Highgly reflective materials laser microwelding
In the frame of the Simulation Program, CEA/DAM conducts experiments on high powerful lasers involving complex targets. Intensive research is therefore conducted to study and manufacture a large panel of targets - with ambitious scientific and technological challenges ahead. In particular, CEA wants to extend its laser microwelding capabilities–at a sub-mm scale. The challenge is to weld both high-reflective and thin materials (aluminum, copper, gold …) with an accurate mastering of heat deposition and penetration depth. The goal is to implement, optimize and qualify a process based on the latest source generation (UV or green laser source), and to get an innovative set of experimental data. A phenomenological model might also be proposed.
The latest generation of laser source emitting in visible wavelengths (green, blue) will be exploited. He/she will participate in the design and qualification testing of the laser station associated with this new source. Once validated, he/she will carry out the study of the operational and metallurgical weldability of the sub-elements. He/she will compare his/her results with the use of a pulse infrared laser. He/she will appraise the joints obtained using different approaches and optimize the design of the welded joints. Its experimental study will go as far as carrying out functional tests on prototypes. External collaborations will be set up to compare the results obtained with simulations in order to deduce a phenomenological model.
Development of artificial intelligence algorithms for narrow-band localization
Narrowband (NB) radio signals are widely used in the context of low power, wide area (LPWA) networks, which are one of the key components of the Internet-of-Things (NB-IoT). However, because of their limited bandwidth, such signals are not well suited for accurate localization, especially when used in a complex environment like high buildings areas or urban canyons, which create signals reflections and obstructions. One approach to overcome these difficulties is to use a 3D model of the city and its buildings in order to better predict the signal propagation. Because this modelling is very complex, state-of-the art localization algorithms cannot handle it efficiently and new techniques based on machine learning and artificial intelligence should be considered to solve this very hard problem. The LCOI laboratory has deployed a NB-IoT network in the city of Grenoble and is currently building a very large database to support these studies.
Based on an analysis of the existing literature and using the knowledge acquired in the LCOI laboratory, the researcher will
- Contribute and supervise the current data collection.
- Exploit existing database to perform statistical analysis and modelling of NB-IoT signal propagation in various environments.
- Develop a toolchain to simulate signal propagation using 3D topology.
- Refine existing performance bounds through a more accurate signal modelling.
- Develop and implement real-time as well as off line AI-based localization algorithms using 3D topology.
- Evaluate and compare developed algorithms with respect to SoTA algorithms.
- Contribute to collaborative or industrial projects through this research work.
- Publish research papers in high quality journals and conference proceedings.
Design and fabrication of the magnetic control of 1.000 qubits arrays
Quantum computing is nowadays a strong field of research at CEA-LETI and in numerous institutes and companies around the world. In particular, RF magnetic fields allow to control the spin of silicon qubits, and pathway for large scale control is a real technological challenge.
The bibliographic analysis and the studies already carried out will able to draw out the pros and cons of the various existing solutions. In collaboration with integration, simulation and design staff, a proof of concept will be develloped and fabricated.
Synthesis by 3D printing of functionnalized geopolymer membrane for the treatment of complex radioactive effluents.
In the field of the treatment of liquid radioactive wastes on solid supports, the development of new composite materials synthetized by 3D printing under filtre shape is of primary of importance to decontaminate some radioactive effluents.
In this phD proposal, we propose to develop a membrane allowing to produce, from effluent containing somes traces of micronic solids in suspension and ionic species, a clarified effluent compatible with a nuclear outlet pipe. The challenge is to study the shaping of a material in a form of a filtration membrane allowing to trap in a single step an effluent containing some solids in suspension and some ionic species. In order to develop both functionnalities, 3D printing will be used to synthetise multiscale porous ceramic composites such as some geopolymers functionnalized by a selective adsorbants. The candidate, mainly based at CEA/ISEC Marcoule, could first formulate a functionnalized geopolymer paste with suitable rheological properties compatible with the constraints of the 3D printing process. A cross-flow filtration membrane with a controled macroporous network will be then printed by optimizing the geometry of the mesh. Finally, some sorption and cross-flow filtration tests will be performed on some model effluents containing calibrated solid in suspension and ions of interest such as Cs and Sr. The relevance of the printed membrane architecture will be assessed in relation to the capture of the solids and radioelements.
The candidate must have skills in the field of rheology, process and modeling. From this research work, job opportunities either in the field og 3D printing of materials or in the field of liquid waste treatment and depolution are potential options.
Auto-adaptive neural decoder for clinical brain-spine interfacing
CEA/LETI/CLINATEC invite applications for postdoctoral position to work on the HORIZON-EIC project. The project goal is to explore novel solutions for functional rehabilitation and/or compensation for people with sever motor disabilities using auto-adaptive Brain-Machine Interface (BMI) / neuroprosthetics. Neuroprosthetics record, and decode brain neuronal signal for activating effectors (exoskeleton, implantable spinal cord stimulator etc.) directly without physiological neural control command pass way interrupted by spinal cord injury. A set of algorithms to decode neuronal activity recorded at the level of the cerebral cortex (Electrocorticogram) using chronic WIMAGINE implants were developed at CLINATEC and tested in the frame of 2 clinical research protocols in tetraplegics in Grenoble and in paraplegics in Lausanne. The postdoctoral fellow will contribute to the next highly ambitious scientific breakthroughs addressing the medical needs of patients. The crucial improvement of usability may be achieved by alleviating the need of constant BMI decoder recalibration introducing an auto-adaptive framework to train the decoder in an adaptive manner during the neuroprosthetics self-directed use. Auto-adaptive BMI (A-BMI) adds a supplementary loop evaluating from neuronal data the level of coherence between user’s intended motions and effector actions. It may provide BMI task information (labels) to the data registered during the neuroprosthetics self-directed use to be employed for BMI decoder real-time update. Innovative A-BMI neural decoder will be explored and tested offline and in real-time in ongoing clinical trials.
