GNNePCSAFT

The project focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT.

Currently, the model takes into account the hard-chain, dispersive, and associative terms of PC-SAFT. Future work on polar and ionic terms is being studied.

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 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

Project Activity

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License

MIT License

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GNNePCSAFT Web Site

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Languages

English

Intended Audience

Education, Engineering, Manufacturing, Science/Research

User Interface

Electron

Programming Language

JavaScript, Python

Related Categories

Python Simulation Software, Python Chemistry Software, Python Machine Learning Software, JavaScript Simulation Software, JavaScript Chemistry Software, JavaScript Machine Learning Software

Registered

2025-02-02

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