Couplings between the distributions of water and current density in operating Proton Exchange Membrane Fuel Cell (PEMFC)
The post-doc work will be focused on the measurement of the current density and of the water distributions in an operating fuel cell with a real design, in order to give a better understanding of PEMFC operation as a function of the operating parameters (Temperature, Gas hydration, Pressure, Gas composition). The measurement of the distribution of the current density will be performed using a reliable commercial setup on a full size cell. CEA developed a technique based on Small Angle Neutron Scattering (SANS) as a non-intrusive tool in order to quantify the water distribution during fuel cell operation within and without the membrane. CEA benefits for international recognition on this topic. These measurements will be conducted in high flux neutron reactors, such Institut Laue Langevin (ILL). Some specific high and low resolution neutron imaging experiments could be also be conducting additionally in order to have a complete 3D view of water repartition.
Minimizing modifications at III-V pattern sidewalls after plasma etching for heterointegrated optoelectronics and nonlinear photonics
This project will focus on understanding plasma-induced damage at the sidewalls of micro-nano-patterned III-V semiconductors to find relevant technological solutions capable to minimize this damage. There is a clear need of knowledge on by which mechanisms and to what extent the plasma etching process modifies the III-V pattern sidewalls and the consequences it has on the device optical performances. The selected III-V semiconductor will be aluminium gallium arsenide which exhibits excellent optoelectronic properties and strong nonlinear parametric gain.
The student will be mainly focused on understanding how the key plasma process parameters influence the structural and chemical changes at the III-V sidewalls, as well as changes of optical properties. This will require the development of a methodology for a 3D quantitative characterization of the sidewalls at the nanoscale, based on Auger microscopy and cathololuminescence. The main objective will be to correlate plasma-induced structural defects and modifications of the optoelectronics properties. The second step will consist in developing optimized plasma etching processes for III-V semiconductors, exploring alternative plasma technologies. You will also be involved in the development of processes for restoring and passivating the AlGaAs sidewalls.
DTCO analysis of MRAM for In/Near-Memory Computing
The energy cost associated to moving data across the memory hierarchy has become a limiting factor in modern computing systems. To mitigate this trend, novel computing architectures favoring a more local and parallel processing of the stored information are proposed, under the labels « Near/In-Memory Computing » or « Processing In Memory ». Substantial benefits are expected in particular for computationally complex (e.g. combinatorial optimization, graph analysis, cryptography) and data-intensive tasks (e.g. video stream analysis, bio-informatics). Such applications are especially demanding in terms of endurance, latency and density. SRAM, fulfilling the first two criteria, may eventually suffer from its footprint and static power consumption. This prompts the evaluation of alternative denser and non-volatile memory technologies, with magnetoresistive memories (MRAM) currently leading in terms of speed-endurance trade-off.
The primary objective will be to estimate improvements brought by MRAM in terms of array-level power, performance, area (PPA), as compared to SRAM-based on-chip memories and for advanced technology nodes. The candidate will establish an analysis and benchmarking workflow for various classes of MRAM, and optimize single bit cells based on a compact model for the memory element. This baseline approach will then be adapted to functional variations specific to IMC in order to assess the benefits of MRAM on an integrated test vehicle.
Combinatorial optimization of base materials for the design of new materials
The design of new materials is a field of growing interest, especially with the emergence of additive manufacturing processes, thin film deposition, etc. In order to create new materials to target properties of interest for an application area, it is often necessary to mix several raw materials.
A physicochemical modeling of the reactions that occur during this mixing is often very difficult to obtain, especially when the number of raw materials increases. We want to free ourselves as much as possible from this modeling. From experimental data and business knowledge, the goal of this project is to create a symbolic AI capable of groping for the optimal mixture to achieve one or more given properties. The idea is to adapt existing methods of operations research, such as combinatorial optimization, in a context of imprecise knowledge.
We will focus on different use cases such as electric batteries, solvents for photovoltaic cells and anti-corrosion materials.
Within the project, you will:
• Study the state of the art,
• Propose one or several algorithms to prototype, and their evaluation,
• Disseminate the resulting innovations to the consortium and the scientific community, through presentations, contributions to technical reports and / or scientific publications.
Maximum duration: 18-24 months (regarding your experience).
Modelling and evaluation of the future e-CO2 refinery
In the context of achieving carbon neutrality by 2050, the CEA has initiated a project in 2021 to assess the relevance of coupling a nuclear power system with a direct atmospheric carbon capture device (DAC) thanks to the use of the system's waste heat.
As a member of a team of about twenty experts(energy system evaluation, techno-economic engineering, energy system modeling, optimization and computer programming), you will participate in a research project on the modeling and evaluation of a CO2 refinery dedicated to the production of Jet Fuel fed by a nuclear reactor and coupled with an atmospheric CO2 capture process.
