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

PostDocs : selection by topics

Construction of databases for radionuclide identification based on neural networks (NANTISTA project)

DM2I (LIST)

Laboratoire de Métrologie de l'Activité

01-06-2015

PsD-DRT-15-0004

christophe.bobin@cea.fr

The project NANTISTA (Neuromorphic Architecture for Nuclear Threat Identification for SecuriTy Applications) deals with the prevention of illegal traffic of nuclear materials at international borders. The project aims at the development of a detection platform using plastic scintillators for fast radionuclide identification (such as fissile materials) based on neural networks. The post-doctoral subject consists in the development of the detection system and the construction of databases dedicated to the learning process and the optimization of the neural networks. The databases will be built with experimental measurements given by radioactive sources. Radiation-matter simulations (Monte-Carlo codes Geant4 and Penelope) will also be implemented for the construction of the databases.

Electric field and ab initio simulations, application to RRAM

Département Composants Silicium (LETI)

Laboratoire de Simulation et Modélisation

01-01-2016

PsD-DRT-16-0009

philippe.blaise@cea.fr

Since several years, LETI/DCOS is engaged in a simulation effort of microscopic phenomena at the heart of oxide-based RRAM operation (made of HfO2, Ta2O5, Al2O3). The correct description of an external electric field applied to a MIM device (Metal-Insulator-Metal) is now possible thanks to two methods one by an orbital separation approach [1] the other by using the non equilibrium green function formalism [2]. In this work, we propose to develop and to handle these methods by combining already existing simulation approaches. The main goal is to study the degradation mechanisms of an oxide by following the oxygen atoms movements coupled directly to the applied external electric field. These mechanisms are not known and this study will support the optimization and characterization efforts already engaged at LETI on RRAM functional prototypes. The targeted simulations tools are SIESTA for the DFT part, and TB_SIM for the electronic transport part. [1] S. Kasamatsu et al., « First principle calculation of charged capacitors under open-circuit using the orbital separation approach, PRB 92, 115124 (2015) [2] M. Brandbyge et al., « Density functional method for nonequilibrium electron transport », PRB 65, 165401 (2002)

Investigation of the reliability of Resistive RAMs for high density memories application

Département Composants Silicium (LETI)

Laboratoire de Composants Mémoires

01-03-2016

PsD-DRT-16-0016

gabriel.molas@cea.fr

In this postdoc, we propose to investigate Resistive memories (RRAM) as a Storage Class Memory (SCM) for high density memory applications. To this aim, both CBRAM and OXRAM will be studied and compared. RRAM technologies, integrating various resistive layers, top and bottom electrodes will be integrated. Then electrical characterization will be performed on these different memory options. The impact of the integration flow on the memory characteristics will be addressed, to evaluate how critical integration steps may impact the memory operation. In particular, MESA (the RRAM stack is etched) vs Damascene (the RRAM stack is deposited in a cavity) approaches will be compared. After the evaluation of the memory basic operation (forming, SET and RESET operation speed, required voltages?), a specific focus will be made on reliability. In particular, endurance will be deeply investigated and optimized. The impact of SET RESET conditions (including smart programming schemes) on the window margin and number of cycles will be analyzed. Finally, the variability issue will be highly covered, in order to quantify how cycle to cycle and device to device variability close the window margin of the RRAM. Specific reliability concerns (read noise?) will also be addressed. Extrapolations on the maximum density a given RRAM technology can reach will be drawn. Based on this detailed study, a benchmark of all the tested RRAM technologies will be made, to identify the pros and cons of each option, and highlight the tradeoff that have to be found (among them: memory speed, endurance, operating voltages, consumption?).

New packaging for power electronics : application to SiC components

Archive des laboratoires DRT (ne pas utiliser)

Laboratoire de Substrats Avancés

01-01-2016

PsD-DRT-16-0019

julie.widiez@cea.fr

In continuity of ongoing work (PhD thesis) on the 3D assembly of vertical Silicon power components, the purpose of the post-doc proposal is to develop a similar assembly on vertical wide-gap SiC power components. The required work will be to define the components (high frequency / high voltage) with the supplier and to adapt them to the best vertical integration (Cu finishing, topology,...), to adjust the metal leadframe design for the 3D assembly, and to develop the transfer layer technology adapted to this new material. The candidate will also take care of the electrical characterizations of the final stack to validate the interest of this 3D packaging on wide-gap power devices.

Département Composants Silicium (LETI)

Laboratoire Masques et Design Kits

01-01-2016

PsD-DRT-16-0023

fabien.gays@cea.fr

Microfluidic cell encapsulation

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Biologie et Architecture Microfluidiques

01-02-2015

PsD-DRT-15-0024

Luis-miguel.FIDALGO@cea.fr

The Laboratory of Biology and Microfluidic Architecture is looking for a candidate to establish a new class of microfluidic devices for cell encapsulation using robust, industry-compatible materials. The laboratory is located in the Microtechnologies for Biology and Healthcare Division of LETI, focused on the development of micro and nanotechnologies for applications in the fields of medical imaging, security, in-vitro diagnostic, nanomedicine, medical devices and environment monitoring. LETI is a research institution focused on creating value and innovation through technology transfer to its industrial partners. It specializes in nanotechnologies and their applications, from wireless devices and systems, to biology, healthcare and photonics.

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