huzongxiang/MatDGL
MatDGL is a neural network package that allows researchers to train custom models for crystal modeling tasks. It aims to accelerate the research and application of material science.
This package helps materials scientists and researchers build and train custom machine learning models to predict properties or behaviors of crystal structures. You input your crystal structure data (like CIF or POSCAR files) and optionally their known labels or properties, and it outputs a trained model capable of making predictions on new material structures. It's designed for those who need to leverage advanced deep learning for material design and analysis.
No commits in the last 6 months. Available on PyPI.
Use this if you are a materials researcher who needs to develop and test custom graph neural network models for crystal structure analysis and property prediction.
Not ideal if you are looking for a ready-to-use application with a graphical interface, as this tool requires familiarity with Python scripting and deep learning workflows.
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52
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Language
Python
License
MIT
Category
Last pushed
Jul 30, 2024
Commits (30d)
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