Study of the thermomechanical properties of solid hydrogen flows
IRIG's Department of Low Temperature Systems (DSBT) is developing several research themes around cryogenic solid hydrogen and its isotopes. The applications of this research range from the production of renewable micrometre-sized solid hydrogen targets for the generation of high-energy protons for laser-plasma acceleration, to the formation and injection of millimetre- or centimetre-sized hydrogen ice cubes for the supply and control of plasma in fusion reactors using magnetic or inertial confinement. A cross-cutting issue in these applications is the need for a detailed understanding of the mechanical properties of solid hydrogen, in order to gain a better understanding of the physics of extrusion and target production, as well as the formation and acceleration of icicles for injection into fusion plasmas.
The subject of this thesis focuses on the study of solid hydrogen extrusion under pressure. Using this technology, the DSBT has been developing several cryostats for over 10 years, enabling the production of ribbons of solid hydrogen, ranging in size from a few millimetres to a few tens of micrometres, extruded at speeds of a few millimetres per second.
The main objective of the research is to gain a better understanding of extrusion mechanisms to enable the development of numerical predictive tools for extrusion system design. This experimental thesis will be based on cryogenic rheometry using a capillary rheometer and/or a duvet experiment developed during a previous thesis. This study will be carried out in collaboration with the Laboratoire de Rhéologie et Procédés at Grenoble Alpes University.
Towards eco innovative, sustainable and reliable piezoelectric technology
Are you looking for a Phd position at the intersection of eco-innovation and high-tech? This subject is for you!
You will participate in efforts aimed at reducing the environmental footprint of piezoelectric (PZE) technology applied to micro actuators and sensors, while maintaining optimal levels of electrical performance and reliability. Currently PZE technology primarily relies on PZT material (Pb(Zr,Ti)O3) which contains lead, as well as electrodes made from materials such as Pt, Ru, and Au, along with doping elements like La, Mn and Nb to enhance piezoelectric properties and electrical performance. These materials not only come with a significant ecological cost but are also facing proven or imminent shortages. In the context of the necessary frugality associated with the energy transition, this PhD position aims to explore more environmentally friendly and sustainable microsystem technologies. The research will create a comparative analysis assessing the ecological footprint, electromechanical performance, and reliability of existing technologies (with lead) versus those under development (lead free). To achieve these objectives, you will employ Life Cycle Analyses (LCA), electromechanical measurements, and reliability tests (accelerated aging tests).
This interdisciplinary research will encompass fields such as eco design materials science, and microelectronic manufacturing processes You will benefit from the support of laboratories specializing in microsystems manufacturing and integration processes, as well as electrical characterization and reliability Collaboration with the “eco innovation” unit at CEA Leti will also enhance the resources available for this project.
Etude du comportement d'un composite CMC en température par essais in situ en tomographie X
The proposed topic concerns the study of the mechanical behavior of an oxide/oxide ceramic matrix composite material at temperature (up to 1000°C). The originality of the subject lies in the use of in situ X-ray tomography to access, on the one hand, the macroscopic deformation of the tested specimens and, on the other hand, the microscopic damage mechanisms that characterize this type of so-called "damageable" material.
This technique was developed at room temperature during a previous thesis: the aim here is to apply it at higher temperature and to more complex stresses (e.g., traction-torsion). The aim will also be to propose developments to the existing volumetric image correlation analysis protocol.
Out-of-Distribution Detection with Vision Foundation Models and Post-hoc Methods
The thesis focuses on improving the reliability of deep learning models, particularly in detecting out-of-distribution (OoD) samples, which are data points that differ from the training data and can lead to incorrect predictions. This is especially important in critical fields like healthcare and autonomous vehicles, where errors can have serious consequences. The research leverages vision foundation models (VFMs) like CLIP and DINO, which have revolutionized computer vision by enabling learning from limited data. The proposed work aims to develop methods that maintain the robustness of these models during fine-tuning, ensuring they can still effectively detect OoD samples. Additionally, the thesis will explore solutions for handling changing data distributions over time, a common challenge in real-world applications. The expected results include new techniques for OoD detection and adaptive methods for dynamic environments, ultimately enhancing the safety and reliability of AI systems in practical scenarios.
