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.
Verification methodology for synchronous systems software
The Synchrone plug-in of Frama-C is dedicated to Lustre programs analysis. It combines the capabilities of the WP and Eva plug-ins and interacts with the GaTeL solver to prove different properties about analyzed programs. This postdoc aims at improving the whole usage of Synchrone throught the following scientific challenges:
- develop a verification methodology that relies on the combination of technics available in the tool, by applying it to representative use-cases,
- in order to support this methodoogy, improve the tools available in Synchrone, in particular the generation of the proof obligations, and their optimization for automatic solvers, like the Colibri2 solver which is developed in the lab,
- improve the link between what the tool verifies and the mathematical specification of the system, by extending LustreSpec and developping associated tools, it comprises aspects related to numerical filters,
- development of tools for visualizing and debugging proof obligations.
This postdoc thus aims at having a global view of the Synchrone tool, targeting publications about proof methodology in an industrial context.
Impact of Microstructure in Uranium Dioxide on Ballistic and Electronic Damage
During reactor irradiation, nuclear fuel pellets undergo microstructural changes. Beyond 40 GWd/tU, a High Burnup Structure (HBS) appears at the pellet periphery, where initial grains (~10 µm) fragment into sub-grains (~0.2 µm). In the pellet center, under high temperatures, weakly misoriented sub-grains also form. These changes result from energy loss by fission products, leading to defects such as dislocations and cavities. To study grain size effects on irradiation damage, nanostructured UO2 samples will be synthesized at JRC-K, using flash sintering for high-density pellets. Ion irradiation experiments will follow at JANNuS-Saclay and GSI, with structural characterizations via Raman spectroscopy, TEM, SEM-EBSD, and XRD. The postdoc project will take place at JRC-K, CEA Saclay, and CEA Cadarache under expert supervision.
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.
Ageing battery analysis with internal multi-sensors analysis: development of sensors and operando measurements
CEA and CNRS collège de France lead the PEPR Batterie , a French National project with the objective to achieve the European Roadmap from Battery2030+ for the development of “smart battery”. The Sensiga project is a part of PEPR Battery. This project aims to develop new sensors technologies for monitoring the critical parameters of the Lithium ion cells during cycling to improve performances, safety and ageing. This new sensors technology will increase the knowledge of the internal physical, chemical and electrochemical process occurs in the cell. The large amount of data measuring operando will be used to developing new algorithm and strategies to improve the battery management systems. In the context of the Sensiga project, doctoral and postdoctoral position was open at CEA for working on this topic with a multidisciplinary and laboratory team. The aims of the work is to developing new sensing technology for in-situ and operando monitoring of the cell. The candidate will integrate a team specialized in the development of specific sensors for Lithium ion battery in the Laboratory of Postmortem Analysis and Security at CEA Grenoble.
The scope of the position will focus on the development of optical fibre sensors, the integration of theses sensors inside pouch cell and performing electrochemistry test for ageing study. This kind of sensors will be used to monitor the internal temperature, strain, and pressure and lithium concentration. The second type of sensors using in the project is the reference electrode using for electrode potential measurement. These data’s are crucial to access to the degradation mechanisms of each materials in operando. The candidate will be participate to the ageing test campaign and to the post-mortem analysis. This analysis compare to the ageing test will be used to identify the degradation mechanisms and correlate it to the sensors signal. The candidate will integrate a multidisciplinary team.
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).