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Our project harnesses the power of Graph Neural Network (GNN) to estimate pure-component parameters of the state-of-the-art Equation of State, PC-SAFT. We aim to empower users to leverage this robust equation without the need for prior experimental data, revolutionizing the calculation of thermodynamic properties and enhancing process simulations. FeOS is used for the PC-SAFT calculations. The estimated parameters can be used in DWSIM and Aspen HYSYS process simulators.
Features
- Estimates PC-SAFT parameters with SMILES or InChI
- Estimate parameters for associative and non-associative molecules
- AI Chat with GNNePCSAFT agent
- Evaluates the efficiency and accuracy for various molecules by comparing their performance to comprehensive experimental data sourced from the ThermoML Archive
- Custom plots for density, vapor pressure, enthalpy, entropy, surface tension and phase diagrams of pure substances
- Custom plots for the density, vapor pressure, VLE and LLE of mixtures
- Currently runs on Windows 11, MacOS and Ubuntu 24.04
Project Samples
License
MIT LicenseFollow GNNePCSAFT
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