Investigation and Modeling of Ferroelectric and Antiferroelectric Domain Dynamics in HfO2-Based Capacitors
The proposed PhD work lies within the exploration of new supercapacitor and hybrid energy storage technologies, aiming to combine miniaturization, high power density, and CMOS process compatibility. The hosting laboratory (LTEI/DCOS/LCRE) has recognized expertise in thin-film integration and dielectric material engineering, offering unique opportunities to investigate ferroelectric (FE) and antiferroelectric (AFE) behaviors in doped hafnium oxide (HfO2).
The thesis will focus on the experimental investigation and physical modeling of thin-film HfO2-based capacitors, intentionally doped to exhibit ferroelectric or antiferroelectric properties depending on the composition and deposition conditions (for instance, through ZrO2 or SiO2 doping). Such materials are particularly attractive for realizing devices that combine non-volatile memory and energy storage functions on a single CMOS-compatible platform, enabling ultra-low-power autonomous systems such as edge computing architectures, environmental sensors, and smart connected objects.
The research will involve the fabrication and characterization of metal–insulator–metal (MIM) capacitors based on doped HfO2 integrated on silicon substrates. Systematic electrical measurements—including current–voltage (I–V) and polarization–electric field (P–E) characterizations—will be carried out under various frequencies, amplitudes, and cycling conditions to investigate the relaxation mechanisms of FE and AFE domains. Analysis of minor hysteresis loops will provide access to the distribution of activation energies and enable the modeling of domain relaxation dynamics. A physical model will be developed or refined to describe FE/AFE transitions under cyclic electrical excitation, incorporating effects such as charge trapping, mechanical stress, and domain nucleation kinetics.
The overall objective is to optimize the recoverable energy density and the energy conversion efficiency of these capacitors, while establishing design guidelines for compact, efficient, and silicon-integrable energy storage devices. The insights gained from this work will contribute to a deeper understanding of the dynamic mechanisms governing FE/AFE behavior in doped HfO2, with potential impact on ferroelectric memories, energy-harvesting devices, and low-power neuromorphic architectures.
Plasma real time control by calorimetry
Inside thermonuclear fusion devices, plasma facing components are subject to intense heat fluxes. The WEST tokamak has water cooled plasma facing components to limit their heating. Calorimetric measurement on these components allows for the measurement of the power received by each component. This makes it possible to control the plasma position or the additional plasma heating in function of the power distribution.
During this PhD, a simulation of plasma control using calorimetry will be performed, simulating the heat fluxes received by the components as a function of the plasma position and the associated calorimetric response. In-situ calorimetric measurements will be carried out on the components at the top and bottom of the machine during dedicated plasma experiments to refine the simulations and the control of the WEST plasma position based on calorimetric measurements will finally be implemented and validated during dedicated experiments, for plasma-facing components protection and plasma physics purposes.
Real-Time control of MHD instabilities during WEST long pulses
In magnetically confined plasmas, low-frequency (typ. 1-10 kHz) large-scale magnetohydrodynamic (MHD) instabilities represent a risk for performance and plasma stability. During long pulses in the WEST tokamak, deleterious MHD modes appear frequently inducing a drop of central temperature and a higher plasma resistivity that result in lower performances and shorter discharge duration. The real-time detection of such instabilities and the application of mitigation strategies is therefore of great importance for plasma control in WEST but also for future devices like ITER.
These MHD instabilities induce coherent temperature/density perturbations. Instruments like Electron Cyclotron Emission (ECE) radiometer or reflectometrer provide localized, high time resolution of temperature or density fluctuations. However, MHD analysis is currently performed offline, after the discharge. Real-time capability is crucial for control applications. The modes must first be identified before applying a mitigation strategy based on the knowledge of the MHD stability criteria. MHD stability is strongly affected by local heating and current drive, for which Electron Cyclotron Resonance Heating and Current Drive systems (ECRH/ECCD) are especially well suited.
The objective of this PhD is to develop a control strategy for WEST long pulse operation. The first step is the real-time detection of low frequency MHD instabilities using first ECE radiometer, then adding instruments like ECE-imaging or reflectometry to enhance reliability and accuracy. Integrated plasma modelling will then be performed to explore MHD mitigation strategies. ECCD is an obvious actuator, but other tools such as a temporary change of the plasma parameters (current, density or temperature) will also be evaluated. The mitigation strategy will be integrated in WEST Plasma Control System. Initial strategy will rely on simple control loop, then Neural Network or deep-leaning algorithms will be tested.
