Study of a low-cost K-ion storage system: electrolyte, safety and prototyping
The UPBEAT project (France 2030) aims to develop a low-cost potassium-ion technology that is free of critical materials and capable of providing the performance of LiFePO4-type Li-ion cells. The work proposed to the post-doc is in line with this objective: it will involve developing optimised organic liquid electrolytes for this new system (Prussian White vs. Graphite), by studying the most promising salts, solvents and additives, while maintaining the objectives of cost and durability. The proposed solutions (with and without fluorine) will be formulated, characterised and electrochemically tested in complete cells (coin cells and pouch cells including components optimisations) to measure their effectiveness in terms of lifetime and power response. Operando measurements and post-mortem characterisations will be used to understand the effects of the various components. The systems that best meet the project's requirements will also be subjected to abuse tests to assess the safety of the final system.
High-performance computing using CMOS technology at cryogenic temperature
Advances in materials, transistor architectures, and lithography technologies have enabled exponential growth in the performance and energy efficiency of integrated circuits. New research directions, including operation at cryogenic temperatures, could lead to further progress. Cryogenic electronics, essential for manipulating qubits at very low temperatures, is rapidly developing. Processors operating at 4.2 K using 1.4 zJ per operation have been proposed, based on superconducting electronics. Another approach involves creating very fast sequential processors using specific technologies and low temperatures, reducing energy dissipation but requiring cooling. At low temperatures, the performance of advanced CMOS transistors increases, allowing operation at lower voltages and higher operating frequencies. This could improve the sequential efficiency of computers and simplify the parallelization of software code. However, materials and component architectures need to be rethought to maximize the benefits of low temperatures. The post-doctoral project aims to determine whether cryogenic temperatures offer sufficient performance gains for CMOS or should be viewed as a catalyst for new high-performance computing technologies. The goal is particularly to assess the increase in processing speed with conventional silicon components at low temperatures, integrating measurements and simulations.
Digital correction of the health status of an electrical network
Cable faults are generally detected when communication is interrupted, resulting in significant repair costs and downtime. Additionally, data integrity becomes a major concern due to the increased threats of attacks and intrusions on electrical networks, which can disrupt communication. Being able to distinguish between disruptions caused by the degradation of the physical layer of an electrical network and an ongoing attack on the energy network will help guide decision-making regarding corrective operations, particularly network reconfiguration and predictive maintenance, to ensure network resilience. This study proposes to investigate the relationship between incipient faults in cables and their impact on data integrity in the context of Power Line Communication (PLC). The work will be based on deploying instrumentation using electrical reflectometry, combining distributed sensors and AI algorithms for online diagnosis of incipient faults in electrical networks. In the presence of certain faults, advanced AI methods will be applied to correct the state of the health of the electrical network's physical layer, thereby ensuring its reliability.
MULTI-CRITERIA ANALYZES OF HYDROGEN PRODUCTION TECHNOLOGIES BY ELECTROLYSIS
LITEN, strongly involved in electrolysis technologies, wishes to compare via a multi-criteria analysis all electrolysis technologies currently available commercially (AEL, PEMEL), in the pre-industrialization phase (SOEL), or in R&D (AEMEL and PCCEL).
Our previous studies were based on specific use cases (fixed hypotheses on the size of the factory, the source of electricity, the technology, etc.).
The objective of this new work is to be able to position the different electrolysis technologies according to parameters which will be defined at the start of the project, these parameters being of a contextual type (e.g. number of operating hours, expected flexibility), technical ( ex yield, lifespan) or technical-economic (ex CAPEX OPEX) and environmental (ex GHG impacts, materials). The aim here will be to develop an original methodology which makes it possible to define the areas of relevance of each of the electrolysis technologies according to these parameters, depending for example on the cost of the hydrogen produced and its environmental impact
Advanced reconstruction methods for cryo-electron tomography of biological samples
Cryo-electron tomography (CET) is a powerful technique for the 3D structural analysis of biological samples in their near-native state. CET has seen remarkable advances in instrumentation in the last decade but the classical weighted back-projection (WBP) remains by far the standard CET reconstruction method. Due to radiation damage and the limited tilt range within the microscope, WBP reconstructions suffer from low contrast and elongation artifacts, known as ‘missing wedge’ (MW) artifacts. Recently, there has been a revival of interest in iterative approaches to improve the quality and hence the interpretability of the CET data.
In this project, we propose to go beyond the state-of-the-art in CET by (1) applying curvelet- and shearlet-based compressed sensing (CS) algorithms, and (2) exploring deep learning (DL) strategies with the aim to denoise et correct for the MW artifacts. These approaches have the potential to improve the resolution of the CET reconstructions and facilitate the segmentation and sub-tomogram averaging tasks.
The candidate will conduct a comparative study of iterative algorithms used in life science, and CS and DL approaches optimized in this project for thin curved structures.
Simulation of thermal transport at sub-Kelvin
Thermal management in quantum computers is an urgent and crucial task. As the number of qubits rapidly scales, more electric circuits are placed close to qubits to operate them. Joule-heating of these circuits could significantly warm the qubit device, degrading its fidelity. With intensive activity in quantum computing at Grenoble, we (CEA-LETI, Grenoble, France) are looking for an enthusiastic post-doc researcher to study thermal transport at cryogenic temperature (sub-Kelvin).
