Plasma Mirrors: towards extreme intensity light sources and high-quality compact electron
Research objectives:
expand the capabilities of the WarpX Partice-In-Cell code for lower cost-to-convergence using mesh refinement.
Devise a high-charge high quality injector for laser-plasma accelerators.
Determine feasibility of the proposed scheme on a 100-TW-class laser system.
The researcher will benefit from a large variety of training available at CEA on HPC and computer programming as well as training at our industrial partners (ARM, Eviden) and Université Paris Saclay. The activities will be carried out in the framework of the Marie Sklodowska Curie Action Doctoral Network EPACE (European compact accelerators, their applications, and entrepreneurship)
Electrocatalyzed Reductive Couplings of Olefins and Carbonyls for the synthesis of sustainable molecules.
The LCMCE aims to develop a sustainable method for the reductive functionalization of carbonyl derivatives with olefins via electrochemistry. Traditional redox processes in organic synthesis often rely on thermochemical methods using stoichiometric oxidants or reductants and produce waste products. The electrification of these processes will improve their atom- and energy economy. The novelty of this project lies in the generation of "metal-hydride" catalytic species by cathodic reduction of organometallic complexes in the presence of protons rather than by adding chemical reductants, as described in the literature. Inserting an alkene function into the metal-hydride bond will lead to the formation of reactive intermediates for coupling with electrophilic carbonyls. The substrates for this project have been selected to provide rapid proof of concept and allow the study of more ambitious reactivities, including carboxylation reactions in which CO2 is the electrophile. Particular attention will be paid to the design of homogeneous catalysts and their synergy with electrochemical conditions to lead to active and selective species. The project will also focus on deciphering the mechanisms involved in these reactions.
Theoretical design of quasi-atomic systems in the band gap of semiconductors/insulators for quantum application
The rise of room-temperature applications like single photon emission of the negatively charged nitrogen-vacancy NV center in diamond has renewed the interest in the search for materials having a quasi-atomic system QAS analogous to that of NV, mainly characterized by the presence of well localized in-gap defect levels generate occupied by electrons and leading to high spin states. In this Ph.D. work, theoretical methods will be used to design new QASs analogous to the NV center as well as, in selected QAS, to predict charge states and explore the effect of the proximity of the surface on the thermodynamic stability and on the spin state structure. The objectives are to design new QASs; To predict charge states of selected QASs in the bulk of the host material; To study changes in the charge state brought by the proximity of the surface; To extend the Hubbard model used to compute the excited states and to account for the electron-lattice interaction in the calculation of the excited states; To study the effect of the presence of deep level states in the band gap on the transport of electrons and phonons. The methodology developed at LSI to design new QASs with high spin states will be exploited and new systems analogous to the NV center will be looked for. Density functional theory (DFT) and a Hubbard model developed at LSI will be the main tools of this PhD.
Porphyrin-based nanostructures
The aim of this project is the synthesis of new molecular structures based on porphyrins for the formation of 0D, 1D and 2D nanostructures. Porphyrins are an important class of molecules that are essential to life through oxygen transport or photosynthesis. Beyond, their importance in Nature, porphyrin derivatives exhibit outstanding optical, electronic, chemical and electrochemical properties that make them promising candidates for applications in catalysis, electrocatalysis, optoelectronics and medicine.
In this project, the porphyrins will be studied in collaboration with several groups of Physicists in order to fabricate 1D or 2D covalent networks on surface via the "bottom-up" approach and to study their electronic and optical properties.
Interfaces in super-concentrated aqueous electrolytes: machine learned simulations at the exascale era
Improving the performance of liquid electrolytes is one of today's major challenges in the field of batteries, with the aim of improving efficiency, safety and economy. Recent advances include superconcentrated media such as WIS (“Water-In-Salts”) solutions. Their properties depend crucially on the chemistry and physics of the interfaces between water and ions (Li+ for lithium-ion batteries, but also Na+, K+, Zn2+), both at a distance and close to the electrodes.
