This multi-scale modeling thesis aims to develop innovative theoretical approaches and numerical tools to revolutionize strategic metal extraction processes, such as liquid-liquid extraction, whose underlying mechanisms remain poorly understood. To address these challenges, 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 an academic background in physical chemistry, theoretical chemistry, or physics, and a strong interest in programming, will be encouraged to disseminate his/her scientific results through publications and presentations at national and international conferences. Upon completion of the thesis, the candidate will have acquired a wide range of skills in modeling and physical chemistry, opening numerous professional opportunities in both academic research and industrial R&D.