matador: a Python library for analysing, curating and performing high-throughput density-functional theory calculations (original) (raw)
Review
Editor: @jgostick (all papers)
Reviewers: @mkhorton (all reviews), @srmnitc (all reviews)
Authors
[Matthew L. Evans](/papers/by/Matthew L%2E Evans) (0000-0002-1182-9098), [Andrew J. Morris](/papers/by/Andrew J%2E Morris) (0000-0001-7453-5698)
Citation
Evans et al., (2020). matador: a Python library for analysing, curating and performing high-throughput density-functional theory calculations. Journal of Open Source Software, 5(54), 2563, https://doi.org/10.21105/joss.02563
@article{Evans2020, doi = {10.21105/joss.02563}, url = {https://doi.org/10.21105/joss.02563}, year = {2020}, publisher = {The Open Journal}, volume = {5}, number = {54}, pages = {2563}, author = {Evans, Matthew L. and Morris, Andrew J.}, title = {matador: a Python library for analysing, curating and performing high-throughput density-functional theory calculations}, journal = {Journal of Open Source Software} }
Tags
density-functional theory ab initio crystal structure prediction materials discovery databases castep quantum espresso mongodb
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