Process Systems Enterprise Ltd

- Advanced Molecular Thermodynamic

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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.

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.

Revolutionising physical property prediction for complex fluids

Accurate design and optimisation of chemical processes requires accurate physical property predictions over a wide range of conditions.

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 provides gSAFT with two methods based on the different SAFT theories developed within Imperial College London's Molecular Systems Group: SAFT VR and SAFT-γ Mie.

Because of the accuracy of the underlying model, SAFT can predict the properties of many complex mixtures with an accuracy that has not been possible in the past.

Component and mixture properties can often be predicted accurately – especially by SAFT-γ Mie – even in cases where very little experimental data is available.

Because of the underlying model, SAFT can provide a prediction of properties of the following complex mixtures with an accuracy that has not been possible in the past. Systems of interest include:

  • 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.

In particular SAFT allows for the treatment of systems with varying polarity, from the standard Lennard-Jones dispersion to highly polar interaction. General association schemes can be incorporated into the treatment.

The underlying model also allows for predictions are valid over a wide range of operating conditions. This is a particular advantage for systems where there is limited experimental data in the areas of operation being studied.

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