Design and accelerated testing of corrosion FOSs for reinforced concrete structures
Corrosion of steel reinforcement is the main pathology threatening the durability of civil engineering structures. Today, structures are mainly monitored by means of periodic visual inspections or even auscultation (corrosion potentials, ultrasonic measurements, core sampling, etc…), which are not very satisfactory. There is therefore a need for instrumentation capable of detecting the initiation and location of corrosion of reinforcement in concrete and ensuring long-term monitoring (several decades or more). In the context of Civil Engineering (CE) structures, Optical Frequency-Domain Reflectometry (OFDR) appears to be a suitable metrological solution because of its centimetre resolution and measurement range (70 metres in the standard version, i.e. several thousand measurement points along an optical fibre).
Content of work: The aim will be to adapt the design of this fibre optic sensor (FOS) to increase its durability and then to verify its applicability in the laboratory. Initially, the person recruited on a fixed-term research contract will be asked to work on the durability of the connexion between the optical fibre and the armature. Two different methods are envisaged: plasma torch spraying of ceramic powders and sol-gel. Both of these processes prevent the galvanic coupling because they involve insulating materials (ceramics) and are already deployed in industry in various civil and military fields. Secondly, test specimens equipped with the FOS will be tested in the laboratory according to classic civil engineering situations, i.e. localised corrosion (pitting induced by exposure to chloride ions) and uniform corrosion (generalised corrosion induced by carbonation of the embedding concrete). OFDR acquisitions will be carried out periodically over time in parallel with conventional metrology (potential, etc.).
Thermodynamic study of the Nb-O-Zr system for the nuclear fuel elements recycling
The first step of nuclear material recycling consists in a section-cutting process of the fuel assemblies leading to shells.
Nuclear materials in the cut sections are dissolved in acid solutions whilst structural as well as cladding materials are rinsed and then compacted in CSD-C containers for a final storage in CIGEO.
The REGAIN project aims at studying the feasibility of an alternative solution: the objective is to investigate the possibility to optimize the nuclear and cladding materials management by reducing the radiological source term. The idea is to proceed to a sequence of decontamination steps in order to minimize the waste volume: The first step consists in removing minor actinides and fission products and the second one in the separation of zirconium from structural activation products.
In order to feed the industrial process study, a part of the REGAIN project aims at collecting raw data, which will be used by the other work packages of the project.
In this framework, CEA proposes a post-doctoral position with the purpose of developing a thermodynamic database for the Nb-O-Zr system starting from literature data as well as using experimental informations obtained within the first stages of the project. It will be also possible to include a selection of key fission products into the existing database. The candidate may also be asked to complete the existing data by an experimental campaign to obtain a complete set of data for the modelling. The scientific approach will be based on the CALPHAD method: this method allows developing a thermodynamic database by the definition of an analytical formulation of the thermodynamic potential, which will be used to calculate phase diagrams as well as thermodynamic properties of multi-components systems.
Development of a simulation tool for the pitting process of a stainless steel used for the storage of nuclear waste
Structural nuclear waste is compacted in patties, stacked in a stainless steel container. In these compacting boxes are placed various metal-type materials with the addition of organic matter, including chlorinated waste. By radiolytic degradation, these can lead to the formation of hydrogen chloride HCl. During the storage phase, relative humidity may be present within the container, which, added to the HCl, may lead to a phenomenon of condensation, resulting, on the surface of the materials, of acid and concentrated into chloride ions condensates. In contact with this acid and chloride electrolyte, a pitting phenomenon is likely to begin on the surface of a stainless steel. This is a local phenomenon that can lead to the piercing of the material in extreme cases. The initiation of this phenomenon depends on several factors: the morphology of the electrolyte, its composition and its evolution over time.
If nowadays this phenomenon is well known, modeling it remains a major challenge because it is a coupled multi-physics and multi-parameter problem. Many questions remain open, particularly at the level of the physical and chemical laws to be used or how to represent the corrosion process?
The objective of the post-doctorate is to develop a tool under COMSOL capable of simulating the initiation and the evolution over time of a pit on the surface of a stainless steel. The approach will be based on a mechanistic modeling of the processes (material transport process and all the chemical and electrochemical reactions).
The post-doctorate will take place in several actions:
1- make a state of the art of the bibliography in order to understand the pitting phenomenon and to identify the laws necessary for modeling.
