Microemulsion model: Towards the prediction of liquid-liquid extraction processes

This multi-scale modeling PhD project aims to develop innovative theoretical approaches and numerical tools to predict the extraction processes of strategic metals, which are essential for the energy transition. Among the existing methods, liquid-liquid extraction is a key process, but its underlying mechanisms remain poorly understood. To address these challenges, the solvent phases will be represented as microemulsions through a synergy of mesoscopic and molecular modeling approaches.
The mesoscopic approach will involve the development of a code based on microemulsion theory using a random wavelet basis. This code will enable the characterization of the structural and thermodynamic properties of the solutions. The molecular approach will rely on classical molecular dynamics simulations to evaluate the curvature properties of the extractants, which are essential for bridging the two scales.
The new high-performance computational code may integrate artificial intelligence techniques to accelerate the minimization of the system’s free energy while accounting for all chemical species present with a minimal number of parameters. This will pave the way for new research directions, such as predicting speciation and calculating thermodynamic instabilities in ternary phase diagrams, thereby identifying unexplored experimental conditions.
This PhD thesis, conducted at the Mesoscopic Modeling and Theoretical Chemistry Laboratory at the Marcoule Institute for Separation Chemistry, will have applications in the recycling domain and extend to the broader field of nanoscience, thereby expanding the impact of this work.
The PhD candidate, with a background in physical chemistry, theoretical chemistry, or physics and a strong interest in programming, will be encouraged to disseminate their scientific results through publications and presentations at national and international conferences. By the end of the thesis, the candidate will have acquired a broad range of skills in theoretical chemistry, modeling, numerical computation, and physical chemistry, providing numerous career opportunities in both academic research and industrial R&D.