The goal of this research group is to advance in the understanding of the complex intermolecular interactions that define the thermodynamic and thermophysical behaviour of fluids for the formulation of physically sound phase behaviour and property models for process and product design and simulation. This group’s research combines experimental data collection, modelling and simulation.

Electrolyte Systems

The phase behaviour of mixtures containing electrolytes is very important for process and product design and simulation. Electrolyte mixtures are found in the production of fertilizers; biochemical processes; precipitation and crystallization processes; purification of pharmaceuticals; desalination of water; carbon capture; salting-in/salting-out based separation processes, etc.

The goal of this project is to study the thermodynamics and the phase behaviour of electrolyte mixtures containing Alcohol/Water/Salt. To do so, experimental data collection and modelling are being used to map and predict the complex phase behaviour of these mixtures. The motivation behind this project is the potential application of salts

Liquid Density of Polar Components

The prediction of liquid density at high temperatures and pressures plays a very important role in the design and simulation of high-pressure processes. The Linear Secant Modulus (LSM) density correlation is a simple, consistent and accurate correlation for the prediction of liquid density at extreme conditions. This correlation is well suited for non-polar and polar components and produces reliable and accurate results at pressures as high as 1000 MPa.

Phase Behaviour of Mixtures of Polar Bio-Solvents

Polar bio-solvents (such as alcohols, ketones, acids and esters) are suitable substances to replace petroleum-derived solvents in multiple industrial applications. Polar bio-solvents are produced from renewable resources such as biomass and have a lower carbon fingerprint and environmental impact than petroleum-derived solvents. Understanding the phase behaviour of these components and their mixtures and developing predictive approaches for their phase behaviour are needed for process and product design and simulation.

Cubic equations of state (CEoS) are the workhorse of the industry because of their simplicity, versatility, and computational efficiency. However, C-EoS are not predictive unless binary interaction parameters are known. The goal of this project is to propose a generalized correlation for the calculation of binary interaction parameters for mixtures containing polar bio solvents. The deliverable is a predictive methodology based on a Cubic Equation of State suitable for process design and simulation.

Categories: Research