jschrier/SynthGPT

Code and Data for "Large Language Models for Inorganic Synthesis Prediction"

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This project helps inorganic chemists predict how to synthesize new materials and whether a material can be synthesized at all. It takes in experimental data about chemical reactions and materials, then uses large language models to suggest specific precursor chemicals and evaluate the likelihood of successful synthesis. The primary users are researchers and scientists working in materials science and inorganic chemistry.

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Use this if you are an inorganic chemist or materials scientist looking to accelerate your research by using AI to predict synthesis pathways or assess the synthesizability of novel inorganic compounds.

Not ideal if you are working with organic chemistry, biochemistry, or other fields outside of inorganic material synthesis, as its models are specifically trained for inorganic reactions.

inorganic-chemistry materials-science chemical-synthesis materials-discovery reaction-prediction
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 11 / 25

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33

Forks

4

Language

Python

License

MIT

Last pushed

Sep 04, 2024

Commits (30d)

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