2-simulate the spread of the pit in a chloride environment in order to establish a propagation criterion.
3-the pitting initiation will be implemented in order to obtain a complete tool capable of simulating the pitting process
Aqueous alteration of nuclear glass in its disposal environment
Exploitation, characterization and modeling of so-called "integral" experiments of glass alteration intended for the confinement of nuclear waste (SON68 and AVM4) in the presence of iron, cementitious material and argillite from the Bure site in two geometrical configurations: one simulating a disposal cell, the other intimately mixing the materials present. These tests were launched on behalf of ANDRA between 2017 and 2018 and their characterization started in the past two years.
Thermodynamic investigation of Metal-Insulator-Transition materials – The case of doped VO2 for smart windows applications
The present post-doc proposal aims to develop a specific thermodynamic database on the V-O-TM (TM=Fe,Cr) system by using the CALPHAD approach. The candidate will conduct experimental campaigns to obtain relevant data to feed the thermodynamic models. The candidate will mostly use the experimental equipment available at the lab (DTA, annealing furnaces, high temperature mass spectrometry, laser heating, SEM-EDS). In addition, the post-doc may participate to combinatorial high-throughput activities led by other laboratory of the Hiway-2-Mat consortium (e.g., ICMCB in Bordeaux), allowing a better connection between the CALPHAD simulation output and the accelerated characterization platform. The thermodynamic database will be then included in the autonomous research routine implemented in the material exploration path.
Mitigation of Alkali Silica Reaction in concrete used for radwaste stabilization and solidification
Electricity production from nuclear power plants generates radioactive wastes, the management of which represents a major industrial and environmental concern. Thus, low- or intermediate - level radioactive aqueous waste streams may be concentrated by evaporation, and immobilized with a Portland cement, before being sent to disposal. Nevertheless, interactions may occur between some components of the waste and the cement phases or aggregates, and decrease the stability of the final waste forms. Thereby, the formation of a gel-like product has been recently observed on the surface of some cemented drums of evaporator concentrates which were produced in the 80’s in Belgium. This product results from a reaction between silica from the aggregates and the very alkaline pore solution of the concrete. However, its composition and rheological properties differ from those reported for alkali-silica gels in civil engineering. Extensive work has been performed to better understand the processes involved in the gel formation within the cement-waste forms and characterize its properties. Based on these results, the post-doctoral project will be focussed on the mitigation of alkali silica reaction in cement-waste forms. Two approaches will be more particularly investigated by decreasing the water saturation ratio of concrete and/or the pH of its pore solution using supercritical carbonation.
This project is intended for a post-doctoral fellow wishing to develop skills in materials science, with an interest in advancing the field of cement chemistry and improving the conditioning of radioactive waste. It will be performed in collaboration with ONDRAF-NIRAS, the Agency in charge of radioactive waste management in Belgium, and will build upon the expertise of two laboratories at CEA Marcoule: the Cements and Bitumen for Waste Conditioning Laboratory for materials elaboration and characterization, and the Supercritical and Decontamination Laboratory.
Next generation PV module packaging design and mechanical testing
Photovoltaic modules are required to last 25- 30 years in harsh outdoor environment. The packaging of PV modules plays an essential role in reaching this target. PV cells are protected by a glass frontsheet, and highly engineered polymeric encapsulants and backsheets. Encapsulants provide moisture, oxygen &UV barrier, electrical isolation and mechanical protection of highly fragile cells while they must ensure optical coupling between the various layers. Current industrial process technology for module manufacturing is lamination that adds additional constraints to the formulation of encapsulants. These numerous requirements lead to ever-involving complex encapsulant composition and behavior.
The aim of this post-doc is to establish the correlation between the material properties of engineered plastics– their processing conditions and thermo-mechanical behavior in high performance PV modules with heterojunction, back-contact or Si/Perovksite tandem cells. Material selection and lamination process development will be guided by detailed material characterization (DSC, DMA, Peel strength, TGA, WVTR, Soxhlet extraction etc.). Moreover, we aim to establish insights in the encapsulant processing conditions and its impact on mechanical stability of PV modules. The selection of the encapsulants to investigate will be strongly guided by eco-design to lower the environmental impact and to increase the recyclability of modules. This postdoc is conducted in the frame of an EU collaboration.
