Postdoc in Multi-instrumented operando monitoring of Li-ion battery for ageing
Nowadays, the development of new battery technology requires increasing the knowledge of degradation mechanisms occur inside the cell and monitor the key parameter in real time during cycling to increase the performances, lifetime and safety of the cells. To achieve these goals development of new sensing technology and integration inside and outside the cell is needed. The goal of the SENSIGA project is used advanced sensing technology to improve the monitoring of the cell by acquiring useful data correlate to the degradation process and develop more efficient battery management system with accurate state estimators. SENSIGA is a part of PEPR Batteries lead by CNRS and CEA and funding by the French Research Programme FRANCE 2030 to accelerate the development of new battery technology.
You will have the opportunity to work in a stimulating scientific environment focusing on the characterisation of both state of the art and latest generations of battery materials. Based on the sensing technology developed at CEA and from the state of the art, the SENSIGA project will reach the objective of the BATTERY2030+ roadmap goals for smart cells (https://battery2030.eu/research/roadmap/). One of the objectives of the project is to use external sensors to monitor the key parameters of the cell related to performances, ageing and safety behaviours.
Development of Algorithms for the Detection and Quantification of Biomarkers from Voltammograms
The objective of the post-doctoral research is to develop a high-performance algorithmic and software solution for the detection and quantification of biomarkers of interest from voltammograms. These voltammograms are one-dimensional signals obtained from innovative electrochemical sensors. The study will be carried out in close collaboration with another laboratory at CEA-LIST, the LIST/DIN/SIMRI/LCIM, which will provide dedicated and innovative electrochemical sensors, as well as with the start-up USENSE, which is developing a medical device for measuring multiple biomarkers in urine.
X-ray tomography reconstruction based on analytical methods and Deep-Learning
CEA-LIST develops the CIVA software platform, a reference for the simulation of non-destructive testing processes. In particular, it proposes tools for X-ray and tomographic inspection, which allow, for a given tomographic testing, to simulate all the radiographic projections (or sinogram) taking into account various associated physical phenomena, as well as the corresponding tomographic reconstruction.
The proposed work is part of the laboratory's contribution to a European project on tomographic testing of freight containers with inspection systems using high-energy sources. The spatial constraints of the projection acquisition stage (the trucks carrying the containers pass through an inspection gantry) imply an adaptation of the geometry of the source/detector system and consequently of the corresponding reconstruction algorithm. Moreover, the system can only generate a reduced number of projections, which makes the problem ill-posed in the context of inversion.
The expected contributions concern two distinct aspects of the reconstruction methodology from the acquired data. On the one hand, it is a question of adapting the analytical reconstruction methods to the specific acquisition geometry of this project, and on the other hand, to work on methods allowing to overcome the lack of information related to the limited number of radiographic projections. In this objective, supervised learning methods, more specifically by Deep-Learning, will be used both to complete the sinogram, and to reduce the reconstruction artifacts caused by the small number of projections available. A constraint of adequacy to the data and the acquisition system will also be introduced in order to generate physically coherent projections.
Development of a new spectrometer for the characterization of the radionuclide-based neutron sources
Since few years, the LNHB is developing a new instrument dedicated to the neutron spectrometry, called AQUASPEC. The experimental device consists of a polyethylene container that is equipped with a central channel accommodating the source and 12-measurement channels (in a spiral formation) around the source, into which detectors can be placed. The container is filled with water in order to moderate neutrons emitted from the source. Measurements have performed with 6Li-doped plastic scintillators, optimized for the simultaneous detection of fast neutrons, thermal neutrons and gamma rays through the signal processing based on pulse shape discrimination (PSD). The spectrum reconstruction is performed with an iterative ML-EM or MAP-EM algorithm, by unfolding experimental data through the detector's responses matrix calculated with MCNP6 code. The candidate will work in the general way on issues related to the neutron spectrometry in the laboratory: Contribution to the development and validation of the new spectrometer AQUASPEC; Participation to the sources measurements and working on aspects of neutron detection and signal processing, in particular issue of the discrimination of neutron/gamma based on the pulse shape discrimination technique (PSD); Usage of Monte Carlo simulation codes and algorithms to reconstruct initial neutron energy distribution; Investigation and integration of information related to neutron/gamma coincidence specific to the XBe type sources.
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.
Study and modeling of fiber Bragg grating acoustic receivers
CEA List has been working for several years on the development of advanced monitoring solutions using fibre optic acoustic receivers called Fiber Bragg Gratings. These optical sensors have a great potential for structural health monitoring, both because of their ability to be integrated into materials (concrete, organic composites, metal) and because of their ability to be deployed in severe environments (embedded, radiative, high temperature).
