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Offers : 80

Optimization and Modeling of ISe using In Situ Characterization Technics (OPTIMISTIC)

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Start date : 1 November 2017

offer n° SL-DRT-17-0503

The detection of ionic species such as metal cations and inorganic anions is of the first importance for the monitoring of physiological disorders, process control for food or pharmaceutical industry, or environmental monitoring of soils and water. In an analytical point of view, ISEs (Ion Sensitive Electrodes) represent the sole systems enabling in situ real-time monitoring of small ion concentrations. Since a decade, CEA is involved in their integration on miniaturized multiparametric analytical platforms for artificial organs, point of care and environmental monitoring. Indeed, the masterpiece of ISEs deals with the ion selective membrane, which is fabricated from a complex formulation (polymer, plasticizer, ionophore, aliphatic charges and solvent). Surprisingly, the basic function of the membrane is still not well understood and poorly studied in a molecular point of view. However, taking account the target application that may requires either fast response time or wide stability, the formulation of the membrane has a great impact and has to be characterized finely in terms of intimate molecular behavior of the membrane to allow reliable optimization. The OpTIMISTIC thesis project deals with this deep comprehensive characterization of the membrane function (regarding for example the role of membrane componants and their temporal evolution as well as membrane aging phenomena). For this, fine comprehensive characterization of the membrane will be performed owing to electrochemical coupled methods (such as RMN, RX diffusion and scattering…) to obtain local and temporal behavior of the membrane components during measurement and aging. This experimental approach will be coupled to modelling studies using Multiphysics models to generate parametric analysis of the membrane function that will direct its optimization regarding target applications.

A research formation on electrochemistry and/or physicochemistry is prefered for the applicant.

  • Keywords : Physical chemistry and electrochemistry, Soft matter and complex fluids, DTBS, Leti
  • Laboratory : DTBS / Leti
  • CEA code : SL-DRT-17-0503
  • Contact :

SystemC Acceleration for multi-physics co-simulation and heterogeneous model complexity

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Start date : 1 October 2017

offer n° SL-DRT-17-0315

The increase in System-on-Chip (SoC) complexity, driven by the reduction in transistor size, called for a design flow integrating validation as early as possible in the design phases. The SystemC hardware description language, is widespread to model and simulate SoCs in this flow. It provides Virtual Prototypes (VP) that ease the development and validation of hardware/software integration in the earliest design phases.

The advent of Internet of Things (IoT) and more generally of autonomous systems requires simulation solution integrating at the same time processing elements but also external actioners and sensors. This calls for SystemC co-simulation with Multiphysics tools. As simulation speed is key to reduce design time and time to market, fast simulation solutions are needed.

CEA and Verimag have both developed state-of-the-art solutions for the acceleration of SystemC simulation. These approaches provide significant acceleration (more than one order of magnitude) to parallel models whose computing complexity is homogeneous. However, they fail to provide significant acceleration when heterogeneous model complexity is encountered. Such heterogeneity historically stemmed from various abstraction levels (CABA, TLM). But Multiphysics simulation will also exhibit strong variation in complexity due to the diversity of physical phenomena.

This thesis will target the definition of a novel parallel SystemC simulation kernel able to accelerate simulations in the context of Multiphysics co-simulation and heterogeneous complexity. To achieve this, the student will leverage the joint usage of state-of-art solutions. The work will take into account models’ synchronization frequencies so as to maximize their parallelism. The thesis will also target the identification of relevant hardware execution support for every SystemC model types, and use this knowledge to define adaptive scheduling of SystemC threads on heterogeneous computing architecture (CPU/GPU/FPGA).

  • Keywords : Engineering science, Computer science and software, Electronics and microelectronics - Optoelectronics, DACLE, Leti
  • Laboratory : DACLE / Leti
  • CEA code : SL-DRT-17-0315
  • Contact :

Innovative CVD growth of Metal-Organic Frameworks thin films

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Start date : 1 September 2017

offer n° SL-DRT-17-0271

Metal Organic Frameworks (MOFs) are periodic hybrid organic-inorganic crystalline materials issued form the periodic assembly of inorganic metallic nodes with polytopic organic bridging ligands. Among these materials, some identified structures have emerged which display nano-sized permanent microporosity coupled to a very large thermal and chemical stability. These materials have several potential applications (sensors, catalysts, insulators, battery electrolytes, materials for optoelectronic and non-linear optics). In particular, their very large specific surface areas (> 7000 m²/g, among the largest recorded for any materials) make them very uniquely adequate for applications in gas-separation or sensing.