Atomic-scale modeling of these superconcentrated liquid electrolytes requires the study of nanoscopic structures and phenomena taking place over long timescales. One relevant solution is to build potentials by machine learning, based on ab initio molecular dynamics (AIMD) trajectories. This method combines an accurate description of the interactions between ions and water molecules, including the breaking and forming of chemical bonds, with fast calculation speed. In particular, the DeePMD kit has recently been successfully ported to GPU architectures, paving the way for calculations on exascale supercomputers (whose power exceeds 10^18 floating-point operations per second).
This theoretical study will be supported by an experimental counterpart, thanks to direct collaboration with a team in the unit specializing in electrochemistry.
Spectrometry and Artificial Intelligence: development of explainable, sober and reliable AI models for materials analysis
The discovery of new materials is crucial to meeting many current societal challenges. One of the pillars of this discovery capacity is to have means of characterizing these materials which are rapid, reliable and whose measurement uncertainties are qualified, even quantified.
This PhD project is part of this approach and aims to significantly improve the different ion beam induced spectrometry (IBA) techniques using advanced artificial intelligence (AI) methods. This project aims to develop explainable, sober and reliable AI models for materials analysis.
The PhD project proposed here has three main objectives:
- Develop an uncertainty model using probabilistic machine learning techniques in order to quantify the uncertainties associated with a prediction.
- Due to the very large number of possible combinatory-generated configurations, it is important to understand the intrinsic dimensionality of the problem. We wish to implement means of massive dimensionality reduction, in particular non-linear methods such as autoencoders, as well as PIML (Physics Informed Machine Learning) concepts.
- Evaluate the possibility of generalization of this methodology to other spectroscopic techniques.
X-ray diffusion assisted by Artificial Intelligence: the problem of the representativeness of synthetic databases and the indistinguishability of predictions.
The advent of artificial intelligence makes it possible to accelerate and democratize the processing of small-angle X-ray scattering (SAXS) data, an expert technique for characterizing nanomaterials that allows to determine the specific surface area, volume fraction and characteristic sizes of structures between 0.5 to 200 nm.
However, there is a double problem around SAXS assisted by Artificial Intelligence: 1) the scarcity of data requires training the models on synthetic data, which poses the problem of their representativeness of real data, and 2) the laws of physics stipulate that several candidate nanostructures can correspond to a SAXS measurement, which poses the problem of the indistinguishability of predictions. This thesis therefore aims to build an artificial intelligence model adapted to SAXS trained on experimentally validated synthetic data, and on the expert response which weights the categorization of predictions by their indistinguishability.
Fluorescence photoswitching for excitonic gate
Förster Resonance Energy Transfer (FRET) enables the exciton diffusion between molecules through a characteristic distance of 1 to 10 nm. The association of multiple fluorophores represents a solution to facilitate exciton diffusion over a longer range, taking profit of homo-FRET and hetero-FRET phenomena. FRET is a fundamental aspect in the development of photo-switchable luminescent devices. At the molecular level, the design of photo-switchable systems relies on the association of two components: a luminescent material and a photochromic compound. The formation of nano-objects with similar molecules leads to intriguing responses in fluorescence and photochromic behavior due to multiple energy transfers. However, these systems are poorly used in molecular logic, and they switch between bright and dark states. Considering an emissive acceptor (a second bright state) would allow exciton diffusion over longer distances and enable its detection.
The FLUOGATE project objective is the preparation and characterization of photoswitchable luminescent molecular nanostructures that behaves as an excitonic gate. The initial step is the preparation and study of 2D photoswitchable monolayers with controlled organization. The combination of optical and local probe measurements will permit the characterization of fluorescence photoswitching following the structural change at the single molecule scale and determination of the quenching radius. Then, the preparation and study of 3D architectures will be undertaken. The strategy entails the successive deposition of various dyes. Layers of the donor fluorophore will be deposited just above the substrate, followed by layers of the photochromic compound and finally layers of the acceptor fluorophore. The ultimate goal will consist in exploring the replacement of the photochromic layer by a photochromic nanoparticle in a polymer matrix.
