Implementation of a sensor allowing the online monitoring of the corrosion of stainless steels in a hot and concentrated nitric acid medium
The control of materials (mainly stainless steel) aging of the spent nuclear fuel reprocessing plant is the subject of permanent attention. Some installations at La Hague plant will have to be replaced very soon. In this context, it is important for the industry to develop sensors that are resistant to concentrated nitric acid (˜ 2.5 mol / L) and temperature (from ambient to 130 °C), allowing the online monitoring of the corrosion.
The aim of this work is to manufacture one sensor for the detection of corrosion of the steel intended for handling by the operators of the plant. In case of a positive response, the second sensor is used.
The challenges of this work are essentially technological since it will develop or use materials adapted to concentrated and hot nitric acid media.
The laboratory is specialized in the corrosion study in extreme conditions. It is composed of a very dynamic and motivated scientific team.
Modeling of the spent fuel alteration mechanisms in a water-saturated environment with temperature effect
Modeling the alteration of spent nuclear fuel in the eventuality of an underwater interim storage in pools or a deep geologic disposal is essential for long-term prediction. In the event of a failed spent fuel assembly, corrosion processes can lead to a deterioration of the failed rod and to a radionuclide release into water. A geochemical model coupling chemistry to transport (reactive transport) was the subject of first developments in connection with deep geological disposal conditions using the CHESS-HYTEC code developed by the Ecole des Mines de Paris. This model makes it possible to take into account the main alteration mechanisms and associated kinetics while relying on robust thermodynamic data. It remains important to pursue these developments by studying the effect of temperature between 20 and 70 °C. Adapting this model to other alteration conditions like an underwater of spent fuel in dedicated pools for several decades is also a short-term objective.
Hybrid CMOS / spintronic circuits for Ising machines
The proposed research project is related to the search for hardware accelerators for solving NP-hard optimization problems. Such problems, for which finding exact solutions in polynomial time is out of reach for deterministic Turing machines, find many applications in diverse fields such as logistic operations, circuit design, medical diagnosis, Smart Grid management etc.
One approach in particular is derived from the Ising model, and is based on the evolution (and convergence) of a set of binary states within an artificial neural network (ANN).In order to improve the convergence speed and accuracy, the network elements may benefit from an intrinsic and adjustable source of fluctuations. Recent proof-of-concept work highlights the interest of implementing such neurons with stochastic magnetic tunnel junctions (MTJ).
The main goals will be the simulation, dimensioning and fabrication of hybrid CMOS/MTJ elements. The test vehicles will then be characterized in order to validate their functionality.
This work will be carried out in the frame of a scientific collaboration between CEA-Leti and Spintec.
Crystal plasticity in classical molecular dynamics and mesoscopic upscaling
Thanks to new supercomputer architectures, classical molecular dynamics simulations will soon enter the realm of a thousand billion atoms, never before achieved, thus becoming capable of representing the plasticity of metals at the micron scale. However, such simulations generate a considerable amount of data, and the difficulty now lies in their exploitation in order to extract the statistical ingredients relevant to the scale of "mesoscopic" plasticity (the scale of continuous models).
The evolution of a material is complex, as it depends on lines of crystalline defects (dislocations) whose evolution is governed by numerous mechanisms. In order to feed models at higher scales, the quantities to be extracted are the velocities and lengths of dislocations, as well as their evolution over time. These data can be extracted using specific analysis techniques based on characterization of the local environment ('distortion score', 'local deformation'), a posteriori or in situ during simulation. Finally, machine learning tools can be used to analyze the statistics obtained and extract and synthesize (by model reduction) a minimal description of plasticity for models at higher scales.
Developement of relaxed pseudo-substrate based on InGaN porosified by electrochemical anodisation
As part of the Carnot PIRLE project starting in early 2021, we are looking for a candidate for a post-doctoral position of 24 months (12 months renewable) with a specialty in material science. The project consists in developing a relaxed pseudo-substrate based on III-N materials for µLEDs applications, especially for emission in red wavelength. The work will focus on developing an InGaN-based epitaxy MOCVD growth process, on an innovative substrate based on electrochemically anodized and relaxed materials. He (She) will have characterize both the level of relaxation of the re-epitaxied layer and its crystalline quality. These two points will promote the epitaxial regrowth of an effective red LED. The candidate will be part of the team, working on the PIRLE project, will be associated to the work on red LED growth and its optical and electro-optical characterizations.
