This is a project which is currently making use of HPC facilities at Newcastle University. It is active.
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This project uses quantum chemistry and molecular thermodynamics to support the design of more energy-efficient industrial separation processes for complex mixtures of heavy lipid molecules, such as esters, fatty alcohols and fatty acids. Many of these molecules are missing from standard property databases, so their phase behaviour cannot be predicted reliably in process simulation software. We will use density functional theory to optimise conformer ensembles of the target molecules and calculate their solvent-screening surfaces. These are used in the COSMO-RS method to predict activity coefficients and vapour–liquid and liquid–liquid equilibria. Thermodynamic model parameters are then fitted to these predictions and used in process simulations to compare lower-energy process options. The work forms part of an EPSRC-funded PhD in collaboration with an industrial partner.
TURBOMOLE (density functional theory: BP86 functional, def-TZVP and def2-TZVPD basis sets, RI-J approximation, COSMO continuum solvation including the FINE cavity); BIOVIA COSMOconf (automated conformer workflow: Balloon and RDKit conformer generation with the MMFF94 force field, geometric clustering, COSMO-RS-based conformer selection); BIOVIA COSMOtherm (COSMO-RS thermodynamic predictions); Python (NumPy/SciPy) for post-processing and parameter regression.