Development of new processes for the fabrication of advanced interconnect structures of solar cells
The fabrication of solar cells with high performances at a reduced cost is a key challenge addressed by many research institutions and industrials worldwide. Many technological solutions are being investigated. Among them, a promising approach consists in forming narrower metal lines to limit shadowing of active areas of the cells. This work aims at replacing serigraphy by new fabrication processes able to reduce line width. For this purpose, the conducting substrate is coated by an insulating mask in which the lines are defined. The metal is then directly plated selectively onto the weakly conducting portions of the substrate, i.e. the lines, using electrolytic or electroless reactions. The process conditions will be adapted with regard to the nature of the initial conducting surfaces.
Design of a safe and secure hypervisor in the context of a manycore architecture
The TSUNAMY project aims at thinking the design of future manycore chips in a collaborative hardware/software approach. It will investigate how crypto-processors can be incorporated into such a chip, turning it into a heterogeneous architecture, where scheduling, resource allocation, resource sharing, and resource isolation will be a concern.
The LaSTRE laboratory has designed Anaxagoros, a micro-kernel which ensures good properties in terms of safety and integration of mixed-criticality applications and is therefore well suited to the virtualization of operating systems. Making this virtualization software layer evolve in the context of the TSUNAMY project is the main goal of this post-doctoral proposal.
The first issue to address deals with the scalability of Anaxagoros on a manycore architecture. This system was designed with multicore scalability in mind : to help reach the highest level of parallelism in a lock-free fashion, innovative techniques were proposed to minimize the amount of synchronization points within the system. This is the first step, but scaling to manycore architectures brings new topics such as cache-coherency or non-uniform memory access that require to focus on data locality as well. The second challenge will be to incorporate genuine security features into Anaxagoros, e.g. regarding protection from covert channels, or confidentiality. The third and final challenge that will be addressed through interactions with the partners of the project is to devise techniques that could be implemented directly in hardware in order to ensure that even a breach in what is usually considered as trusted software will not allow an attacker to gain unprivileged data access or let information leak.
Optimal Multi Agent System management of smart heat grid using thermal storage
The aim of this work is a major contribution to a software framework based on coupling of Modelica/Jade environments that will allow to model, to simulate and to optimise the control of smart heat grid through dedicated thermal storage models development: interface specification to control the storages in the grid, simplified models design of heat grid’s most crucial components to be integrated in Agents (production, distribution/storage, consumption) and design of consumption and production forecast models in order to manage anticipation and improve the overall efficiency. The evaluation of performance is based on the test case build in Modelica simulation environment.
Large-area processing and design of functional piezoelectric nanomaterials for flexible sensors and systems
CEA LETI develops innovative highly flexible strain sensors which exploit the piezoelectric properties of self-organized gallium nitride nanowires. The fabrication steps are basically: i) nanowire growth, ii) nanowire assembly, iii) encapsulation, iv) contacting. First demonstrators with small active area (1.5 cm²) have already been achieved using the Langmuir Blodgett (LB) technique for the assembly of nanowires. The present project is concerned with the scaling-up of the assembly process over large surface areas, as well as controlled patterning of nanowire assemblies in 1D and 2D by using an innovative CEA LITEN roll-to-roll technology called Boostream® which has the same functionalities as LB in its basic function.
The aim of the post doc is to develop a new building block for the Boostream® equipment enabling a controlled assembly of wires with a pre-defined design. The candidate will carry out studies to optimize the wire assembly, develop the process of film patterning and fabricate, integrate and characterize GaN nanowire piezoelectric transducers with dimensions of 15x15 cm².
More generally, this post doc will also provide the opportunity to develop a generic knowledge to manipulate micro or nano wires or fibers giving new solutions in various fields such as surface structuration, electronic skin, energy...
Internet of Things applications: Ultra Low power and adaptive analog-to-digital converters in advanced FD-SOI process
The post-doctoral project aims to study Ultra Low Power and Adaptive Analog-to-Digital Converter (ADC) over a wide operating range of microsystem from Internet of Things or sensor networks applications.
The ADC is one of the main blocks into System on Chip (SoC) because of its position between physical signal treatment (Front-End) and digital treatment (Digital Base Band). Its performances in terms of resolution or frequency ranges affect the overall performances of the SoC. A particular consideration will be carrying out on power consumption and some reconfigurability technics will be used to adapt its consumption to the contextual performances required. To reduce as possible the ADC consumption, advanced FDSOI process will be used.
Based on Ultra Low Power constraints, the post-doctorate student will study the literature and will propose, design and experimentally demonstrate a relevant topology to increase the power efficiency and the performances of ADC by using advanced FDSOI process.