Modelling of uranium precipitation kinetics as a function of pH. Application to fluidized bed reactor
The Orano plant in Niger (Somaïr) precipitates its uranium concentrate in a fluidized bed reactor by adding sodium hydroxide. The concentrate obtained contains around 6% sodium which leads to converter penalties. Orano carried out tests at the end of 2019 on a fluidized bed in the laboratory to change the operating point of precipitation and preferentially form UO3 via a change in pH. To refine the management of the industrial unit, it is necessary to model the precipitation reactions of uranium. The candidate will have to propose and calibrate a competitive precipitation model for Na2U2O7 and UO3 based on the equilibrium constants and reaction kinetics, as a function of the pH within the reactor. In particular, the model should make it possible to understand the impact of pH on the distribution of the two main species identified in the concentrate: Na2U2O7 and UO3. This chemical model should serve as input to an existing physical model of the fluidized bed reactor. An extension of the model to other precipitation reagents, in particular magnesia, could also be studied.
Synthesis and structural analysis of reference uranium minerals for the identification of uranium-bearing phases in mining environment by TRLFS.
In the frame of the collaborative project between the ICSM , CEA and Orano, a study is conducted in order to detect and identify minerals containing uranium (VI) by Time-Resolved Laser Fluorescence Spectroscopy (TRLFS). This technique showed its efficiency in order to identify the presence of uranyl in natural assemblies through the probing of the local environment of uranium. However, it requires the establishment of a database from synthetic and natural samples fully characterized. Therefore, in order to achieve this goal, we intend to synthesis, and thoroughly characterize a variety of compounds containing uranyl groups within the crystal structure. We can cite the families of oxi-hydroxide, sulfate, and silicates based compounds. Then, TRLFS spectra will be collected in order to complete the database and to evidence the impact of the local structure of uranyl cation on the intensity and the position of the emission bands. The obtained data will be also compared to a collection of natural samples.
Modeling of trapping and vertical leakage effects in GaN epitaxial substrates on Si
State of the art: Understanding and modeling vertical leakage currents and trapping effects in GaN substrates on Si are among the crucial subjects of studies aimed at improving the properties of GaN power components : current collapse and Vth instabilities reductions, reduction of the leakage current in the OFF state.
Many universities [Longobardi et al. ISPSD 2017 / Uren et al. IEEE TED 2018 / Lu et al. IEEE TED 2018] and industrials [Moens et al. ISPSD 2017] are trying to model vertical leakages but until now, no clear mechanism has emerged from this work to model them correctly over the entire range of voltage and temperatures targeted. In addition, modeling the effects of traps in the epitaxy is necessary for the establishment of a a robust and predictive TCAD model of device.
For LETI, the strategic interest of such a work is twofold: 1) Understanding and reducing the effects of traps in the epitaxy impacting the functioning of GaN devices on Si (current collapse, Vth instabilities…) 2) Reaching the leakage specifications @ 650V necessary for industrial applications.
The candidate will have to take charge in parallel of the electrical characterizations and the development of TCAD models:
A) Advanced electrical characterizations (I (V), I (t), substrate ramping, C (V)) as a function of temperature and illumination on epitaxial substrates or directly on finite components (HEMT, Diodes, TLM )
B) Establishment of a robust TCAD model integrating the different layers of the epitaxy in order to understand the effects of device instabilities (dynamic Vth, dynamic Ron, BTI)
C) Modeling of vertical conduction in epitaxy with the aim of reducing leakage currents at 650V
Finally, the candidate must be proactive in improving the different parts of the substrate
Optical sensor development for in-situ and operando Li-ion battery monitoring
To improve the battery management system, it is required to have a better knowledge of the physical and chemical phenomena inside the cells. The next generation of cells will integrate sensors for deepest monitoring of the cell to improve the performances, safety, reliability and lifetime of the battery packs. The main challenge is thus to measure relevant physico-chemical parameters in the heart of the cell to get a direct access to the real state of the cell and thus to optimize its management. To address this challenge, a research project will start at CEA at the beginning of 2020 to develop innovative optical sensors for Li-ion battery monitoring. He / She will participate, in a first step, to the development of optical probes and their integration on optical fibres. The work will focus on the synthesis of a photo-chemical probe (nanoparticle and/or molecule) as active part of the sensor. Then, theses probes will be put on the optical fibre surface to form the sensor. The candidate will also participate to the realization of an optical bench dedicated to the testing of the sensors. In a second step, he / she will work on integrating the sensors into the Li-ion cells and test them in different conditions. The objective is to demonstrate the proof of concept: validation of the sensors efficiency to capture the behaviour of the cell and correlate it to electrochemical measurements.