hitarth64/quantum-inspired-cluster-expansion

Quantum-inspired Cluster Expansion: formulating chemical space search as QUBOs and Ising models

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Experimental

This tool helps materials scientists and chemists efficiently explore vast chemical spaces to discover new materials. By taking computational chemistry data (like DFT or ML potential outputs), it can predict material properties and identify optimal compositions or structures. Researchers focused on material discovery and optimization would find this useful.

No commits in the last 6 months.

Use this if you need to systematically and efficiently search a large number of possible material compositions or configurations to find those with desired properties.

Not ideal if you are only performing simple computational chemistry calculations for a few known structures and do not need to explore a combinatorial space.

materials-discovery chemical-space-exploration computational-materials-science materials-optimization inorganic-chemistry
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 6 / 25

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12

Forks

1

Language

Python

License

BSD-3-Clause-Clear

Last pushed

Jan 14, 2023

Commits (30d)

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