Project R-13344

Unravelling membrane processes in organic solvents by data-driven modelling. (Research)

Membranes are very powerful and versatile separation tools for a more sustainable chemistry, offering an energy-lean alternative to the ubiquitous distillations and evaporations. The potential to use membranes in organic solvents, gave rise to a whole new R&D and application field named Organic Solvent Nanofiltration (OSN). The current absence of detailed fundamental understanding of the OSN process is a bottleneck for industrial use: membranes need to be screened based on trial and error for each solute- solvent couple to be separated. The main objective of this PhD project is to develop efficient, predictive data-driven OSN models, that will allow to unravel the transport of solute and solvent through a membrane, and to perform underpinned process design and membrane optimization, minimizing current tedious experimental membrane screening

16 November 2022 - 15 November 2026