eltonpan/zeosyn_gen

DiffSyn: A Generative Diffusion Approach to Materials Synthesis Planning (Nature Computational Science, 2026)

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Emerging

This project helps materials scientists and chemical engineers discover new ways to synthesize complex materials, specifically zeolites. By inputting the desired zeolite structure and organic structure-directing agent, it generates potential synthesis recipes (like ingredient lists and conditions) that are likely to work. This tool is for researchers developing novel materials for applications in catalysis, separations, and other advanced technologies.

Use this if you need to quickly explore many potential synthesis routes for a specific zeolite structure and OSDA, saving significant time and resources compared to traditional lab-based trial and error.

Not ideal if you are looking for a tool to simulate the performance of already-synthesized materials or to optimize existing, known synthesis pathways.

materials-synthesis zeolite-design chemical-engineering materials-science experimental-planning
No Package No Dependents
Maintenance 10 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 6 / 25

How are scores calculated?

Stars

35

Forks

2

Language

Python

License

MIT

Last pushed

Feb 10, 2026

Commits (30d)

0

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