sfalmo/NeuralDFT-Tutorial
Neural functional theory for inhomogeneous fluids - Tutorial
This project helps researchers and students understand how to apply neural network techniques to study the behavior of inhomogeneous fluids. It takes theoretical models and simulation data of fluids as input and demonstrates how to construct and train neural functionals to predict properties like density profiles. This is useful for computational physicists, physical chemists, and materials scientists working on fluid simulations and statistical mechanics.
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Use this if you are a researcher or student in physics or chemistry looking to learn and apply neural functional theory to model inhomogeneous fluids.
Not ideal if you need a high-performance simulation tool for production-level research, as this is primarily a teaching and demonstration resource.
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Language
Jupyter Notebook
License
MIT
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Last pushed
May 20, 2025
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