Large scale visual recognition
This post-doc deals with detection and recognition of objects in images and video streams, on a large scale. This is a fundamental task that is the subject of active research in the world, including recent challenges in the evaluation campaigns. The "large scale" aspect refer to both large size databases (eg ten million images) and large number of concepts to recognize (eg 100-10000).The work will concern bothimage description and classification.
At the description level, state of the art techniques rely on local descriptors, aggregated according to dictionaries of "visual words" possibly constructed using Fisher kernels. It is nevertheless necessary to recode these signatures effectively in order to manage large databases. Regarding learning of visual concepts or objects, many algorithms use SVM (support vector machines) but other approaches are sometimes considered, such as those based on boosting or logistic regression.
The proposed position involves research and development of efficient algorithms to find visual entities in very large databases. Tracks are considered and should be discussed with the candidate selected based on prior knowledge and technical discussions.
In situ analytical device based on the LIBS technique for the characterization of hard environment liquid media
The proposed research project aims at developing an in situ analytical device based on the LIBS technique for the characterization of hard environment liquid media such as high temperature melting materials or highly volatile liquid metals used for development of low carbon energy production. The project involves two CEA teams specialized in LIBS instrumentation, analytical developments and high temperature environments.
At high temperature, the molten metals have a high surface reactivity leading to processes of oxidation, slagging … Non-intrusive analysis of this surface by traditional LIBS tools leads to a non-representative results of the molten metal chemical composition. In this project, a new-patented concept based on a mechanical stirring coupled to the LIBS device is developed in order to have a renewable and stable surface of the liquid metal. The aim is to have an on-line representative composition of the metal during the treatment process. The developed demonstrator will be validated for the analysis of impurities (at ppmw ranges) in liquid silicon (T> 1450 °C) during the purification process and the crystallization one for photovoltaic applications. At the end of the project, recommendations for in-situ analysis of liquid sodium (used as cooling fluid in nuclear reactors) will be given.
Machine learning technics and knowledge-based simulator combined for dynamic process state estimation
This project aims to estimate the real state of a dynamic process for liquid-liquid extraction through the real data record. Data of this kind are uncertain due to exogenous variables. They are not included inside the simulator PAREX+ dedicated to the dynamic process. So, the first part of the project is to collect data from simulator. By this way the operational domain should be well covered and the dynamic response recorded. Then, the project focuses to solve the inverse problem by using convolutionnal neural networks on times series. Maybe a data enrichment could be necessary to perfect zones and improve estimations. Finally, the CNN will be tested on real data and integrate the uncertainty inside its estimations.
At the end, the model built needs to be used in operational conditions to help diagnosis and improve the real-time control to ensure that the dynamic observed is the one needed.
Hydrothermal carbonization as a pretreatment of wastes before their thermochemical conversion by gasification
Gasification, a thermochemical transformation generally performed at about 850°C, produces a gas that can be valorised in cogeneration, or for the synthesis of chemical products or fuels. Some bottlenecks are still present mainly for the gasification of biogenic or fossil origin wastes: irregular feeding in the reactor due to the heterogeneity in form and composition; formation of inorganic gaseous pollutants (HCl, KCl, NaCl, H2S) or organic ones (tars), which are harmful for the process and/or decrease its efficiency, and must be removed before the final application.
The objective of the post-doctoral work will be to test and optimize a pre-treatment step of the resource based on hydrothermal carbonisation (HTC). This transformation is performed at 180-250°C, in a wet and pressurised environment (2-10 MPa). The principal product is a carbonaceous solid residue (hydrochar), that can be valorised by gasification. HTC aims to limit the release of inorganic and organic pollutants in gasification, and to homogenise and improve the physical properties of the resource.
The proposed approach will consist in: experimentations in batch reactors on pre-selected resources and model materials, together with quantification and analyses of products; analysis of results aiming at elucidating the links between the resource and the properties of the hydrochar, as a function of operating conditions; an evaluation of mass and energy balances for the HTC-gasification process.
Design of a control system of a plane based on distributed electric propulsion
The objective of this post doctorate is to design a control system to manage the electrical power on an electric plane proposed by many electrical turbines. The aim of the work is to demonstrate the possibility to increase the propulsion efficiency by using many cooperative electrical turbines placed judiciously on plane compare to a plane having only two or four turbine. Furthermore, one idea is to completely drive the plane by adjusting in real time the power of each electrical turbine taking advantage of their high reactivity compare to classical thermal turbines. The background required for that post doctorate is a good knowledge in control system and power electronic.