Experimentation and numerical simulation of lithium battery thermal runaway
In the current Energy transition context, the lithium battery is an essential technology to address the strong challenge of the electrical energy storage. However, Li battery severe solicitations/loadings can lead to a thermal runaway phenomenon, which can cause an outbreak of fire, even an explosive combustion of the cell or of the whole battery pack. If this phenomenon is well known, the research and development dedicated to the battery safety is emerging and must be consolidated. The post-doctorate global objective is to develop a numerical modelling and simulation strategy for thermal runaway occurring when a Li battery is subjected to mechanical/thermal/electrical abuse, in order to gain an understanding of the phenomenon, estimate the thermal spreading risk as a result of gas combustion, or study the runaway mechanical consequences (fluid structure interaction). This strategy relies on physical testing campaigns carried out as part of the post-doctorate, and on numerical tools developed by CEA (EUROPLEXUS, Cast3M). The work will be organised into three main content areas: Understanding and modelling of the phenomena on the basis of experimental tests (shock tube, abusive tests), Development of a numerical model representative of identified phenomena, Modelling including fluid-structure interaction (case deformation due to pressure increase).
Environmental dosimetry: study, design and implementation of a calibration facility for low dose equivalent rates
In order to meet the calibration needs of the European radioactivity monitoring network, the Laboratoire national Henri Becquerel, part of CEA List, is installing a calibration facility for low dose equivalent rates, below 1 µSv/h. The work includes a study of the performance of the existing radiation beams and the design, installation and dosimetric characterization of a shielded facility to reduce the radiative background, in which low activity photon sources will be installed.
Design of an embedded vision system integrating a fast intelligent imager
The goal of the postdoc is to evaluate the interest of smart imagers integrating processing in the focal plane in embedded vision systems for a localization function and to propose a complete embedded vision system integrating a smart imager and a host.
The study will focus on ego-localization applications, to realize, for example, a 3D localization function.
From an existing application chain, the post-doctoral fellow will be able to carry out an algorithmic study in order to optimize it to exploit the qualities of the intelligent imager.
Then he will be able to propose a partitioning between smart imager and host system, according to performance criteria.
An experiment using the RETINE smart imager as well as the IRIS host board could be conducted to validate the proposal.
Elaboration of a common robot/human action space
This post-doc aims at establishing by artificial intelligence methods (e.g. signal processing on graphs), the mapping of an industrial task performed by a human operator, and acquired by visual sensors, in order to be interpretable and exploitable by a robot. It is part of a project aiming at designing a demonstrator in which a robot will learn to reproduce by observation a task performed by a human. The platform has been deployed at CEA Tech and is currently operated by an engineer.
The objective of this post-doc is mainly to study and develop a set of methods to build a mapping between the actions performed by a human operator and perceived through visual sensors and the actions performed by the robot. These methods and the work of the related theses will then be implemented in the demonstrator in order to test them experimentally.
Due to the central position of the subject of this post-doc, under the triple supervision of the PACCE and IPI teams of LS2N and CEA, you will have to collaborate closely with the two PhD students already involved in the project. You will have to conceptualize and formalize the methods and representations on the one hand by synthesizing the existing literature on the subject and on the other hand by establishing a common framework encompassing the two thesis works.
Evaluation of RF system power consumption for joint system-technology optimization
To be able to increase and optimize wireless transmission systems based on a hybridization of technologies, it is strategic to be able to quickly evaluate the capabilities of these technologies and to adapt the associated architecture as best as possible. To this end, it is necessary to implement new approaches to global power management and optimization.
The work of this post-doctoral contract is at this level.
The first step will be to develop some new power consumption models of the RF transceivers building blocks (LNA, Mixer, Filter, PA, …). A modelization approach has already been tested and validated in the group. In the next step, it will be needed to link the performances of the overall wireless system to the building blocks characteristics. Lastly, the optimization will be applied thanks to an efficient solution. Lastly, the proposed approach will be validated in the optimisation of a multi-antenna millimeter wave wireless system. An evaluation methodology specific to 3D will also be put in place
Optomechanical force probes development for high speed AFM
The proposed topic is part of a CARNOT project aiming at developing a new generation of force sensors based on optomechanical transduction. These force sensors will be implemented in ultrafast AFM microscopes for imaging and force spectroscopy. They will allow to address biological and biomedical applications on sub-microsecond or even nanosecond time scales in force spectroscopy mode.