Physical-attack-assisted cryptanalysis for error-correcting code-based schemes
The security assessment of post-quantum cryptography, from the perspective of physical attacks, has been extensively studied in the literature, particularly with regard to the ML-KEM and ML-DSA standards, which are based on Euclidean lattices. Furthermore, in March 2025, the HQC scheme, based on error-correcting codes, was standardized as an alternative key encapsulation mechanism to ML-KEM. Recently, Soft-Analytical Side-Channel Attacks (SASCA) have been used on a wide variety of algorithms to combine information related to intermediate variables in order to trace back to the secret, providing a form of “correction” to the uncertainty associated with profiled attacks. SASCA is based on probabilistic models called “factor graphs,” to which a “belief propagation” algorithm is applied. In the case of attacks on post-quantum cryptosystems, it is theoretically possible to use the underlying mathematical structure to process the output of a SASCA attack in the form of cryptanalysis. This has been demonstrated, for example, on ML-KEM. The objective of this thesis is to develop a methodology and the necessary tools for cryptanalysis and residual complexity calculation for cryptography based on error-correcting codes. These tools will need to take into account information (“hints”) obtained from a physical attack. A second part of the thesis will be to study the impact that this type of tool can have on the design of countermeasures.
Development of machine learning algorithms to improve image acquisition and processing in radiological imaging
The Nuclear Measurements Laboratory at the LNPA (Laboratory for the Study of Digital Technologies and Advanced Processes) in Marcoule consists of a team specializing in nuclear measurements in the field. Its activities are divided between developing measurement systems and providing technical expertise to CEA facilities and external partners (ORANO, EDF, IAEA).
The LNPA has been developing and using radiological imagers (gamma and alpha) for several years. Some of the developments have resulted in industrial products, while other imagers are still being developed and improved. Alpha imaging, in particular, is a process that allows alpha contamination zones to be detected remotely. Locating the alpha source is an important step in glove boxes, whether for a cleanup and dismantling project, for maintenance during operation, or for the radiation protection of workers. The alpha camera is the tool that makes alpha mapping accessible remotely and from outside glove boxes.
The objective of the thesis is to develop and implement mathematical prediction and denoising solutions to improve the acquisition and post-processing of radiological images, and in particular alpha camera images.
Two main areas of research will be explored in depth:
- The development of real-time or post-processing image denoising algorithms
- The development of predictive algorithms to generate high-statistics images based on samples of real images.
To do this, an experimental and simulation database will be established to feed the AI algorithms.
These two areas of research will be brought to fruition through the creation of a prototype imager incorporating machine learning capabilities and an image acquisition and processing interface, which will be used in an experimental implementation.
Through this thesis, students will gain solid knowledge of nuclear measurements, radiation/matter interaction, and scientific image processing, and will develop a clear understanding of radiological requirements in the context of remediation/decommissioning projects.
Methods for the Rapid Detection of Gravitational Events from LISA Data
The thesis focuses on the development of rapid analysis methods for the detection and characterization of gravitational waves, particularly in the context of the upcoming LISA (Laser Interferometer Space Antenna) space mission planned by ESA around 2035. Data analysis involves several stages, one of the first being the rapid analysis “pipeline,” whose role is to detect new events and to characterize them. The final aspect concerns the rapid estimation of the sky position of the gravitational wave source and their characteristic time, such as the coalescence time in the case of black hole mergers. These analysis tools constitute the low-latency analysis pipeline.
Beyond its value for LISA, this pipeline also plays a crucial role in the rapid follow-up of events detected by electromagnetic observations (ground or space-based observatories, from radio waves to gamma rays). While fast analysis methods have been developed for ground-based interferometers, the case of space-borne interferometers such as LISA remains an area to be explored. Thus, a tailored data processing method will have to consider the packet-based data transmission mode, requiring event detection from incomplete data. From data affected by artifacts such as glitches, these methods must enable the detection, discrimination, and analysis of various sources.
In this thesis, we propose to develop a robust and effective method for the early detection of massive black hole binaries (MBHBs). This method should accommodate the data flow expected for LISA, process potential artifacts (e.g., non-stationary noise and glitches), and allow the generation of alerts, including a detection confidence index and a first estimate of the source parameters (coalescence time, sky position, and binary mass); such a rapid initial estimate is essential for optimally initializing a more accurate and computationally expensive parameter estimation.
Multi-criteria Navigation of a Mobile Agent applied to nuclear investigation robotics
Mobile robots are increasingly deployed in hazardous or inaccessible environments to perform inspection, intervention, and data collection tasks. However, navigating such environments is far more complex than simple obstacle avoidance: robots must also deal with communication blackouts, contamination risks, limited onboard energy, and incomplete or evolving maps. A previous PhD project (2023–2026) introduced a multi-criteria navigation framework based on layered environmental mapping and weighted decision aggregation, demonstrating its feasibility in simulated, static scenarios.
The proposed thesis aims to extend this approach to dynamic and partially unknown environments, enabling real-time adaptive decision-making. The work will rely on tools from mobile robotics, data fusion, and autonomous planning, supported by experimental facilities that allow realistic validation. The objective is to bring navigation strategies closer to real operational conditions encountered in nuclear dismantling sites and other industrial environments where human intervention is risky. The doctoral candidate will benefit from an active research environment, multidisciplinary collaborations, and strong career opportunities in autonomous robotics and safety-critical intervention systems.
