Scientific Direction
Transfer of knowledge to industry
Scientific Direction
Département Ingénierie Logiciels et Systèmes (LIST)
Lab.systèmes d'information de confiance, intelligents et auto-organisants
01-10-2019
SL-DRT-19-1032
sara.tucci@cea.fr
To make progress with respect to the state of the art, the objective of the thesis is to address the design and implementation of a graph-based blockchain based, inspired by Sycomore, but based on Proof-of-Stake and proper rewarding mechanisms. The proposed protocol must ensure security and scalability assuming a mix of rational, malicious and honest participants and network mis-behavior ? the adversary model. Resilience to misbehavior will be evaluated using both empirical and analytical approaches. The following research questions will be addressed - How to adapt the Sycomore protocol under the Proof-of-Stake paradigm in a permission-less setting ? How to properly design the selection and rewarding mechanisms? Which kind of consistency can be achieved and under which conditions ? - Would it be possible to optimize the PoS graph-based protocol in a permissioned setting to assure stronger consistency and higher throughput ? What model for the adversary in the permissioned model ? References [1]Emmanuelle Anceaume, Antoine Guellier, Romaric Ludinard, Bruno Sericola: Sycomore: A Permissionless Distributed Ledger that Self-Adapts to Transactions Demand. NCA 2018: 1-8 [2]Emmanuelle Anceaume, Antonella Del Pozzo, Romaric Ludinard, Maria Potop-Butucaru, Sara Tucci Piergiovanni: Blockchain abstract data type: to appear in SPAA 2019 [3]Alejandro Ranchal Pedrosa, Maria Potop-Butucaru, Sara Tucci Piergiovanni: Scalable lightning factories for Bitcoin. SAC 2019: 302-309 [4]Yackolley Amoussou-Guenou, Bruno Biais, Maria Potop-Butucaru, Sara Tucci Piergiovanni: Rationals vs Byzantines in Consensus-based Blockchains. CoRR abs/1902.07895 (2019) [5] Yackolley Amoussou-Guenou, Antonella Del Pozzo, Maria Potop-Butucaru, Sara Tucci Piergiovanni: Correctness of Tendermint-Core Blockchains. OPODIS 2018: 16:1-16:16
DM2I (LIST)
Laboratoire Capteurs et Architectures Electroniques
01-10-2019
SL-DRT-19-1033
gwenole.corre@cea.fr
Machine learning classification methods have become ubiquitous in the fields of signal and image processing. Nevertheless, these classification methods remain very little used today in the fields of embedded applications. In fact, several studies have shown that machine learning classification methods provide satisfactory performance in classifying signals received from radiological sensors. However, most of these studies and solutions have been developed and experimented offline, and there are few or no real-time neural network learning based solutions. The aim of the thesis is to propose learning methods that can be embedded in real-time portable measurement devices. The proposed methods have to meet the radiological signal classification constraints and to enhance the performance of these measurement devices.
Département Thermique Biomasse et Hydrogène (LITEN)
Laboratoire Conception et Assemblages
01-11-2019
SL-DRT-19-1038
laurent.briottet@cea.fr
GRTgaz is currently studying the opportunity to introduce some hydrogen content in the existing natural gas transport grid. It is thus necessary to quantify the deleterious effect of this hydrogen content on the mechanical behaviour of the pipe steels. The proposed work will specifically addressed the effect of NG/H2 blend on the cyclic behaviour of these materials. First, fatigue crack propagation tests will be performed to obtain the propagation laws depending on the hydrogen content. Second, the crack initiation and propagation mechanisms will be carefully addressed through low cycle fatigue tests and specific analysis (SEM, EBSD, TEM).Finally, the obtained results should help GRTgaz to adapt their own defects acceptance criteria in presence of NG/H2 blends.
Département technologies silicium (LETI)
Autre laboratoire
01-10-2019
SL-DRT-19-1048
denis.rouchon@cea.fr
2D-materials, especially transition metal dichalcogenides (TMD), have recently received considerable attention since they are emerging as a class of exceptional semiconductor materials with many potential applications (supercapacitors, batteries, electronics and opto-electronics, flexible electronics ...). However, a sizeable bottleneck for their full deployment stems from the lack of scalable fabrication methods with atomic scale precision. Both Atomic Layer Deposition (ALD) and Molecular Layer Deposition (MLD) are based on sequential, self-limiting surface reactions that allow conformal film growth with precise thickness control. They are ideal techniques for depositing scalable ultrathin inorganic and organic films. The thesis project aims to achieve the synthesis of intermediate layered metal-organic hybrid films by a combination of Atomic Layer Deposition and Molecular Layer Deposition (ALD/MLD) followed by mild thermal treatment (annealing) en route to the crystalline final phase. The targeted materials are first TiS2 then SnS2. We want to explore with the thermal treatment a possible route to synthesize graphitic interfaces which could allow new electrodes or electrical contacts. Provide an atomic-level insight and control over the growth by combining ab initio calculations (not to be performed by the PhD student) and in situ chemical and structural studies performed during the growth and thermal treatment, i.e. in situ X-ray absorption and scattering with custom-built equipment, in situ Raman scattering, residual gas analysis, ellipsometry
Département d'Optronique (LETI)
Laboratoire d'integration technologique pour la photonique
01-10-2019
SL-DRT-19-1055
christophe.jany@cea.fr
For more than 25 years, the heart of telecom networks has become one of the fields of application of the III-V components (InP_like, and AsGa_like). This field is based on the transmission of IR waves in optical fibers, powered by laser sources in III-V materials. Over the past ten years, a new technological path has been developed, based Silicon-Photonics, which makes it possible to lower manufacturing costs by increasing integration (3D integration, Wafer Level Packaging). The approach usually chosen here consists of a molecular bonding of a III-V wafer (epitaxial) on an SOI previously structured optical guides. A technological treatment is then applied to make III-V transmitter guides connected to the silicon guides. Since less than 5 years; a new integration scheme is developing, it is the direct epitaxy of III-V materials on silicon. For 3 years, the CEA / LETI laboratories, already experts in the development of photonics on Silicon by bonding process, have decided to investigate this highly innovative approach with high potential. The proposed thesis will thus rely heavily on the CNRS / LTM laboratory, which has been developing for the last 4 years new MOCVD epitaxial concepts for III-V materials (AsGa base) on textured silicon wafer. This subject of study will enable the establishment of a new roadmap of III-V epitaxy on Silicon, with the aim of designing a new generation of photonic circuits. The PhD student will be involved both in the development of III-V materials on silicon, as well as in the design and realization of photonic circuits 2.0.
DM2I (LIST)
Laboratoire Capteurs et Architectures Electroniques
01-10-2019
SL-DRT-19-1069
adrien.sari@cea.fr
The management of radioactive waste packages is a major challenge for the nuclear industry. Characterization of the packages requires non-destructive nuclear measurement solutions in order to preserve the integrity of packages. The present thesis will focus on a concrete case of application which will consist in equipping with embedded sensors a six-axis robotic arm bearing a smear system, a contaminameter, and a gamma spectrometer. The robotic arm will allow multipoint measurements, in dose rate (with a Geiger-Müller type detector) and gamma spectrometry (with a CdZnTe detector). The drums to be characterized will have weak or medium activities, and the radioelements to be identified will be activation products and actinides. The aim of this thesis is to define a dynamic multipoint measurement method for optimizing the declaration of uncertainty associated with the quantity of interest (dose rate and activity). This thesis will include an MCNP6 simulation component and an experimental component.
