Data presented in "A method to computationally screen for tunable properties of crystalline alloys."

These files are a static database dump of the database presented in: <br> Woods-Robinson, R., Horton, M. K., &amp; Persson, K. A. (2022). A method to computationally screen for tunable properties of crystalline alloys. arXiv preprint arXiv:2206.10715. <br> The database presented in this work is intended to be a living resource, and will be updated and revised over time. The files here are made available only a static snapshot to store a record of the latest version of the database available at the point in time that the manuscript was finalized. It is expected that the latest version will be available at Materials Project and users are strongly advised to retrieve the latest data when performing any follow-up work. This data will be available from the Materials Project API, https://materialsproject.org/api, and will be the most up-to-date, incorporating any new database additions or changes, and the latest bug fixes (where applicable). <br> The files in this snapshot can be loaded via either Python, using the `monty` package and its `loadfn` function, or via other JSON parsing libraries, or can be imported directly in MongoDB or similar database system. It is advisable to have the `pymatgen-analysis-alloys` package installed via `pip` or otherwise to make use of this data, version 0.0.6 or greater. Note that duplicates of the respective `AlloyPair` objects are not included within the `AlloySystem` records for reasons of space, but the relevant the `pair_id` identifiers are included, and these objects can be fully reconstructed as necessary from the data stored within the `alloy_pairs.json.gz` file. <br> Please refer any questions to the authors. <br> <br>