Statistical Associating Fluid Theory, or SAFT, is an advanced molecular thermodynamic method that can predict a wide variety of thermodynamic properties of mixtures accurately based on physically-realistic models of molecules and their interactions with other molecules.
PSE has implemented the SAFT-VR and the SAFT-γ Mie group contribution methods in the gSAFT® product. gSAFT properties can be used within any applicable gPROMS® family product.
The advantages of SAFT
Because SAFT uses a more physically-realistic underlying model than standard cubic equations of state, it has many advantages when it comes to accurately predicting properties of pure components and mixtures over a wide range of operating conditions from limited experimental data.
In particular, it can predict properties of complex mixtures with an accuracy that has not been possible in the past, including:
- polar fluids (e.g. CO2, refrigerants)
- strongly associating / hydrogen bonding (e.g. carboxylic acids, HF, water)
- mixed electrolytes (e.g. inorganic salts, charged surfactants)
- polymers
- gas hydrates & asphaltenes.
The power of group contribution
A key advantage of the PSE gSAFT implementation is the use of group contribution methods that allow highly-accurate prediction of a wide range of properties and mixture equilibria from a very limited set of measured data.
This is particularly important in industries dealing with non-standard chemicals such as surfactants, oleochemicals or polymers.
Using gSAFT with gPROMS family products
gSAFT can be used alongside the various other physical property packages available within the gPROMS family products.
PSE has acquired SAFT-VR and SAFT-γ Mie technology developed by Imperial College London’s Molecular Systems Engineering group
