Nanofabrication of spintronic spiking neurons
In the frame of the French national ANR project SpinSpike, Spintec laboratory is opening a postdoctoral researcher position. The candidate will work in collaboration with UMPhy CNRS-Thales and Thales TRT. The objective is the realization of proof-of-concept magnetic tunnel junction based artificial spiking neurons able to generate spikes and propagate them between coupled artificial neurons.
The candidate should have a strong background in nanofabrication and should be familiar with common techniques of optical and e-beam lithography as well as different etching techniques. The candidate can also be involved in the electrical characterization of the devices.
The position is expected to start on April 1, 2021 and go on for up to 2 years jointly between the RF team and MRAM teams of Spintec. The contract will be managed by CEA and funded by ANR Agency.
We offer an international and competitive environment, state-of-the-art equipment, and the possibility to perform research at the highest level. We promote teamwork in a diverse and inclusive environment and welcome all kinds of applicants. Further information about Spintec laboratory www.spintec.fr .
Simulation of PEMFC flooding phenomena
The proton exchange membrane fuel cell (PEMFC) is now considered as a relevant solution for carbon-free electrical energy production, for both transport and stationary applications. The management of the fluids inside these cells has a significant impact on their performance and their durability. Flooding phenomena due to the accumulation of liquid water are known to impact the operation of the cells, causing performance drops and also damages that can be irreversible. With the use of thinner channels in ever more compact stacks, these phenomena are becoming more and more frequent. The objective of this post-doc is to progress in the understanding of flooding in PEMFCs. The work will consist in analyzing the link between the operating conditions, the design of the channels and the materials used in the cell. It will be based on a two-phase flow modeling approach at different scales, from the local scale at the channel-rib level, up to, via an upscaling approach, the level of the complete cell. The study will also be based on numerous experimental results obtained at the CEA or in the literature.
High entropy alloys determination (predictive thermodynamics and Machine learning) and their fast elaboration by Spark Plasma Sintering
The proposed work aims to create an integrated system combining a computational thermodynamic algorithm (CALPHAD-type (calculation of phase diagrams)) with a multi-objective algorithm (genetic, Gaussian or other) together with data mining techniques in order to select and optimize compositions of High entropy alloys in a 6-element system: Fe-Ni-Co-Cr-Al-Mo.
Associated with computational methods, fast fabrication and characterization methods of samples (hardness, density, grain size) will support the selection process. Optimization and validation of the alloy’s composition will be oriented towards two industrial use cases: structural alloys (replacement of Ni-based alloys) and corrosion protection against melted salts (nuclear application)
Eco-innovation of insulating materials by AI, for the design of a future cable that is long-lasting, resilient, bio-sourced and recyclable.
This topic is part of a larger upcoming project for the AI-powered creation of a new electrical cable for future nuclear power plants. The goal is to design cables with a much longer lifetime than existing cables in an eco-innovative approach.
The focus is on the cable insulation because it is the most critical component for the application and the most sensitive to aging. The current solution is based on adding additives (anti-rad and antioxidants) to the insulation to limit the effects of irradiation and delay aging as much as possible. However, there is another solution that has never been tested before: self-repairing materials.
The project to which this topic is attached aims to design and manufacture several test model of insulation specimens. With several test characterization protocols, in order to verify the gain in terms of reliability and resilience. The results obtained will begin to fill a future database for the AI platform Expressif, developed at CEA List, which will be used to design the future cable.
Contribution to the metrological traceability of emerging alpha-emitting radiopharmaceuticals in the framework of the european AlphaMet project (Metrology for Emerging Targeted Alpha Therapies)
The Laboratoire national Henri Becquerel (LNE-LNHB) at CEA/Saclay is the laboratory responsible for the french references in the field of ionizing radiation. The LNHB is involved in the european EPM AlphaMet (Metrology for Emerging Targeted Alpha Therapies) submitted under the Metrology support for Health call (2022) to provide metrological support for clinical and preclinical studies; it began in September 2023 for a total duration of three years. The project comprises four Work Packages (WP) targeting different issues, with WP1 in particular dedicated to activity metrology and nuclear data measurements for imaging and dosimetry. This project aims at to improve the metrological traceability of emerging alpha-emitting radiopharmaceuticals such as 211At, 212Pb/212Bi, 225Ac.
The candidate will participate in the various tasks defined as part of the European AlphaMet project in which the LNHB is involved. Radiation-matter simulations will be carried out to study the response of the laboratory's ionisation chambers in various situations concerning: (i) the evolution of the response during the in-growth of the ?-emitting progeny of 225Ac, (ii) the quantification of the influence of the 210At impurity in the case of the measurement of 211At, and (iii) the search for a long-lived radionuclide surrogate of 212Pb for the quality control of dose calibrators. The candidate will also be involved in setting up a new device aimed at improving the linearity of the measurement of half-life with an ionization chamber. During the post-doctoral stay at LNHB, the candidate will interact with the various partners in the AlphaMet project (activity metrology laboratories, hospitals, clinical study centres).
The initial duration of the post-doctorate is 12 months (renewable) at the Laboratoire National Henri Becquerel (CEA/Saclay). It is hoped to start in the first half of 2024.
