gSAFT: Advanced physical property prediction in gPROMS

A 3-part webinar series

Intro to gSAFT - Available on-demand
Solubility prediction - Available on-demand
Polymer modelling - Available on-demand

Accurate prediction of physical properties is an essential component of process modelling. The advent of equations of state derived formally from molecular-level interactions, such as those based on the Statistical Associating Fluid Theory (SAFT), marks a step change in this context. SAFT-type approaches are capable of accurately modelling challenging systems, from small gas molecules to polymers, surfactants and electrolytes, all within a consistent theoretical framework.

PSE’s next-generation gSAFT physical properties technology provides robust and efficient implementations of two equations of state based on the SAFT theory, namely SAFT-VR SW and SAFT-γ Mie. The latter represents a state-of-the-art group contribution approach which offers the possibility of predicting the properties of pure components and mixtures with little (or sometimes, no) reliance on experimental data. By effectively addressing the underlying mathematical and numerical complexity, gSAFT now provides a general-purpose physical property framework that can be used efficiently within the gPROMS process modelling environment across a wide range of processes, from upstream oil & gas applications to fine chemicals and pharmaceuticals.

In this series of three webinars, Thomas Lafitte will present an in-depth description of gSAFT and its capabilities, especially in terms of predicting properties of complex fluids that pose serious challenges to other methods.

Webinar 1: Introduction to gSAFT


  • Brief review of the fundamentals behind the SAFT-γ Mie equation of state
  • Accurate prediction of physical properties of fluid phases involving complex mixtures, including those involving polar molecules, strongly associated species etc.
  • Key aspects of the implementation of SAFT-γ Mie within gSAFT, and the gSAFT parameter databank
  • Deploying gSAFT within gPROMS models, and its efficient use in large-scale simulation and optimisation

Webinar 2: gSAFT for solubility prediction


  • Theoretical background for prediction of solid/liquid equilibria
  • Gibbs free energy models for solid phases
  • Solubility predictions of complex molecules in pure and multicomponent solvents, with particular emphasis on active pharmaceutical ingredients

Webinar 3: gSAFT for polymer modelling


  • Predictive capabilities of gSAFT for polymer solutions
  • Defining polymer mixtures in gSAFT
  • Accurate and reliable phase equilibrium calculations for mixtures involving polymers
  • Reactor modelling: modifying the polymer structure during process simulation: variable molecular structures in gSAFT


Thomas Lafitte Thomas Lafitte is a Senior Scientist - Materials Modelling at Process Systems Enterprise. Thomas leads the development of gSAFT.

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