Robotics Moonshot : digital twin of a laser cutting process and implementation with a self-learning robot
One of the main challenges in the deployment of robotics in industry is to offer smart robots, capable of understanding the context in which they operate and easily programmable without advanced skills in robotics and computer science. In order to enable a non-expert operator to define tasks subsequently carried out by a robot, the CEA is developing various tools: intuitive programming interface, learning by demonstration, skill-based programming, interface with interactive simulation, etc.
Winner of the "moonshot" call for projects from the CEA's Digital Missions, the "Self-learning robot" project proposes to bring very significant breakthroughs for the robotics of the future in connection with simulation. A demonstrator integrating these technological bricks is expected on several use cases in different CEA centers.
This post-doc offer concerns the implementation of the CEA/DES (Energy Department) demonstrator on the use case of laser cutting under constraints for A&D at the Simulation and Dismantling Techniques Laboratory (LSTD) at the CEA Marcoule.
Etudes et développement d’un système laser dans l’UV pour la démonstration à l’échelle laboratoire de l’épuration isotopique du palladium (naturel).
Le palladium est un métal rare dont la demande mondiale est en forte augmentation. Or, il est présent en tant que produit de fission dans les combustibles nucléaires usés qui sont retraités en France. Il serait donc intéressant de recycler ce métal. Pour cela, il est nécessaire de procéder à une épuration isotopique, afin de supprimer un des isotopes du palladium, le 107, qui est un radionucléide artificiel à vie longue émetteur béta. Dans le cadre d'un nouveau projet sur 4 ans construit en réponse à l'appel d'offre du Plan d'Investissement et d'Avenir de l’État, le Service d’Etude des Procédés d’Enrichissement propose un contrat post-doctoral portant sur le développement d’un système laser dans l’UV pour le procédé de séparation isotopique du palladium par Lasers actuellement en cours de développement. L’objectif principal du projet est la démonstration finale de la faisabilité de séparation de palladium naturel (et non radioactif) pour la phase suivante de développement d’un premier pilote.
Le post-doctorant devra développer des lasers prototypes de procédé à haute cadence en partant du visible (système lasers colorant) jusqu’à l'UV. Le passage dans l’UV se fait par doublage de fréquence avec des objectifs élevés en terme de performance. Il s’agit d’utiliser un cristal doubleur de fréquence de type BBO, LBO, KDP ou autre. Pour ce faire, le post-doctorat participera à la définition de ce cristal, mais aussi au développement de l’environnement du cristal doubleur (comportement, performances attendues et la tenue au flux des différents matériels). Des échanges seront mis en place sur ce sujet spécifique avec des spécialistes reconnus au sein de la Direction de la Recherche Fondamentale du CEA. La programmation (en Python et/ou sous Labview) de ces outils ou asservissements est à développer également. Une attention particulière sera portée sur les publications à réaliser essentiellement dans le cadre du doublage de fréquence, sujet complexe très étudié mondialement.
Decentralized Solar Charging System for Sustainable Mobility in rural Africa
A novel stand-alone solar charging station (SASCS) will be deployed of in Ethiopia. Seeing as 45% of Sub-Saharian Africa’s population lacks direct access to electricity grids and seeing as the the infrastructure necessary to reliably harness other energy sources is largely non-existent for many such populations in Ethiopia, introducing the SASCS among some of the country’s rural communities is a necessary effort. It could ostensibly invigorate communities’ agricultural sector and support those whose employment is rooted in farming. A SASCS could also serve to integrate renewable energy within the country’s existing electricity mix. CEA INES will act as a consulting Partner for the design and implementation of the solution (second life batteries, solar will be investigated). In addition, because of CEA INES’s established expertise in the installation of solar tools within various communities, the initiative will also provide know-how for the installation of the SolChargE in Ethiopia as well as cooperate on workshops for students and technicians employed by the project.
Development of large area substrates for power electronics
Improving the performance of power electronics components is a major challenge for reducing our energy consumption. Diamond appears as the ultimate candidate for power electronics. However, the small dimensions and the price of the substrates are obstacles to the use of this material. The main objective of the work is to overcome these two difficulties by slicing the samples into thin layers by SmartCut™ and by tiling these thin layers to obtain substrates compatible with microelectronics.
For this, various experiments will be carried out in a clean room. Firstly, the SmartCut™ process must be made more reliable. Characterizations such as optical microscopy, AFM, SEM, Raman, XPS, electrical, etc. will be carried out in order to better understand the mechanisms involved in this process.
The candidate might be required to work on other wide-gap materials studied in the laboratory such as GaN and SiC, which will allow him to have a broader view of substrates for power electronics.