Development of innovative metal contacts for 2D-material field-effect-transistors
Further scaling of Si-based devices below 10nm gate length is becoming challenging due to the control of thin channel thickness. For gate length smaller than 10nm, sub-5nm thick Si channel is required. However, the process-induced Si consumption and the reduction of carrier mobility in ultrathin Si layer can limit the channel thickness scaling. Today, the main contenders that allow the extension of the roadmap to ultra-scaled devices are 2D materials, particularly the semiconducting transition metal dichalcogenides (TMD). Due to their unique atomically layered structure, they offer improved immunity to short-channel-effects in comparison to usual Si-based field-effect-transistors (FETs). This makes them very attractive for the application of more-Moore electronics.
However, the scalability of MOSFET device and the introduction of new material make source and drain contact a major issue. If many efforts have been made, in the past years, to reduce Fermi level pinning and Schottky barrier height, for many, these approaches are not industrially scalable. The main objective of this work is then to propose an in-depth understanding of electrical contact characteristics (based on different material) to identify the lowest contact resistance. The processes involved, offering an optimal contact resistance, must be compatible with wafer-scale processing for an integration in our 200/300mm advanced CMOS platform. The post-doc will in-depth study mechanisms enabling the formation of small contact resistances (between MoS2 and metal). It will have to identify the most promising contact material and to develop the associated deposition processes (ALD/PVD). Finally, electrical characterization of contact will be performed to qualify both material and interfaces enabling optimal operation of future 2D FETs
Development and application of TERS/TEPL technique for advanced characterization of materials
TERS/TEPL (Tip-Enhanced Raman Spectroscopy and Tip-Enhanced Photoluminescence) are powerful analytical techniques developed for nanoscale material characterization. The recent acquisition of a unique and versatile TERS/TEPL equipment at PFNC (Nano-characterization Platform) of CEA LETI opens up new horizons for materials characterization. This tool combines Raman spectroscopy, photoluminescence, and scanning probe microscopy. It features multi-wavelength capabilities (from UV to NIR), allowing a wide range of applications and providing unparalleled insights into the composition, structure, and mechanical/electrical properties of materials at nanoscale resolution. The current project aims to develop and accelerate the implementation of the TERS/TEPL techniques at PFNC to fully exploit its potential in diverse ongoing projects at CEA-Grenoble (LETI/LITEN/IRIG) and with its partners.
Batteries recycling :Development and understanding of a new deactivation concept of lithium ion domestic batteries
Domestic lithium ion batteries gather all batteries used in electronic devices, mobile phone, and tooling applications. By 2030, the domestic lithium-ion battery market will increase up to 30%. With the new European recycling regulation and the emergency to find greener and safer recycling process, it is today necessary to develop new deactivation process of domestic lithium ion batteries.
The process has to address several lithium ion chemistries, be continuous, safe, controllable and low cost.
To develop this new concept, the first step will be to define the most appropriate chemical systems. Then these chemical systems will be tested in a dedicated experimental laboratory setup using chemistry and electrochemistry, allowing the simulation of real conditions of domestic batteries deactivation.
The third step will be to characterize, understand and validate the electrochemical and physico chemical mechanisms. The last step will be to participate to the validation of the deactivation concept on a real object (a lap top battery) in representative conditions (on the abuse tests plateform of CEA).
Unsupervised Few-Shot Detection of Signal Anomalies
Our laboratory, located at Digiteo in CEA Saclay, is looking for a postdoc candidate working on the subject of anomaly detection in manufacturing processes, for a duration of 18 months starting from Feburary 2022. This postdoc is part of HIASCI (Hybridation des IA et de la Simulation pour le Contrôle Industriel), a CEA LIST project in an internal collaboration which aims at building a platform of AI methods and tools for manufacturing applications, ranging from quality control to process monitoring. Our laboratory contributes to HIASCI by developping efficient methods of anomaly detection in acoustic or vibrational signals, operating with small amounts of training data. In this context, the detection of signal anomalies (DSA) consists of extracting from data the information about the physical process of manufacturing, which is in general too complex to be fully understood. Moreover, real data of abnormal states are relatively scarce and often expensive to collect. For these reasons we privilege a data-driven approach under the framework of Few-Shot Learning (FSL).
Scalable digital architecture for Qubits control in Quantum computer
Scaling Quantum Processing Units (QPU) to hundreds of Qubits leads to profound changes in the Qubits matrix control: this control will be split between its cryogenic part and its room temperature counterpart outside the cryostat. Multiple constraints coming from the cryostat (thermal or mechanical constraints for example) or coming from Qubits properties (number of Qubits, topology, fidelity, etc…) can affect architectural choices. Examples of these choices include Qubits control (digital/analog), instruction set, measurement storage, operation parallelism or communication between the different accelerator parts for example. This postdoctoral research will focused on defining a mid- (100 to 1,000 Qubits) and long-term (more than 10,000 Qubits) architecture of Qubits control at room temperature by starting from existing QPU middlewares (IBM QISKIT for example) and by taking into account specific constraints of the QPU developed at CEA-Leti using solid-state Qubits.