omron-sinicx/crystalframer

The official code respository for "Rethinking the role of frames for SE(3)-invariant crystal structure modeling" (ICLR 2025)

42
/ 100
Emerging

This tool helps materials scientists and researchers predict the properties of crystal structures. By inputting crystal structure data, it can output predictions for various material properties like formation energy, bandgap, and stability. It's designed for professionals in materials science, chemistry, and physics who work with crystal structure analysis and discovery.

Use this if you need to accurately model and predict properties of crystal structures based on their atomic arrangements.

Not ideal if you are looking for a general-purpose machine learning library or a tool for molecular dynamics simulations.

materials-science crystal-engineering materials-discovery solid-state-physics computational-chemistry
No Package No Dependents
Maintenance 6 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 14 / 25

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Stars

15

Forks

3

Language

Python

License

MIT

Last pushed

Oct 16, 2025

Commits (30d)

0

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