soap-tastes-ok/thermo-ml
Thermodynamics powered by Machine Learning
This project helps scientists in thermodynamics predict unknown properties of materials more accurately by leveraging machine learning. It takes chemical formulas and properties of constituent atoms as input, and aims to output predictions for various thermodynamic properties of compounds, such as enthalpy or electronegativity. The intended users are chemists, materials scientists, and researchers who work with thermodynamic data and want to use AI for better predictions.
No commits in the last 6 months.
Use this if you are a scientist in thermodynamics who wants to quickly access physical and chemical data for atoms and compounds, and eventually predict their properties using machine learning.
Not ideal if you are looking for a fully-fledged, production-ready solution for complex thermodynamic simulations or if you require predictions for a wide range of compound types beyond oxides and basic atomic properties immediately.
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11
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2
Language
Python
License
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Category
Last pushed
May 07, 2021
Commits (30d)
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