Chemical recycling of oxgenated and nitrogenated plastic waste by reductive catalytic routes
Since the 1950s, the use of petroleum-based plastics has created a modern consumerist world based on the use of disposable products. Global production of plastic waste is therefore considerable, and has almost doubled 20 years, now reaching 468 million tons/year. This non-biodegradable plastic waste causes a great deal of environmental pollution (disturbance of flora and fauna, water and soil pollution, etc.). Barely 9% of this waste is recycled, the rest being burnt or landfilled. The health, climate and social problems inherent in this linear economy mean that we need to create a circularity for these materials by developing effective and robust recycling routes. While current recycling methods rely mainly on mechanical processes and are limited to specific types of waste (e.g. plastic water bottles), the development of chemical recycling methods seems promising for treating waste for which there are no recycling channels. Such chemical processes make it possible to recover the carbonaceous matter in plastics in order to regenerate new plastics.
Within this objective of material circularity, this doctoral project aims to develop new chemical recycling routes for mixed oxygen/nitrogen plastic waste such as polyurethanes (insulation foam, mattresses, etc.) and polyamides (textile fibres, circuit breaker boxes, etc.), for which recycling routes are virtually non-existent. This project is based on a strategy of depolymerizing these plastics by the selective cleavage of the carbon-oxygen and/or carbon-nitrogen bonds to form the corresponding monomers or their derivatives. To do that, catalytic systems involving metal catalysts coupled with abundant and inexpensive reducing agents, such as alcohols and formic acid, will be developed. The use of dihydrogen, an industrial reducing agent, will also be considered. In order to optimize these catalytic systems, we will seek to understand how they proceed and the mechanisms involved.
Early diagnosis of sepsis using a GMR sensor-based biochip
Sepsis, an extreme and deregulated immune response to an infection that then spreads through the bloodstream, can lead to organ dysfunction and death (11 million deaths worldwide every year). The patented GMR (Giant MagnetoResistance) sensor-based biochip we have developed has real potential for the early detection of pathogens involved in sepsis or biomarkers of the disease, present in very small quantities in the blood, without the need for a culture step. The innovative approach we are proposing is cross-disciplinary, since it is based on the use of magnetic nanoparticles (NPM), functionalized by monoclonal antibodies produced in the LERI laboratory, directed against target biological objects (cells, bacteria, yeasts, etc.) which are detected dynamically and simultaneously one by one by GMR sensors arranged on either side of a microfluidic channel in which they flow. Proof of concept for this biochip was obtained on a murine myeloma cell model.We were able to achieve a sensitivity and specificity with this model that makes our technique highly competitive with existing Point-of-Care tests. However, we still need to validate these results on pathogens.
During the course of the thesis, two objectives will be defined. Following on from the current thesis, the first objective of the student at the LNO will be to adapt the biochip (sensors, microfluidics and signal processing) so that it is sensitive and rapid for the detection of bacteria and yeasts involved in sepsis in blood samples. At LERI, he will optimize the magnetic labeling of bacteria and yeasts in this clinical matrix using commercial NPM functionalized with one or more antibodies directed against the target. This stage of the thesis will be carried out in close collaboration with the Service de Bactériologie et Hygiène at Hôpital Béclère (also a member of the IHU), which will recommend and supply relevant bacterial and yeast strains for detection, as well as clinical samples.One of the GMR biochips will be installed at Hôpital Béclère for measurements under real-life conditions. The second objective will be to use the GMR biochip to quantify the reduction in monocyte expression of mHLA-DR molecules, which is an indicator of the immunosuppressed state of sepsis associated with increased infectious risk and mortality.