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.
Explainable AI for interpretation of Small Angle Scattering
The PhD will be conducted in two laboratories at Paris-Saclay: one group with expertise in artificial intelligence developed over many years, MIA-PS (INRAE), and another in the physics of matter – soft matter, biology – MMB-LLB (CEA/CNRS).
Small-Angle Scattering techniques (X-rays, neutrons, light) involve a constantly growing community, particularly active in France, especially in soft matter and biology. The transition of data from reciprocal space to real space is achieved via different models – in which the MMB group is an expert – whether concerning shape – sphere, rod, platelet, polymer chain – or interactions – attraction, aggregation, repulsion, arrangement. Furthermore, more complex structures, such as proteins or irregular aggregates, require computational or empirical approaches. In all cases, the results are not unequivocal. This is particularly challenging for research groups new to the technique.
In this thesis, thanks to MIA-PS's expertise in AI (machine learning, optimization, visualization), the focus will be on developing explainable AI methods. Part of the modeling involves explained mathematical and physical models, while another part relies on so-called "black box" models, which will be progressively explained. The doctoral candidate will have access to data from three use cases provided by the LLB, and to their experts, to develop a generic methodology. A first step could be based on the globally shared software SasView, a treasure trove of explicit models. We have already received a positive response from the SasView developers, which could therefore serve as a dissemination tool. A valuable contribution will be the access to complementary DPA measurements via the LLB platforms and the SOLEIL and ESRF synchrotrons.
Subsequently, a component focusing on human-computer interaction—ensuring that users remain fully responsible for constructing a physico-chemical-biological explanation—can be implemented. MIA-PS is also an expert in advanced interactive visualization methods.
This project therefore combines highly advanced developments in computer science with a wealth of real-world systems chosen for their originality and, of course, their potential applications.
Toughening random lattice metamaterials with structure heterogeneities
To reduce the environmental and/or the energetic impact of vehicles, a favored method is to decrease the mass of prime materials used to build them, that being done without hindering their mechanical performances. In this field, the use of mechanical metamaterials has been a major breakthrough. These metamaterials, generally created using additive manufacturing techniques, have a microscopic truss structure. They are porous by design, and thus very lightweight, and the distribution of their microscopic beams or tubes (i.e. their architecture) can be chosen to make them as stiff as possible, making them choice candidates for high technology applications where the rigidity-density ratio is paramount, such as aerospatial research (https://en.wikipedia.org/wiki/Metallic_microlattice).
For the most part however, metamaterials that have been designed up to now present periodical architectures. As a consequence, their mechanical behavior is inherently anisotropic, which makes them difficult to model using material mechanics conventional approaches, and strongly limits their usage in various possible fields of applications. In recent works, we have developped a new class of microlattice metamaterials with a random spatial distribution of beams, generated with a combination of random close packing and Delaunay triangulation algorithm then 3D-manufactured. These metamaterials show an isotropic mechanical behavior, and their stiffness-density ratio reaches the theoretical limit for porous materials. They are neverheless still fragile and subject to fracture and yielding.
The aim of this PhD project is to toughen these metamaterials based on techniques and mechanisms from polymer and soft matter physics. Our hypothesis is that including in a controlled statistical way structure heterogeneities, at the node level by modulating the connectivity or at the beam level by changing their section or shape, can allow toughening of the metamaterial. Indeed, localized heterogeneities can introduce mechanical dissipations in the network at various scales. The work of this project will consist in experiementally characterizing the mechanical properties of the metamaterials and to compare them to their homogeneous equivalent, and to describe their fracture resistance. Mechanical tests will be performed on an experimental setup conceived in the SPHYNX group. Analysis of the local and global deformation will be performed using different experiemental methods, in order to detect micro crack events with precision. An additionnal theoretical approach completed by numerical simulations based on fuse network and random beam models can also be discussed.
A strong interest for instrumentation and teamwork is requested for this project with a major experimental component. Proficiencies in experimental mechanics, material sciences and/or statistical physics are desirable. Some knowledge in modelization and numerical simulations are a bonus without being required. This project has both fundamental and applied interests and can help the student find prospects both in academia and in industrial opportunities.
Investigation of Lanthanide Salt Interactions with Lipid Systems
Lanthanide–lipid interactions have gained significant attention due to their importance in biophysical and technological applications, including magnetic resonance imaging, fluorescence-based cell labelling and drug delivery. This project aims to investigate the interactions between different lanthanide salts (LnX3, where X = Cl?, ClO4?, NO3?, etc.) and lipid aggregates, focusing on the precipitation and gelation phenomena that occur when their concentration exceeds a certain threshold. Understanding these phenomena is essential for studying self-assembly and phase behaviour in soft matter systems. By examining how lanthanide ions interact with lipid aggregates—particularly in the presence of different anions—this study seeks to elucidate their roles in inducing precipitation and gelation. To this end, a combination of spectroscopic, scattering, microscopy, and rheological techniques will be employed to characterize the molecular interactions in lanthanide–phospholipid systems. These investigations will provide insights into the structural and dynamic properties of such systems and support their application in both biophysical and technological contexts.