sparks-baird/mat_discover
A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.
This tool helps materials scientists and researchers identify promising new material compositions. You input a list of chemical compositions and their known properties, and it outputs a ranked list of novel compositions predicted to have high performance. It's designed for anyone working on discovering new materials with specific desired characteristics.
No commits in the last 6 months. Available on PyPI.
Use this if you are a materials scientist or researcher who wants to efficiently explore new chemical spaces and discover novel, high-performing materials compositions beyond what is already known.
Not ideal if you are looking for a tool to simulate material properties at an atomic level or to optimize existing material compositions, rather than discover entirely new ones.
Stars
46
Forks
9
Language
Python
License
MIT
Category
Last pushed
Aug 20, 2024
Commits (30d)
0
Dependencies
24
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