Diamond Beam Monitor for FLASH Therapy
Optimizing tumor dose delivery requires advanced treatment techniques. One promising approach focuses on refining beam delivery through ultra-high dose rate irradiation (UHDR), with temporal optimization being a key strategy. Recent studies highlight the effectiveness of FLASH irradiation using electrons, demonstrating similar tumor inhibition capabilities as gamma rays but with reduced damage to healthy tissue. To fully harness this potential, we are exploring innovative beams, such as high energy electron beams, which offer instantaneous dose rates and per-pulse doses many times higher than those produced by conventional radiation sources. However, accurately monitoring and measuring these beams remains a significant challenge, primarily due to the high dose rate.
The Sensors and Instrumentation Laboratory (CEA-List) will collaborate with the Institut Curie as part of the FRATHEA project. We propose the development of a novel diamond-based monitor, connected to associated electronics, to achieve precise measurements of dose and beam shape for high-rate electron and proton beams. Interdisciplinary experimental techniques, including diamond growth, device microfabrication, device characterization under radioactive sources, and final evaluation with electron beam, will be used for prototyping and testing the diamond beam monitor.
As part of the FRATHEA project, the PhD student will work on the following tasks:
• Growth of optimized single-crystal chemical vapor-deposited (scCVD) diamond structures
• Characterization of the electronic properties of the synthesized diamond materials
• Estimation of the dose response characteristics of a simplified prototypes
• Fabrication of a pixelated beam monitor
• Participation in beam times at the Institut Curie (an other institutes) for devices testing in clinical beams
Required Skills:
• Strong background in semiconductor physics and instrumentation
• Knowledge of radiation detectors and radiation-matter interactions
• Ability to work effectively in a team and demonstrate technical rigor in measurements
Additional Skills:
• Knowledge of electronics, including signal processing, amplifiers, oscilloscopes, etc.
• Familiarity with device fabrication and microelectronics
• Previous experience working with diamond materials
Profile:
• Master's level (M2) or engineering school, with a specialization in physical measurements
• Adherence to radiation protection regulations (category B classification required)
PhD Duration: 3 years
Start Date: Last semester of 2025
Contact:
Michal Pomorski : michal.pomorski@cea.fr
Guillaume Boissonnat: guillaume.boissonnat@cea.fr
Design, fabrication, and characterization of GeSn alloy-based laser sources for mid-infrared silicon photonics
You will design and fabricate laser and LED sources based on GeSn alloy in a cleanroom environment. These novel group-IV direct-bandgap materials, epitaxially grown on 200 mm Si wafers, are considered CMOS-compatible and hold great promise for the development of low-cost mid-infrared light sources. You will characterize these light sources using a mid-infrared optical test bench, with the goal of their future integration into a Germanium/Silicon photonic platform. Additionally, you will assess the feasibility of gas detection within a concentration range from a few dozen to several thousand ppm.
The objectives of the PhD are to:
• Design efficient GeSn (Si) stack structures that confine both electrons and holes while providing strong optical gain.
• Evaluate the optical gain under optical pumping and electrical injection at different strain levels and doping concentrations.
• Design and fabricate laser cavities with strong optical confinement.
• Characterize the fabricated devices under optical and electrical injection as a function of their strain state at both room and low temperatures.
• Achieve electrically pumped continuous-wave group-IV lasers.
• Understand the physical phenomena that may impact the material and device performance for light emission.
• Characterize the best-fabricated devices for low-cost environmental gas detection applications.
This work will involve collaborations with international laboratories working on the same dynamic research topic.
High mobility mobile manipulator control in a dynamic context
The development of mobile manipulators capable of adapting to new conditions is a major step forward in the development of new means of production, whether for industrial or agricultural applications. Such technologies enable repetitive tasks to be carried out with precision and without the constraints of limited workspace. Nevertheless, the efficiency of such robots depends on their adaptation to the variability of the evolutionary context and the task to be performed. This thesis therefore proposes to design mechanisms for adapting the sensory-motor behaviors of this type of robot, in order to ensure that their actions are appropriate to the situation. It envisages extending the reconfiguration capabilities of perception and control approaches through the contribution of Artificial Intelligence, here understood in the sense of deep learning. The aim is to develop new decision-making architectures capable of optimizing robotic behaviors for mobile handling in changing contexts (notably indoor-outdoor), and for carrying out a range of precision tasks.
