Selenium 79 quantification in nuclear waste
Accurate assessment of the inventory of long-lived radionuclides represents a major challenge for nuclear sites. Selenium 79 is one of the seven main long-lived fission products, but very few actual measurements of 79Se in real samples are reported in the literature. Its measurement is difficult due to its low concentration in spent fuel.
The main goal of this post-doctoral project is to develop an analytical protocol for lowering the detection limit (below ng/L) for 79Se in nuclear waste, and more specifically in the zircaloy cladding of spent fuel.
The candidate will be responsible for sample preparation, establishing protocols for the separation of selenium by ion exchange chromatography, development of an ICP-MS/MS measurement method to eliminate interferences and achieve the best possible sensitivity, interpretation of the results as well as their presentation at scientific conferences and publication in peer-reviewed journals.
The post-doctorate is initially financed for one year, but may be extended for a further year to develop the measurement of 107Pd and 126Sn.
Thermochemical and thermodynamic study of chloride molten salts
In today’s climate emergency, access to clean and cheap energy is more important than ever. Several ways have been envisaged for several years now, but a number of technological issues still need to be overcome before they can be put into practice, as they represent breakthroughts. Whether for energy storage than for fourth generation nuclear reactors, molten salt environment used as coolant and/or as fuel is highly corrosive requiring a complexe choice of structural materials.
The aim of this subject proposed in the Corrosion and Materials Behavior Section is to study in depth the chemical properties of different chloride molten salts : the basic ternary salt (NaCl-MgCl2-CeCl3) but also the corrosion/fission/activation products that can be produced (MxCly with M=Cr, Fe, Te, Nd, Ni, Mo,…). The activity coefficients and solubility limits of these metallic elements will be determined using various techniques such as electrochemistry and Knudsen cell mass spectrometry. If required, this study can be completed by the phase transition temperature and heat capacity measurements using differential scanning calorimetry.
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.
Development of innovative electrolytes for high power Na-ion batteries
The Postdoctoral position will be part of the PEPR Battery Hipohybat project. This project aims to develop high-power Na-ion batteries in close collaboration with academic partners such as Collège de France and IS2M. The Na+ ion conductivity in the bulk of the electrolyte, as well as at the electrode-electrolyte interface (EEI), are the two major criteria that need to be optimized in electrolytes to enable the development of fast-charging Na-ion cells.
The first strategy to increase bulk conductivity will be to use less viscous co-solvents, such as ethers or nitriles. However, these solvents exhibit poor electrochemical stability. Therefore, as a first step, the impact of adding such co-solvents to the state-of-the-art Na-ion electrolyte in various proportions will be studied to (i) determine their electrochemical stability windows and (ii) analyze their solvation/desolvation behavior, which is critical for their power rate capabilities. The fluorinated counterparts of the most promising co-solvents will also be investigated to improve oxidative stability and enable the formation of a stable solid electrolyte interphase at the negative electrode.
The second approach will focus on identifying additives that lead to ‘non-resistive’ interphases. Both commercial and in-house synthesized additives will be explored for this purpose. By tuning the three electrolyte components together, new formulations will be developed to achieve a better compromise between fast Na?-ion kinetics and stable cycling performance of Na-ion cells.
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.
In situ analysis of dislocations with Molecular Dynamics
Thanks to new supercomputer architectures, classical molecular dynamics (MD) simulations will soon reach the scale of a trillion atoms. These unprecedentedly large simulation systems will thus be capable of representing metal plasticity at the micron scale. Such simulations generate an enormous amount of data, and the challenge now lies in processing them to extract statistically relevant features for the mesoscale plasticity models (continuous-scale models).
The evolution of a material is complex as it depends on extended crystal defect lines (dislocations), whose dynamics are governed by numerous mechanisms. To feed higher-scale models, the key quantities to extract are the velocities and lengths of dislocations, as well as their evolution over time. These data can be extracted using specific post-processing techniques based on local environment characterization ('distortion score' [Goryaeva_2020], 'local deformation' [Lafourcade_2018], ‘DXA’ [Stukowski_2012]). However, these methods remain computationally expensive and do not allow for in situ processing.
We have recently developed a robust method for real-time identification of crystalline structures [Lafourcade_2023], which will soon be extended to dislocation classification. The objective of this postdoctoral project is to develop a complete analysis pipeline leading to the in situ identification of dislocations in atomic-scale simulations and their extraction in a nodal representation.
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.
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).
Postdoc in Advanced Fault-Tolerant Control for Fuel Cell Durability Enhancement
Fuel cells are a key technology for clean and sustainable energy systems, particularly in hybrid configurations for transport and stationary applications. However, their durability under real-world conditions remains a critical challenge. This project aims to address these challenges by exploring advanced control strategies that leverage state-of-the-art prognostic algorithms for fuel cell health assessment.
This postdoc offer focalizes on Advanced Control and Optimization, specifically the design of Fault-Tolerant Control (FTC).
Building on prior work in machine learning-based prognostics for fuel cell health, the focus of this project is to develop methods to utilize this prognostic information to optimize the operation of the fuel cell system.
By incorporating both model-based, data-driven approaches and testing on real test-bench platforms, the project aims to create robust, deployable solutions that enhance fuel cell durability while reducing the complexity and cost of implementation.