Repository associated with Physical descriptor for the Gibbs energy of inorganic crystalline solids and temperature-dependent materials chemistry article used to predict the temperature-dependent Gibbs energies of inorganic crystalline solids.
This repository is a rewritten copy of original repo.
Table of 440 compounds used for training and testing the SISSO-learned descriptor.
Dictionary of atomic masses (amu) in format {element : mass}
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Dictionary of experimental Gibbs energies (chemical potentials) for the elements in format {temperature (K) : {element : G (eV/atom)}}
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Structure file for Al2O3 from Materials Project to demonstrate use of descriptor.
CLI is provided for the Gibbs energy approximation. An example usage of it for Al2O3:
./cli.py --formula Al2O3 --H=-3.442 --structure=data/POSCAR.mp-1143_Al2O3
Contains class for implementing SISSO-learned descriptor; see comments within and arXiv link for detailsю
Contains chemical formula parser; see comments within for usage examples.
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Formula standardizer extracted into separate class, now it is much more time-efficient (from 9x to 28x on different benchmarks) and able to process more complicated formulas;
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Tests provided to cover formula standartization;
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Predictor refactored and type hints provided in accordance with MyPy guidelines;
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Integrational tests for matching results with previous implementation provided;
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CLI interface for predictor provided;
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CI/CD pipelines added for code quality control and testing.
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Move floating-point calculations to high-precision class, such as Decimal;
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Provide GUI-backed application for the predictor.