Implicit/explicit transition for numerical simulation of Fluid-Structure Interaction problems treated by immersed boundary techniques
In many industrial sectors, rapid transient phenomena are involved in accident scenarios. An example in the nuclear industry is the Loss of Primary Coolant Accident, in which an expansion wave propagates through the primary circuit of a Pressurized Water Reactor, potentially vaporizing the primary fluid and causing structural damage. Nowadays, the simulation of these fast transient phenomena relies mainly on "explicit" time integration algorithms, as they enable robust and efficient treatment of these problems, which are generally highly non-linear. Unfortunately, because of the stability constraints imposed on time steps, these approaches struggle to calculate steady-state regimes. Faced with this difficulty, in many cases, the kinematic quantities and internal stresses of the steady state of the system under consideration at the time of occurrence of the simulated transient phenomenon are neglected.
Furthermore, the applications in question involve solid structures interacting with the fluid, undergoing large-scale deformation and possibly fragmenting. A immersed boundary technique known as MBM (Mediating Body Method [1]) recently developed at the CEA enables structures with complex geometries and/or undergoing large deformations to be processed efficiently and robustly. However, this coupling between fluid and solid structure has only been considered in the context of "fast" transient phenomena treated by "explicit" time integrators.
The final objective of the proposed thesis is to carry out a nominal regime calculation followed by a transient calculation in a context of fluid/immersed-structure interaction. The transient phase of the calculation is necessarily based on "explicit" time integration and involves the MBM fluid/structure interaction technique. In order to minimize numerical disturbances during the transition between nominal and transient regimes, the calculation of the nominal regime should be based on the same numerical model as the transient calculation, and therefore also rely on an adaptation of the MBM method.
Recent work defined an efficient and robust strategy for calculating steady states for compressible flows, based on "implicit" time integration. However, although generic, this approach has so far only been tested in the case of perfect gases, and in the absence of viscosity.
On the basis of this initial work, the main technical challenges of this thesis are 1) to validate and possibly adapt the methodology for more complex fluids (in particular water), 2) to introduce and adapt the MBM method for fluid-structure interaction in this steady-state calculation strategy, 3) to introduce fluid viscosity, in particular within the framework of the MBM method initially developed for non-viscous fluids. At the end of this work, implicit/explicit transition demonstration calculations with fluid-structure interaction will be implemented and analyzed.
An internship can be arranged in preparation for thesis work, depending on the candidate's wishes.
[1] Jamond, O., & Beccantini, A. (2019). An embedded boundary method for an inviscid compressible flow coupled to deformable thin structures: The mediating body method. International Journal for Numerical Methods in Engineering, 119(5), 305-333.
Modelling/Simulation of the synthesis of anti-corrosion coatings using the MOCVD process for low-carbon energy production
The durability of materials used in many areas of energy production is limited by their degradation in the operating environment, which is often oxidising and at high temperature. This is particularly true of High Temperature Electrolysers (HTE) for the production of ‘green’ hydrogen, or the fuel cladding used in nuclear reactors to produce electricity. Anti-corrosion coatings can/should be applied to improve the lifespan of these installations, thereby conserving resources. A process for synthesising coatings using a reactive vapour route with liquid organometallic precursors (DLI - MOCVD) appears to be a very promising process.
The aim of this thesis is to model and simulate the DLI-MOCVD coating synthesis process for the two applications proposed above. Simulation results (deposition rate, deposit composition, spatial homogeneity) will be compared with experimental results from large-scale ‘pilot’ reactors at the CEA in order to optimise the model's input parameters. On the basis of this CFD simulation/experiments dialogue, the optimum conditions for deposition on a scale 1 component will be proposed. A coupling between CFD simulations and Machine Learning will be developed to accelerate the change of scale and the optimisation of scale 1 deposits.