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craabreu/cosmolayer

Differentiable COSMO-Type Activity Coefficient Layer

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PyPI version PyPI version PyPI version

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Overview

CosmoLayer is a package implementing differentiable COSMO-type activity coefficient calculation layers for neural network models.

CosmoLayer leverages automatic differentiation and GPU acceleration to enable efficient computation and gradient-based optimization of COSMO model parameters.

Installation and Usage

CosmoLayer is available as a conda package on the mdtools channel. To install it, run:

    conda install -c conda-forge -c mdtools cosmolayer

Or:

    mamba install -c mdtools cosmolayer

To use CosmoLayer in your own Python script or Jupyter notebook, simply import it as follows:

    import cosmolayer

Documentation

Documentation for the latest CosmoLayer version is available at Github Pages.

Copyright

Copyright (c) 2026 Charlles Abreu

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Differentiable COSMO-Type Activity Coefficient Layer

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