In-situ measurement of liquid composition by digital in-line holography

This postdoctoral position is part of the ANR ATICS project (Advanced Tri-dimensional Imaging of Complex Particulate Systems), which aims to develop a set of advanced tools and methods for modeling and reconstructing holograms to enhance the practical capabilities of three-dimensional imaging through digital inline holography. This is a collaborative research project lasting four years, involving four university laboratories, the CNRS, grandes écoles, and the CEA. Within this framework, the objective of the postdoctoral work is to provide physical knowledge and data to other team members and to demonstrate the contributions of the theoretical and numerical developments made in ATICS in two research areas in which the partners are regularly involved: multiphase flows and recycling processes. To achieve this, new experimental devices for measuring the composition of liquids will be developed, leveraging the potential of inline digital holography at various scales, from microfluidics to the study of sprays in acoustic levitation. The work will be conducted in close collaboration with the teams at the IUSTI laboratory of Aix-Marseille University.

Dimensionality reduction and meta-modelling in the field of atmospheric dispersion

Modelling and simulation of atmospheric dispersion are essential to ensure the safety of emissions emitted into the air by the authorized operation of industrial facilities and to estimate the health consequences of accidents that could affect these facilities. Over the past twenty years, physical dispersion models have undergone significant improvements in order to take into account the details of topography and land use that make real industrial environments complex. Although 3D models have seen their use increase, they have very significant calculation times, which hinders their use in multi-parametric studies and the assessment of uncertainties that require a large number of calculations. It would therefore be desirable to obtain the very precise results of current models or similar results in a much shorter time. Recently, we have developed a strategy consisting of reducing the dimension of distribution maps of an atmospheric pollutant obtained using a reference 3D physical model for different meteorological conditions, then having these maps learned by an artificial intelligence (AI) model which is then used to predict maps in other meteorological situations. The postdoctoral project will focus on complementing the research started by evaluating the performance of dimension reduction and model substitution methods already explored and by studying other methods. Applications will concern, in particular, the simulation of concentrations around an industrial production site that emits gaseous emissions into the atmosphere. The developments will aim to obtain an operational meta-modelling tool.

Signal processing of ultra-fast gamma-ray detectors using Machine Learning

In the frame of the ANR project AAIMME dedicated to the Positron-Emission Tomography (PET), we propose a 24-month post-doctoral position that will focus on the development of signal processing methods for the detector ClearMind, designed at the CEA-IRFU. The detector is specifically developed to provide a precise interaction time in the sensitive volume. It consists of a scintillator PbWO4 detector, coupling with a Micro Channel Plate PhotoMultiplier Tube, whose signals are digitized using fast acquisition modules SAMPIC. The main advantage is to exploit both fast Tcherenkov and scintillation photons to reconstruct as accurately as possible the interactions inside the Crystal.
The analysis of the detector signal represents a major challenge: they are complex and intricated, thus, it necessitates a dedicated processing step.
The objective of this post-doc is to develop these trustworthy Machine Learning algorithms to reconstruct the properties of the gamma-ray interaction in the detector, with the highest achievable accuracy, using the detector signals.

Comparison of Diamond and vertical GaN technologies to SiC and Si for power applications

Power devices based on wide band gap semiconductors are increasingly being studied and adopted in commercial products, driven by the electrification of our societies. Among these wide band gap devices, SiC-based technologies are the most mature, at the industrial production stage. Other materials are being studied to achieve higher performance, in particular diamond, whose intrinsic physical properties offer great potential, as well as GaN components in a vertical architecture. However, the real benefits of these materials compared with existing Si or SiC solutions have not been clearly demonstrated and might strongly depend on the applications considered. The aim of this project is to identify one or more applications where vertical GaN and diamond technologies are likely to bring significant benefits, taking into account the current and/or projected market for these applications. Then, using TCAD and SPICE simulations as well as experimental test device characterizations, we will compare the estimated performance of industrially viable diamond and GaN components, designed for these applications, with that of SiC and Si.

High-performance computing using CMOS technology at cryogenic temperature

Advances in materials, transistor architectures, and lithography technologies have enabled exponential growth in the performance and energy efficiency of integrated circuits. New research directions, including operation at cryogenic temperatures, could lead to further progress. Cryogenic electronics, essential for manipulating qubits at very low temperatures, is rapidly developing. Processors operating at 4.2 K using 1.4 zJ per operation have been proposed, based on superconducting electronics. Another approach involves creating very fast sequential processors using specific technologies and low temperatures, reducing energy dissipation but requiring cooling. At low temperatures, the performance of advanced CMOS transistors increases, allowing operation at lower voltages and higher operating frequencies. This could improve the sequential efficiency of computers and simplify the parallelization of software code. However, materials and component architectures need to be rethought to maximize the benefits of low temperatures. The post-doctoral project aims to determine whether cryogenic temperatures offer sufficient performance gains for CMOS or should be viewed as a catalyst for new high-performance computing technologies. The goal is particularly to assess the increase in processing speed with conventional silicon components at low temperatures, integrating measurements and simulations.

