PBEsol, FHI-aims, Python, Matplotlib, phonons, Phonopy, thermochemistry

Cite this dataset as:
Jackson, A., Walsh, A., 2015. Supporting data for "Ab initio thermodynamic model of Cu2ZnSnS4". Version 1.2. Zenodo. Available from:


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Adam Jackson
University of Bath

Aron Walsh
University of Bath


University of Bath
Rights Holder


Data collection method:

First-principles calculations within density functional theory (DFT), using the Fritz Haber Institute ab initio simulations package (FHI-aims) and the PBEsol DFT functional. Details given in paper.

Data processing and preparation activities:

Analysis with original code using the typical scientific Python stack: Python 2.7, Numpy, Scipy and Matplotlib

Additional information:

This dataset corresponds to release v1.2a. The code initially released with the paper corresponds to the v1.0 tag in the GitHub repository.


Engineering and Physical Sciences Research Council

Doctoral Training Centre in Sustainable Chemical Technologies

Publication details

Publication date: 2015
by: Zenodo

Version: 1.2


URL for this record:

Related papers and books

Jackson, A. J., and Walsh, A., 2014. Abinitio thermodynamic model of Cu2ZnSnS4. J. Mater. Chem. A, 2(21), 7829-7836. Available from:

Contact information

Please contact the Research Data Service in the first instance for all matters concerning this item.

Contact person: Adam Jackson


Faculty of Science