CAF helps solid-state chemists and materials scientists in generating compositional training data for compounds. Both experimentalists and novices can use this tool with a basic understanding of Python. The codebase is designed for easy customization.
Features:
- Generate compositional descriptors for binary, ternary, and quaternary compounds from Excel or
.ciffiles - Filter and sort chemical formulas using four different methods
- Merge Excel files
- No coding required
If you use CAF in your scientific publication, please cite the software package:
Digital Discovery, https://doi.org/10.1039/D4DD00332B
as well as the Oliynyk elemental property dataset:
Data in Brief, https://doi.org/10.1016/j.dib.2024.110178
To learn more, please read the official documentation at https://github.com/bobleesj/composition-analyzer-featurizer.
CAF is built and maintained with scikit-package.