Detection of traces of narcotics in saliva by electrochemiluminescence on diamond electrodes
The consumption of narcotics is becoming a problem for road safety because 23% of road deaths in France occur in an accident involving at least one driver who tested positive. Thus, one objective of road safety in consultation with the concerned ministries (Ministry of Transport, Ministry of Interior, Ministry of Health and Ministry of Economy) is to improve the fight against road insecurity linked to narcotics consumption. In particular, this involves increasing and facilitating roadside checks using a portable device dedicated to controlling the use of narcotics on the roadside, similar to what is already done for breathalyzer tests. Such a device is not commercially available today. The main prerequisites of this device will be to provide reliable, immediate confirmation results with evidentiary value for the courts as well as a purchase cost compatible with large-scale deployment on French road networks. In this context, the subject of study proposed aims to study the possible detection of traces of narcotics in saliva using electroluminescence on a boron-doped diamond electrode. This method is considered promising for such an application because it potentially allows extremely low detection thresholds to be reached and, in accordance with legislative requirements, offers multiple possibilities aimed at achieving high selectivity towards chemical targets, with a high detection capacity. miniaturization of equipment and a relatively low cost of apparatus compared to analytical tools such as mass spectrometer, IMS, etc.
Design of Ising Machines based on a network of spintronics oscillators copled through CMOS circuitry
Our information and communication society is asking for always more computing tasks of increasing complexity. Their energy bargain increases quickly so that it is mandatory to find new architecture of computing processors with improved energy efficiency.
The post doc applicant will contribute to the design of Ising machines which are computing architectures inspired from biology and physics and which permit to solve complex optimization problems. Under the scope of SpinIM project (french ANR funding), the applicant will contribute to the demonstration of an Ising machine based on the electrical coupling of spin torque nano-oscillators (STNO). More specifically, the post doc role will be to design the configurable CMOS chip implementing the electrical coupling. He will have to propose a VerilogA model of the STNO with the help of Spintec experience on STNO theory. Then the post doc will have to propose an optimized design of the CMOS chip from schematics to layout and he will have to assess the chip performances in laboratory. Finally, the post doc will participate to the demonstration of the full Ising machine consisting of the CMOS chip and a STNO network on some optimization tasks. The post doc will take place in the LGECA laboratory of CEA-Leti which have gained experience on CMOS-Spintronics co-design.
Photonic Accelerators: Driving Innovation in Quantum Simulations
Photonic circuits, specialised low-power processors, are emerging as one of the most promising technologies for accelerating the execution of complex algorithms in the fields of machine learning and scientific computing, while maintaining low heat dissipation.
The success of simulating quantum systems and implementing quantum-inspired simulation algorithms on photonic units suggests the potential of these accelerators to advance computing capabilities in the fields of computational chemistry and materials science.
The aim of this project is to integrate photonic technologies with neural and tensor networks, pushing back the limits of quantum simulations and classical devices. This is a promising direction for the future of hardware-accelerated, specialised algorithmic innovation.
This research will focus on adapting algorithms to photonic devices, optimising energy consumption and developing new algorithms inspired by the specificities of hardware.
Optimization of Li metal/electrolyte for the next generation of all-solid-state battery
CEA Tech Nouvelle-Aquitaine, created in 2013, set up a new laboratory, since more than two years, focused on both the development of materials and the high throughput screening to accelerate the discovery of materials for the next generations of Li-ion batteries. For that, the CEA Tech Nouvelle-Aquitaine acquires different vacuum deposition equipment (sputtering, evaporation, atomic layer deposition) integrated in glovebox and different automated characterization techniques (SEM-EDX, profilometer, XRD, LIBS and confocal microscope later).
The Li metal/electrolyte interface constitutes one of the main challenges to overcome for the next generation of all-solid-state battery. The reactions of decompositions at the interface associated to uneven plating/stripping of Li ions lead to quick cell failure. One of the avenue for stabilizing it is to use a protective layer, which must feature numerous physical-chemical properties. In this context, this internal CEA project aims at setting up a combinatorial synthesis methodology associated to high throughput characterizations in order to accelerate the discovery of new protective layers at the Li metal/electrolyte interface.
We are seeking for an outstanding applicant who will be in charge of setting up the whole methodology, from the synthesis to the physical-chemical-electrochemical characterizations of the materials. She/he will have at her disposal a new state-of-the-art infrastructures. She/he will collaborate with other CEA labs located at LITEN (Grenoble, France).
Correlative X-ray and ToF-SIMS tomography Data fusion of 3-D data sets from X-ray and ToF-SIMS tomography
The nanocaracterisation platform of the CEA Grenoble has recently installed 2 state-of-the-art tools for 3-D imaging with 100 nm resolution: X-ray tomography in a SEM and time of flight secondary ion mass spectrometry (ToF-SIMS) assisted by focused ion milling (FIB). X-ray tomography delivers non-invasive 3-D images of the internal morphology of an object whilst ToF-SIMS is able to map the local composition in 3-D. We aim to combine the two techniques to perform quantitative 3-D investigations of objects such as copper pillars for microelectronics or silicon electrodes for Li battery applications.
The proposed research subject is data analysis orientated. Some simulation work may be performed to implement and test existing 3-D data fusion methods with a view to adapting and improving them. The candidate will assist with the experimental measurements and be responsible for treating the data with the chosen protocols. The candidate should be pragmatic, at ease with applied mathematics and have good programming skills. These will be essential in understanding and manipulating the fusion and reconstruction algorithms, from the simplest, to the increasingly advanced (prior information, superiorisation, Bayesian fusion)
The candidate will have completed a PhD in physics and have good computer (Python, Matlab, C) and image treatment skills, or a PhD in mathematics/computational science with an interest in applications. The candiate will need to interface with a multidisciplinary team, and be receptive to new ideas. The candidate will be proficient in both written and spoken English in order to communicate with the team and to disseminate their results in articles or at conferences.