The post-doc will apply the finite-element non-equilibrium Green’s function [1], developed in the group of Natalio Mingo at CEA-Grenoble, to simulate phonon transport in various designed structures. The simulation result promotes comparison with on-going experiments and constructive discussions in order to optimize the thermal management.
[1] C. A. Polanco, A. van Roekeghem, B. Brisuda, L. Saminadayar, O. Bourgeois, and N. Mingo, Science Advances 9, 7439 (2023).
Exploring microfluidic solutions for manufacturing targets for fusion power generation
As part of a call for projects on "innovative nuclear reactors", the TARANIS project involves studying the possibility of energy production by a power laser-initiated inertial confinement fusion power plant. The current context, which encourages the development of low-carbon energies, and the fusion experiments carried out by the NIF's American teams, make it very attractive to conduct high-level research aimed at eventually producing an economically attractive energy source based on inertial fusion.
Among the many technical hurdles to be overcome, the production of fusion targets with a suitable reaction scheme compatible with energy production is a major challenge. The CEA has the know-how to produce batches of capsules containing the fusible elements of the reaction. However, the current process is not suitable for mass production of hundreds of thousands of capsules per day at an acceptable cost.
One high-potential avenue lies in the use of microfluidic devices, for which the Microfluidic Systems and Bioengineering Laboratory (LSMB) of the Health Technologies and Innovation Department (DTIS) of CEA's DRT has recognized expertise.
Development of noise-based artifical intellgence approaches
Current approaches to AI are largely based on extensive vector-matrix multiplication. In this postdoctoral project we would like to pose the question, what comes next? Specifically we would like to study whether (stochastic) noise could be the computational primitive that the a new generation of AI is built upon. This question will be answered in two steps. First, we will explore theories regarding the computational role of microscopic and system-level noise in neuroscience as well as how noise is increasingly leveraged in machine leaning and artificial intelligence. We aim to establish concrete links between these two fields and, in particular, we will explore the relationship between noise and uncertainty quantification.
Building on this, the postdoctoral researcher will then develop new models that leverage noise to carry out cognitive tasks, of which uncertainty is an intrinsic component. This will not only serve as an AI approach, but should also serve as a computational tool to study cognition in humans and also as a model for specific brain areas known to participate in different aspects of cognition, from perception to learning to decision making and uncertainty quantification.
Perspectives of the postdoctoral project should inform how future fMRI imaging and invasive and non-invasive electrophysiological recordings may be used to test theories of this model. Additionally, the candidate will be expected to interact with other activates in the CEA related to the development of noise-based analogue AI accelerators.
Development of piezoelectric resonators for power conversion
CEA-Leti has been working to improve energy conversion technologies for over 10 years. Our research focuses on designing more efficient and compact converters by leveraging GaN-based transistors, thereby setting new standards in terms of ultra-fast switching and energy loss reduction.
In the pursuit of continuous innovation, we are exploring innovative paths, including the integration of piezoelectric mechanical resonators. These emerging devices, capable of storing energy in the form of mechanical deformations, offer a promising perspective for increased energy density, particularly at high frequencies (>1 MHz). However, the presence of parasitic resonance modes impacts the overall efficiency of the system. Therefore, we are in need of an individual with skills in mechanics, especially in vibrational mechanics, to enhance these cleanroom-manufactured micromechanical resonators.
You will be welcomed in Grenoble within a team of engineers, researchers and doctoral students, dedicated to innovation for energy, which combines the skills of microelectronics and power systems from two CEA institutes, LETI and LITEN, close to the needs of the industry (http://www.leti-cea.fr/cea-tech/leti/Pages/recherche-appliquee/plateformes/electronique-puissance.aspx).
If you are a scientifically inclined mind, eager to tackle complex challenges, passionate about seeking innovative solutions, and ready to contribute at the forefront of technology, this position/project represents a unique opportunity. Join our team to help us push the boundaries of energy conversion.
References : http://scholar.google.fr/citations?hl=fr&user=s3xrrcgAAAAJ&view_op=list_works&sortby=pubdate
Modeling of charge noise in spin qubits
Thanks to strong partnerships between several research institutes, Grenoble is a pioneer in the development of future technologies based on spin qubits using manufacturing processes identical to those used in the silicon microelectronics industry. The spin of a qubit is often manipulated with alternating electrical (AC) signals through various spin-orbit coupling (SOC) mechanisms that couple it to electric fields. This also makes it sensitive to fluctuations in the qubit's electrical environment, which can lead to large qubit-to-qubit variability and charge noise. The charge noise in the spin qubit devices potentially comes from charging/discharging events within amorphous and defective materials (SiO2, Si3N4, etc.) and device interfaces. The objective of this postdoc is to improve the understanding of charge noise in spin qubit devices through simulations at different scales. This research work will be carried out using an ab initio type method and also through the use of the TB_Sim code, developed within the CEA-IRIG institute. This last one is able of describing very realistic qubit structures using strong atomic and multi-band k.p binding models.