A post-doctoral work is proposed to carry out modelling of these Fiber Bragg Grating transducers in order to refine the understanding of their sensitivity to ultrasonic guided elastic waves and to help in the design of an associated control system thanks to an intelligent placement of the sensors. Ultimately, the aim is to be able to simulate their response within the Civa non-destructive testing software developed by CEA List, and more particularly via its module dedicated to Structural Health Monitoring (SHM). Such work would strongly contribute to the adoption and exploitation of this technology for Structural Health Monitoring applications.
Microfluidic biocatalysis
The overall objective of the project is to propose a new mode of biocatalytic production based on continuous flow and combining macro and micro-fluidics. The aim is to develop a biocatalysis process involving fluidic bioreactors capable of ensuring continuous biotransformation, thanks to immobilized enzymes or whole cell catalysts. This process will be optimized to improve the efficiency of enzymatic reactions on the one hand and to obtain important production capacities on the other hand. Two types of enzymes will be studied, nitrilases and ketoreductases.
First, the candidate will be responsible for the search for robust enzymes for the target reactions and screening on the defined substrates. He or she will be responsible for the development of reaction conditions in isolated enzymes and whole cells and the determination of apparent kinetics. Then, he/she will be in charge of setting up the biocatalysis operating conditions and the immobilization of the biocatalyst in versatile continuous reactors.
This subject is carried out between two departments of the CEA (Direction of Fundamental Research/IBFJ/Genoscope in Evry and Direction of Technological Research/Leti in Grenoble).
The candidate will work in pair with a PhD student on the design of the biocatalytic reactor and the scaling up of the biocatalytic process.
Development of irradiation resistant silicon materials and integration in photovoltaïcs cells for space applications
Historically, photovoltaic (PV) energy was developed together with the rise of space exploration. In the 90’s, multijunction solar cells based on III-V materials progressively replaced silicon (Si) cells, taking advantage of higher efficiency levels and electrons/protons irradiation resistance. Nowadays, the space environment is again looking at Si based PV applications: request of higher PV power, moderated space mission lengths, cost reduction issues (€/W Si ~ III-V/500), higher efficiencies p-type Si PV cells… Solar cells are exposed to cosmic irradiation in space, especially to electrons and protons fluxes. The latter’s affect the cells performances, essentially because of bulk defect formations and charge carrier recombination. In order to use Si based solar cells in space, we need to increase their irradiation resistance, which is the main goal of this post-doc position. To do so, the work will first consist in elaborating new Si materials, with increased irradiation resistance. Compositional aspects of the Si will be modified, particularly by introducing elements limiting the formation of bulk defects under irradiations, developing electrical passivation properties. The electronic properties of the materials will be deeply characterized before and after controlled irradiation. Then, this Si material will be used to fabricate heterojunction solar cells. Their performances will be evaluated again before and after irradiation. Such experimental work could be supported by numerical simulation at the device scale.
Modeling of faults on low voltage DC networks in buildings, towards fault detection algorithms
The development of the use of renewable energies and energy storage as well as the progress made by power electronic components are gradually leading to a rethinking of the architectures of low voltage electrical distribution networks in buildings. These developments will allow the development of direct current or mixed alternating-direct current networks supplied by static converters. On this type of network, faults become more difficult to manage due to the power sources used. Indeed, the usual signatures of the short-circuit or the overload are no longer the same and will vary according to the converters used and the architecture of the network. For this, it is necessary to identify, by simulation, the most suitable protection topologies (by neutral systems for example) and to identify the typical fault signatures. Ultimately, these signatures will provide optimum detection devices.
HPC simulations for PEM fuel cells
The goal is to improve TRUST-FC software -a joint development between LITEN and DES institutes at CEA- for detailed full 3D simulation of hydrogene PEM fuel cells and to run simulations on whole real bipolar plate geometries. Funded by AIDAS virtual lab (CEA/Forshungs Zentrum Juelich), a fully coupled electro-chemical, fluidic and thermal model has been built, based on CEA software TRUST. The model has been benchmarked against its FZJ counterpart (Open fuelcell, based on OpenFoam). The candidate will adapt the software and toolchain to larger and larger meshes up to billion cells meshes required to model a full bipolar plate. Besides, he will introduce two phase flow models in order to address the current technological challenges (local flooding or dryout). This ambitious project is actively supported by close collaboration with CEA/DES and FZJ.