RyotaroOKabe/phonon_prediction
We present the virtual node graph neural network (VGNN) to address the challenges in phonon prediction.
This project helps materials scientists quickly predict a material's phonon properties, which determine how heat and sound travel through it. You input a crystal structure file (CIF), and it outputs a detailed phonon prediction, including phonon band structures. It's designed for researchers and engineers in materials science and engineering.
No commits in the last 6 months.
Use this if you need to rapidly predict the thermal and acoustic properties of new materials based on their crystal structures, without requiring extensive, time-consuming simulations.
Not ideal if you are looking for a general-purpose machine learning library rather than a specialized tool for materials science phonon prediction.
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23
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2
Language
Jupyter Notebook
License
MIT
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Last pushed
Oct 28, 2024
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