First optomechanical VLSI force probes on silicon have been designed and fabricated in LETI's industrial grade clean rooms and have led to first proofs of concept for fast AFM [1,2]. The post-doctoral student will be in charge of the preparation of force probes in order to integrate them in a high speed AFM developed by our partner at CNRS LAAS (Toulouse). He will be in charge of the back end operations, from the release of the structures, their observation (SEM, optical microscopies, etc.), to the optical packaging with fiber optic ferrules. He will also participate in the development of a test bench for components before and after packaging to select devices and validate the packaged probes before integration into an AFM.
The post-doctoral student will also investigate the operation of the probe in a liquid medium to allow later AFM studies of biological phenomena: for this, the development of efficient actuation means (electrostatic, thermal or optical) of the mechanical structure will be carried out and applied experimentally. A feedback on the modeling and the design is expected from the measurements, in order to ensure the understanding of the observed physical phenomena. Finally, the post-doctoral fellow will have the possibility to propose new device designs to target the expected performances. The devices will be fabricated in Leti's clean room, then tested and compared to the expected performances.
Wood modifications by supercritical CO2
In order to replace current high environmental impact construction materials, CEA leads research work on chemical functionalization of wood (from French local forests) to improve its properties and make them a viable substitute of these construction materials or imported construction wood.
In this frame, chemistry under supercritical CO2 appears to be an efficient way to carry innovative chemistries while liùmiting the environmental impact & VOCs emissions of such processes.
Thus, you will be in charge of the development of new processes of chemical modification of local wood species under supercritical CO2. You will lead the research project by perfroming the state of the art, making technical propositions (around the adapted functionalization chemistries), carrying out the eperiments & the characterizations and will be in charge of respecting the deadlines & redacting the associated deliverables.
Multi-scale modeling of the electromagnetic quantum dot environment
In the near future, emerging quantum information technologies are expected to lead to global breakthroughs in high performance computing and secure communication. Among semiconductor approaches, silicon-based spin quantum bits (qubits) are promising thanks to their compactness featuring long coherence time, high fidelity and fast qubit rotation [Maurand2016], [Meunier2019]. A main challenge is now to achieve individual qubit control inside qubit arrays.
Qubit array constitutes a compact open system, where each qubit cannot be considered as isolated since it depends on the neighboring qubit placement, their interconnection network and the back-end-line stack. The main goal of this post-doctoral position is to develop various implementation of spin control on 2D qubit array using multi-scale electromagnetic (EM) simulation ranging from nanometric single qubit up to millimetric interconnect network.
The candidate will i) characterize radio-frequency (RF) test structures at cryogenic temperature using state-of-the-art equipment and compare results with dedicated EM simulations, ii) evaluate the efficiency of spin control and allow multi-scale optimization from single to qubit arrays [Niquet2020], iii) integrate RF spin microwave control for 2D qubit array using CEA-LETI silicon technologies.
The candidate need to have a good RF and microelectronic background and experience in EM simulation, and/or design of RF test structures and RF characterization. This work takes place in a dynamic tripartite collaborative project between CEA-LETI, CEA-IRIG and CNRS-Institut Néel (ERC “Qucube”).
Postdoctoral fellow in AI, real time signal processing and software for real time epilepsy prediction/forecasting for closed loop neuromodulation by focal Cooling.
To date seizure suppression stimulation technologies (electrical stimulation) are majorly based on seizure detection procedure. No study has provided sound evidence that prospective seizure prediction/forecasting can be used to trigger closed loop therapeutics for drug resistant epilepsy treatment. Our proposal is based on the existing motor brain-computer interface algorithms already in clinical use. They can be adapted to generate prediction/forecasting of seizures occurrence. Our working hypothesis is that treating during high-risk seizures periods and not during the actual seizure would require relatively minor doses of the therapeutical element. This will reduce the power consumption and open the door to fully implantable system. Decoding algorithms will be potentially redesigned to respond better to the epileptic seizures forecasting task. They will be compared to the state of the art CNN based approaches, and other approaches. Prediction/forecasting seizures algorithms will be evaluated in an epilepsy model established at Clinatec, using non-human primates, and the algorithms will be refined over time. Cooling the epileptic foci is an effective way to stop de seizure before generalization. This model allows us to test the efficacy of the algorithms in treating focal seizures. An assessment of hardware embedding design constraints would be conducted to facilitate next steps for the clinical device development. The project will benefit from a collaboration between Clinatec and DSYS/SSCE; and will be in line with upcoming activities of LETI’s artificial intelligence platform.
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.