The GNNPCSAFT Web App is an implementation of our project that focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT. We developed this app so the scientific community can access the model's results easily.
In this app, the estimated pure-component parameters can be used to calculate thermodynamic properties and compare them with experimental data from the ThermoML Archive.
More info on github repository.
Features
- Estimates PC-SAFT parameters with SMILES or InChI
- Estimate parameters for associative and non-associative molecules
- 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
License
MIT LicenseFollow GNNPCSAFT Web App
You Might Also Like
Gen AI apps are built with MongoDB Atlas
MongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of GNNPCSAFT Web App!