Removing PFAS by foam fractioning: Experimental study, modelling and Chemoinformatic

Context and objectives : PFAS (per- and polyfluoroalkyl substances), are a broad group of synthetic chemical compounds which exhibit exceptional properties, such as omniphobic behavior or extremely high chemical and thermal stability. This high stability grants them their popular nomination as “forever chemicals” because they are virtually no bio or chemically degradable. Among these compounds (more than 4 700 substances according to the OCDE), it is non-polymeric short chain PFAS which interest us, more specifically per- and polyfluoroalkyl acids, are those to which the regulation is most focused due to their potential toxicity.

There are several technologies capable of capturing PFAS, like sorption, reverse osmosis, membrane filtration, foam fractioning, but none of them are capable to remove all different compounds nor the phenomena taking place on the capture process is fully understood. For this project, we will focus on one of these techniques, foam fractioning. It is a physical-chemical process in which surface active compounds are removed from a liquid matrix (usually aqueous) through bubbling. In fact, foam fractioning has become an interesting technology to treat recalcitrant pollutants in water. Thus, it is very important to be able to predict and control the amount of foam produced as well as its quality during the removal process.

Workplan: We propose a two-step approach: a first experimental phase followed by a modelling one. First of all, it is required to map the impact of the different physical-chemical and compositional parameters on the PFAS adsorption process. To do so, the resulting foam characteristics (foam stability and quality, foamability, bubble size and distribution) should be analyzed along with the impact of process parameters such as aeration time, gas flowrate or the phases composition. After this, the experimental data gathered will allow to perform a more comprehensive study on the PFAS foaming phenomena through empirical modelling where chemoinformatic tools could be a strong ally to obtaining predictive models, in particular QSPR models (quantitative structure-property relationship).

Keywords: Foam fractioning, PFAS, model, chemoinformatic, QSPR.

• Academic supervisor  Dr Christophe PREUX, IFPEN, ORCID : 0000-0002-7528-9270    
• Doctoral School    Sorbonne Université, ED 388
• IFPEN supervisor   Dr Christian BLAZQUEZ EGEA, ORCID : 0000-0002-1604-8370 
• PhD location    IFPEN, Rueil-Malmaison, France
• Duration and start date    3 years, starting in the fourth quarter 2025 (November, 3rd 2025)
• Employer    IFPEN
• Academic requirements  Master 2 in Physical-chemistry, Chemical engineer
• Language requirements  English level B2 (CEFR)
• Other requirements    Process engineer, with a strong interest for experimental research and skills in modelling and chemoinformatic.

To apply, please send your cover letter and CV to the supervisors indicated here below.