Multi-objective topological optimization in nonlinear mechanics

The CEA-Cesta aims at developing topological optimization tools with performances that are not achievable by commercial software. As part of this post-doc, it will be a question of taking advantage of a collaboration initiated in the LRC Cosims (I2M-Arts et métiers Bordeaux) to progress on the subject, to develop innovative optimization methods in the field of non-linear mechanics. Two application test cases are envisaged:
- Topological optimization of two geometric structures of very different shapes;
- Optimization of a structuring spring.

Adapting the Delayed Hydride Cracking (DHC) experience to irradiated materials

The objective of this study is to nuclearize the Delayed Hydride Cracking (DHC) experiment developed as part of Pierrick FRANCOIS PhD research (2020-2023). This experiment enables the reproduction of the DHC phenomenon in Zircaloy cladding under laboratory conditions to determine the material's fracture toughness in case of DHC: KI_DHC.
The term "nuclearize" refers to the adaptation of the experiment to test irradiated materials within dedicated shielded enclosures (called hot cells), where materials are handled using remote manipulators. The experimental protocols described in Pierrick FRANCOIS' thesis must therefore be modified, and ideally simplified, to allow for their implementation in hot cells. This will require close collaboration with the personnel responsible for the tests and the use of numerical simulation tools developed during the same PhD research.
The development of this hot cell procedure will be used by the postdoctoral researcher to assess the risk of HC during dry storage of spent fuel assemblies by quantifying the fracture toughness of irradiated claddings.

Design and Implementation of a Neural Network for Thermo-Mechanical Simulation in Additive Manufacturing

The WAAM (Wire Arc Additive Manufacturing) process is a metal additive manufacturing method that allows for the production of large parts with a high deposition rate. However, this process results in highly stressed and deformed parts, making it complex to predict their geometric and mechanical characteristics. Thermomechanical modeling is crucial for predicting these deformations, but it requires significant computational resources and long calculation times. The NEUROWAAM project aims to develop a precise and fast thermomechanical numerical model using neural networks to predict the physical phenomena of the WAAM process. An internship in 2025 will provide a database through thermomechanical simulations using the CAST3M software. The post-doc's objective is to develop a neural network architecture capable of learning the relationship between the manufacturing configuration and the thermomechanical characteristics of the parts. Manufacturing tests on the CEA's PRISMA platform will be conducted to validate the model and prepare a feedback loop. The CEA List's Interactive Simulation Laboratory will contribute its expertise in accelerating simulations through neural networks and active learning to reduce training time.

Aerosol generation and transformation mechanisms during the fuel debris cutting at Fukushima Daiichi future dismantling

During Fukushima Daiichi nuclear reactor accident, several hundred tons of fuel debris (the mixture generated by the reactor core melting and its interaction with structural materials) have been formed. Japanese government plans to dismantle with 30 to 40 years Fukushima Daiichi nuclear power station, which implies recovering these fuel debris that are there. CEA is part to several projects aiming at mastering the risks due to aerosols generated during fuel debris cutting.
The post-doctoral work objective is to exploit the large experimental database created thanks to these projects in order to study the generation and transformation mechanisms of these cutting aerosols for both thermal and mechanical cutting. An important source of aerosol seems to be partial evaporation/condensation, close to fractional distillation. A thermodynamic modelling shall be proposed, coupled with some kinetic effects. For mechanical cutting, aerosol analyses shall be compared to fuel debris block microstructure to quantify a preferential release of some phases.
After a bibliographic study, a synthesis of the experimental results will be carried out and completed, where necessary, by chemical or crystallographic analyses. The aim will be to propose a modelling of these aerosol generation and transformation mechanisms.
The postdoctoral researcher will work within an experimental laboratory of about 20 staff within CEA IRESNE institute (Cadarache site, Southern France).

Design of electromagnets for magnetized plasma experiments on the LMJ-PETAL laser facility

With the aim of increasing the LMJ-PETAL facility's capabilities, particularly in the fields of Inertial Confinement Fusion, radiation source generation and astrophysics, the CEA, with the funding support of the Nouvelle Aquitaine region, has just carried out a feasibility study for an additional system enabling experiments to be carried out under an intense magnetic field (several 10T). The continuation of the project, with a view to its integration into the facility, is the subject of collaboration between several CEA departments, as well as with other laboratories in France (LULI, CELIA) and abroad (Japan, USA).
The magnetic field generation system essentially consists of a consumable coil (electromagnet) positioned around the laser target and powered by an energy bank via a transmission line. The continuation of the project requires in-depth work on the design of the coils, which will have to meet the required performance in terms of magnetic field generation (intensity, magnetized volume, spatial homogeneity and temporal stability), while at the same time being adapted to the characteristics of the high pulsed power supply (~10µs, qq. 10kA and qq. 10kV) and to the experimental constraints of a very large laser facility (integration in the experimental chamber center, alignment, risk of debris, nuclear safety, etc.).

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