Turbulence synthetization methods in porous media from detailed simulations for multi-scale simulations of nuclear cores
The production of electricity through nuclear energy plays a crucial role in the energy transition due to its low carbon impact. To continuously improve safety and performance, it is essential to develop new knowledge and tools.
The core of a nuclear reactor consists of thousands of fuel rods traversed by a turbulent flow. This flow can cause vibrations, leading to wear. Two flow scales are identified: a local scale, where the fluid interacts with the rods, and a global scale, representing the flow distribution within the core. The local scale requires CFD simulations and fluid-structure coupling, while the global scale can be modeled using averaged approaches, such as porous media simulations.
Coupled fluid-structure interaction (FSI) simulations at the CFD scale are limited to small domains. To overcome this limitation, multi-scale approaches are required, combining large-scale porous media simulations and detailed small-scale CFD simulations. The goal of the thesis is to develop methods for synthesizing turbulence from the results of porous media simulations to improve boundary conditions for CFD simulations. The candidate will first study how existing turbulence models can provide details on turbulent flow at the component scale, and then how to synthesize turbulence for local CFD simulations.
This PhD project is the subject of a collaboration between the IRESNE Institute (CEA) and the ASNR (main execution site of the thesis) in Cadarache. Funding is provided by a MSCA Doctoral Network. The PhD student will be integrated into a network of 17 PhD students. To be eligible, the candidate must have resided no more than 12 months in the last 36 months in France.
Characterisation of reaction pathways leading to thermal runaway for new battery technologies
The development of all-solid-state cells is no longer a mere hypothesis today. As part of the Safelimove project, we assessed the safety of hybrid polymer cells of 1 Ah and 3 Ah, which led to a publication. Additionally, within the Sublime project, we evaluated the safety of 1 Ah sulfide-based cells (argyrodite), and a publication is currently being submitted.
With the arrival of these new cells, it becomes even more crucial to support their development with a detailed safety assessment and the identification of the complex mechanisms involved. Large-scale instruments such as synchrotrons and neutron reactors offer a powerful opportunity to achieve this goal, as they provide the best spatial and temporal resolutions. For example, thanks to fast X-ray radiography at ESRF, it is possible to visualize the inside of a cell during thermal runaway, thereby identifying the local impact of (electro)chemical reactions on the microstructure of components and validating our thermal runaway models. Moreover, with wide-angle X-ray scattering (WAXS), it is possible to monitor in situ the evolution of the crystalline structure of active materials during a very rapid thermal runaway reaction. Indeed, synchrotron radiation allows the acquisition of one diffractogram every 3 milliseconds. The neutron beam at ILL also enables us to track the evolution of lithium metal structure before, during, and after runaway. It is important to emphasize that these three techniques are currently mastered by the LAPS teams and have already led, or will lead, to publications.
Furthermore, new complementary techniques may be explored, such as studying the impact of thermal/mechanical stress on active materials using the BM32 beamline, or evaluating the oxidation states of metals via X-ray absorption spectroscopy (XAS) on ID26.
More conventional laboratory characterizations will also be carried out, such as DSC, TGA-MS, and XRD.
As part of our various collaborations, for the all-solid-state system, the active material of the positive electrode will most likely be NMC, or even LMFP in the event of supply difficulties. The electrolyte used will be sulphide-based, or even halide-based, while the anode will be composed of lithium metal or even a lithium alloy. If time permits, a post-Na-ion system will be considered from the second year onwards. Among other things, the thesis will aim to identify, based on the materials used, whether there are reactions prior to cathode destabilisation, whether the solid electrolyte reacts with the oxygen in the cathode or with the anode material, and whether these parallel reactions contribute to better or worse cell safety.
The three years of the PhD will be structured as follows: the first year will be dedicated to a literature review and the characterization of sulfide technology. Following the first milestones (1st CSI) and the evaluation of ongoing work on sulfides, the second year will focus either on sodium-ion technology or on further development of sulfide technology. Finally, the third year, in addition to the thesis writing, will concentrate more specifically on the impact of the identified materials on safety.
Direct lithium extraction from brine through adsorption
The development of electric vehicles due to climate and the decision to turn towards a greener energy has increased sharply the demand of lithium over the past decade and will continue to escalate. Thus, lithium extraction projects are proliferating worldwide. Since mining presents a quite highly energy-consuming and polluting solution, alternative lithium sources like brine deposits or seawater are being currently investigated. In this study, we will focus on the approach of a direct lithium extraction from brine sources with different concentrations by adsorption. The first step will be to synthesize and characterize a wide range of materials as adsorbents, from classic oxides (LMO, LTO, etc) to functionalized hybrid porous materials (ZIFs, MOFs, etc). It is also intended to shape these materials with the help of an extruder, in order to enhance performances. Then, these materials will be evaluated both in static and dynamic conditions. Various parameters like the concentration of lithium, the presence of other cations and their concentration will be also evaluated and optimized so that we obtain a facile, efficient and selective process. The results of this study will be valorized through the deposit of patents and the submission of scientific articles along the whole duration of the thesis.