Automatic machine learning identification of nanoscale features in transmission electron microscopy images
Imaging nanoscale features using transmission electron microscopy (TEM) is key to predicting and assessing the mechanical behaviour of structural materials in nuclear reactors or in the fields of nanotechnology. These features, visible by phase contrast (nanobubbles) or diffraction contrast (dislocation loops or coherent precipitates), are prime candidates for automation. Analysing these micrographs manually is often tedious, time-consuming, non-universal and somehow subjective.
In this project, the objective is to develop a Python-based framework for data treatment of transmission electron microscopy (TEM) images.
Machine Learning approaches will be implemented in order to tackle the following tasks:
- Data collection: The success of any machine learning approach is linked to the database quality. In this project, a huge database is available. Four microscopists are involved in the project and will continuously enrich the database with images containing easily recognizable features.
- Denoising and finding the defect contour both through existing open-access software and in-house developed descriptors. Representative ROI (region-of-Interest) will be generated on images.
- Design of the Convolutional Neural Network (CNN) Architecture and model training: A collective feature map will be generated for the entire images in order to identify some representatives ROI. Each ROI is then overlaid to the original feature map and is passed to the CNN for individual region classifications. Secondly, recent advances in image segmentation will be placed in the core engine of the workflow.
- Model performance metrics: The aim is to reach a compromise between the training time and the detector performance.
The process will be applied to nanometer-sized features formed under irradiation in nuclear oriented materials (Co-free high entropy alloys (HEA), UO2) and precipitates in materials with a technological interest (coherent Cr precipitates in Cu).
Lean-Rare Earth Magnetic materials
The energy transition will lead to a very strong growth in the demand for rare earths (RE) over the next decade, especially for the elements (Nd, Pr) and (Dy, Tb). These RE, classified as critical materials, are used almost exclusively to produce NdFeB permanent magnets, and constitute 30% of their mass.
Several recent international studies, aiming to identify new alloys with low RE content and comparable performances to the dense magnetic phase Nd2Fe14B, put hard magnetic compounds of RE-Fe12 type as advantageous substitution solutions, allowing to reduce more that 35% of the amount of RE, while keeping the intrinsic magnetic properties close to those of the Nd2Fe14B composition.
The industrial developments of the RE-Fe12 alloys cannot yet be considered due to the important technological and scientific challenge that remain to be lifted in order to be able to produce dense magnets with resistance to demagnetization sufficient for current applications (coercivity Hc > 800 kA/m).
The aim of the post-doctoral work is to develop Nd-Fe12 based alloys with optimized intrinsic magnetic properties and to master the sintering of the powders in order to obtain dense magnets with coercivity beyond 800 kA/m, to fulfil the requirements of the applications in electric mobility. Two technological and scientific challenges are identified:
- understanding of the role of secondary phases on the coercivity. This will open the way to the implementation of techniques called "grain boundary engineering", well known for the NdFeB magnets to have remarkably improved the resistance to demagnetization.
- mastering the sintering step of these powders at low temperature (< 600°C) in order to avoid the decomposotion of the magnetic phase by grain boundary engineering
Highgly reflective materials laser microwelding
In the frame of the Simulation Program, CEA/DAM conducts experiments on high powerful lasers involving complex targets. Intensive research is therefore conducted to study and manufacture a large panel of targets - with ambitious scientific and technological challenges ahead. In particular, CEA wants to extend its laser microwelding capabilities–at a sub-mm scale. The challenge is to weld both high-reflective and thin materials (aluminum, copper, gold …) with an accurate mastering of heat deposition and penetration depth. The goal is to implement, optimize and qualify a process based on the latest source generation (UV or green laser source), and to get an innovative set of experimental data. A phenomenological model might also be proposed.
The latest generation of laser source emitting in visible wavelengths (green, blue) will be exploited. He/she will participate in the design and qualification testing of the laser station associated with this new source. Once validated, he/she will carry out the study of the operational and metallurgical weldability of the sub-elements. He/she will compare his/her results with the use of a pulse infrared laser. He/she will appraise the joints obtained using different approaches and optimize the design of the welded joints. Its experimental study will go as far as carrying out functional tests on prototypes. External collaborations will be set up to compare the results obtained with simulations in order to deduce a phenomenological model.