These materials are generally synthetized via solution methods, which complicate the growth of performing thin films. Very recently, the first reports of Chemical Vapor Deposition (CVD) and/or Molecular Layer Deposition (MLD) routes have appeared. These breakthroughs pave the way to applications in micro- and nanotechnologies.

The work proposed herein aims at developing a CVD and/or MLD-based route for MOFs to be used for gas-sensing applications. Firstly, the gas-phase MOF growth through surface organometallic chemical approaches will be undertaken. In particular we will investigate the effect of varying surface pretreatment and post-synthesis activation routes on the growth parameters and on the final porosity of the materials. This task will include fine structural characterization of the grown MOF thin films (by X-ray diffraction, electronic microscopy), their chemical composition (by XPS, FTIR, ToF-SIMS) and porosity (by ellipso-porosimetry and GISAXS). The next task will focus on the development of sensitive microporous layers to allow the detection of small molecules (CH4, NOX, …). The most performing materials will be characterized under gas atmosphere firstly on simple sensors (on Quartz microbalance) and then in integrating devices (pre-concentrators).

  • Keywords : Engineering science, Chemistry, Materials and applications, DTSI, Leti
  • Laboratory : DTSI / Leti
  • CEA code : SL-DRT-17-0271
  • Contact :

Deep learning with attention model applied to occupation grid analysis

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Start date : 1 September 2017

offer n° SL-DRT-17-0331

This topic falls in the context of the development of autonomous vehicles, drones, and robotics.

The environment of the vehicle is described in an occupation grid, each cell of the grid containing the probability of occupation by an object. This grid is updated over time with sensors data.

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.

Most of the 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 occupation grids specific characteristics (lack of textures, a priori knowledge of areas of interest…). In this PhD, we want to explore new techniques, tailored to occupation grids, and more compatible with embedded and low cost implementation.

The purpose of this thesis is, starting from a fusion-based occupation grid, to get the contained objects, including their position, speed vector, and nature, by using attention-based artificial neuron networks.

  • Keywords : Engineering science, Computer science and software, DACLE, Leti
  • Laboratory : DACLE / Leti
  • CEA code : SL-DRT-17-0331
  • Contact :

Efficient single-photons source based on semiconductor nanowires

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Start date : 1 October 2017

offer n° SL-DRF-17-0322

The single-photons source is a key element in the framework of quantum communication and computing. Single-photons, emitted one by one and encoded by their polarization, act as flying qubits for the information exchanges. They are in particular required in many quantum cryptography protocols, intrinsically secure, that allow the transmission of a secret decryption key. Such a source can be obtained using semiconductor quantum dots as demonstrated in various material system. However such demonstrations were mostly restricted to cryogenic temperatures. Our group has demonstrated very recently that a CdSe quantum dot inserted in a ZnSe nanowire can emit single-photons up to room temperature [1]. This first demonstration for an epitaxial quantum dot opens the prospect for a realistic application of quantum dots in quantum information technologies. Moreover, the emission in the visible spectral range of these CdSe/ZnSe quantum dots is particularly well suited for communications in free space (for ground-satellite links for example) thanks to the transparency of the atmosphere and the availability of fast single-photon detectors in this spectral domain.

The PhD goal consists in developing efficient single-photons sources made of quantum dots formed in II-VI semiconductor nanowires. It will consist in investigating (i) the growth of core-shell type nanowire heterostructures in order to enhance the emission quantum yield, (ii) the coupling of these nano-emitters to various photonic structures for an efficient light extraction and collection, (iii) the possibility to implement an optical excitation with micro-laser for a compact device. These studies offer the possibility to explore basic physical phenomena (growth mechanisms, nanostructure-photon interaction etc…) at the nanometric scale while contributing to the development of an original and essential device for the field of quantum communication and quantum information processing.

[1] Ultrafast Room Temperature Single-Photon Source from Nanowire-Quantum Dots, S. Bounouar et al., Nano Lett. 12, 2977 (2012).

  • Keywords : Radiation-matter interactions, Solid state physics, surfaces and interfaces, INAC, PHELIQS
  • Laboratory : INAC / PHELIQS
  • CEA code : SL-DRF-17-0322
  • Contact :
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