Scientific direction Development of key enabling technologies
Transfer of knowledge to industry

PostDocs : selection by topics

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Development of lead free piezoelectric actuator

Département Composants Silicium (LETI)

Labo Composants Micro-actuateurs

01-02-2018

PsD-DRT-18-0033

gwenael.le-rhun@cea.fr

At CEA-Tech, the LETI Institute creates innovation and transfers it to industry. The micro-actuator component laboratory (LCMA) is working on the integration of piezoelectric materials into microsystems that allow electromechanical transduction. Lead zirconate titanate (PZT) is today the most powerful piezoelectric material for micro-actuator applications. However, the introduction in the near future of a new standard regarding the lead amount allowed in chips (European RoHS directive) leads us to evaluate alternative lead-free materials to PZT for piezoelectric actuator applications. The development of lead-free materials has thus become a major focus of piezoelectric research. This research led to revisit and modify some classical piezoelectric such as KNbO3 and BaTiO3. In particular, the KNaxNb1-xO3 (KNN) family has been identified as promising. The objective of the postdoc is therefore to evaluate some lead-free piezoelectric materials and to compare their properties with that of the reference material, PZT. Suitable test vehicles will be fabricated in LETI's clean rooms for electrical and piezoelectric characterizations by mean of dedicated tools already available at lab. For this work the candidate will lean on a solid experience developed at LETI for more than 20 years on piezoelectric thin films.

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Sizing and control optimisation of a hydrogen production system coupled with an offshore wind farm

DPLOIRE (CTReg)

Autre

01-03-2018

PsD-DRT-18-0034

guenael.lesolliec@cea.fr

Coupling MRE (Marine Renewable Energy) and hydrogen sectors reveal an important potential long-term assets. The MHyWind project suggests to estimate the energetic and economic potential of a hydrogen production system integrated into a substation of an offshore wind farm. The hydrogen produced and stored locally will be distributed by boat for harbour uses, as a replacement of fossil fuels. For that purpose, it will be organized a simulation which will integrate all the energy chain towards the harbour uses of hydrogen. It will allow to estimate various configurations and sizing according to the local uses, valuation leverages, control modes and behavior of the system. The criteria will be the producible (kg of H2 producted and used) and complet costs (CAPEX and OPEX). The objective of the postdoctoral student will be to develop the simulation tool on this applicative being fully integrated with the teams of concerned laboratories.

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Simultaneous Localisation and Mapping with an RGB-D camera based on a direct and sparse method

Département Intelligence Ambiante et Systèmes Interactifs (LIST)

Vision & Ingénierie des Contenus (SAC)

01-01-2018

PsD-DRT-18-0038

steve.bourgeois@cea.fr

Recent advances in the methods of locating a device (smartphone, robot) in relation to its environment make it possible to consider the deployment of augmented reality solutions and autonomous robots. The interest of RGB-D cameras in such a context is notable since it allows to directly acquire the depth map of the perceived scene. The objective of this post docorate consists in developping a new SLAM (Simultaneous Localisation and Mapping) method relying on a depth sensor. To reach a solution both robust, accurate and with small CPU/memory comsumption, the depth image will be exploited though a direct and sparse approach. The resulting solution will be then combined with the solution of "RGB SLAM Constrained to a CAD model" developped in our laboratory, resulting finaly in an "RGB-D SLAM Constrained to a CAD model"

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3D occupancy grid analysis with a deep learning approach

Département Architectures Conception et Logiciels Embarqués (LIST-LETI)

Laboratoire Infrastructure et Ateliers Logiciels pour Puces

01-02-2018

PsD-DRT-18-0042

remy.gauguey@cea.fr

The context of this subject is the development of autonomous vehicles / drones / robots. The vehicle environment is represented by a 3D occupancy grid, in which each cell contains the probability of presence of an object. This grid is refreshed over time, thanks to sensor data (Lidar, Radar, Camera). Higher-level algorithms, like path planning or collision avoidance, think in terms of objects described by their path, speed, and nature. It is thus mandatory to get these objects from individual grid cells, with clustering, classification, and tracking. Many previous publications on this topic comes from the context of vision processing, many of them using deep learning. They show a big computational complexity, and do not benefit from occupancy grids specific characteristics (lack of textures, a priori knowledge of areas of interest?). We want to explore new techniques, tailored to occupation grids, and more compatible with embedded and low cost implementation. The objective of the subject is to determine, from a series of 3D occupation grids, the number and the nature of the different objects, their position and velocity vector, exploiting the recent advances of deep learning on unstrucured 3D data.

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Ge-on-Insulator (GeOI) substrates for photonics

Département Composants Silicium (LETI)

Laboratoire Intégration et Transfert de Film

01-02-2018

PsD-DRT-18-0045

julie.widiez@cea.fr

The induction of tensile strain in intrinsic and doped Germanium (Ge) is one approach currently explored to transform the Ge indirect bandgap into a direct one. To take full advantage of Ge, we study the Ge CMOS photonics platform with Ge-on-Insulator (GeOI) structure, which enables strong 2D optical confinement in the Ge photonic-wire devices. One recent study in our lab showed the interest of a method of incorporation of mechanical stress into Ge, one of the essential ingredients of the laser. In particular, the method could be applied to the massive Ge, making compatible gap direct and crystalline quality. Post-doc objectives : Development of GeOI substrates from massive Ge donors with tensile strain inside the Ge film. These developments will be realized from the existing Smart Cut / thinning processes, combined with technological steps to overcome their current limits (SAB bonding). The substrates obtained will be characterized to determine their state of deformation as well as their damage (Raman / XRD) and final GeOI substrates will be provided to the application laboratories for the production of photonic components.

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Tunnel Junction for UV LEDs: characterization and optimization

Département d'Optronique (LETI)

Laboratoire des Matériaux pour la photonique

01-09-2018

PsD-DRT-18-0047

guy.feuillet@cea.fr

Besides existing UV lamps, UV LEDs emitting in the UV-C region (around 265 nm) are considered as the next solutions for cost efficient water sterilization systems. But existing UV-C LEDs based on AlGaN wide band gap materials and related quantum well heterostructures still have low efficiencies which precludes their widespread use in industrial systems. Analysing the reasons of the low efficiencies of present UV-C LEDs led us to propose a solution based on the use of a Tunnel Junction (TJ) inserted within the AlGaN heterostructure diode. p+/ n+ tunnel junctions are smart solutions to cope with doping related problems in the wide band gap AlGaN materials but give rise to extra tunneling resistances that need to be coped with. The post-doctoral work is dedicated to understanding the physics of tunneling processes in the TJ itself for a better control of the tunneling current. The post-doctoral work will be carried out at the ?Plate-Forme de Nanocaractérization? in CEA/ Grenoble, using different optical, structural and electrical measurements on stand-alone TJs or on TJs inserted within LEDs. The candidate will have to interact strongly with the team in CNRS/CRHEA in Sophia Antipolis where epitaxial growth of the diodes will be undertaken. The work is part of a collaborative project named "DUVET" financed by the Agence Nationale de la Recherche (ANR).

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