We propose a fundamental study, coupled with the exploration of first applications, of the high frequency properties of heavily boron doped superconducting silicon. This non-equilibrium material, synthesized for the first time in our group, is very stable and is obtained by laser doping. We have previously studied its properties and measured its main parameters in the 3D configuration (~ 100 nm thick). However, superconductivity could also be observed in the 2D limit (thickness <50 nm). The prospects opened by the recent demonstration of all-silicon Josephson junctions and SQUIDs lead us to investigate the RF properties, largely unknown but fundamental for a superconducting quantum electronics of major impact for quantum information. This study is particularly relevant as the feasibility of silicon spin qubits has recently been demonstrated. In this context, the contribution of superconducting silicon resonators will be crucial for a scalable, integrated technology. The RF resonators needed are coplanar waveguides (CPW) and lumped resonators (formed by inductive meanders and interdigitated capacitors), and constitute the core of SUPERR project. We will first study the parameters for the appearance of superconductivity in layers and wires a few nanometers thick in the 2D and 1D limits and characterize their superconducting properties. The amount and not the dopant concentration being the dominant parameter, high concentrations of boron atoms randomly scattered by the laser, are necessary and will induce a disorder in the thin Si:B layers, not necessarily negative according to our preliminary results but inducing a competition between localization (insulator) and Cooper pairs (supra) with a transition that we will try to highlight. We will test the influence of a gate potential on superconducting silicon, boosted by the carrier density 100-1000 times lower than in a metal. Field effect modulation of silicon superconducting properties (DC or RF) could prove to be the key for the design of applications. The study of high-frequency properties of resonators with temperature, doping and layer thickness provides access to the mechanisms of loss and the lifetime of quasiparticles, highlighting possible deviations of the BCS theory when switching from a 3D to 2D regime. In addition, we will probe the evoked gate effects in an attempt to modulate the resonance properties. Finally, we will test the practical possibility to achieve Kinetic Inductance Detectors (KID) for the highly sensitive detection of astronomical photons, promising devices as Si has easily adjustable superconducting Tc and normal state resistance as well as a large kinetic inductance. Thanks to this project, the physics of a disordered covalent superconductor with a low number of carriers will be better understood, simultaneously inducing progress in superconducting silicon applications.

To improve the sustainability of our electricity consumption, efficient thermal management and energy harvesting are becoming critical issues. In this context, semiconductor nanostructures are expected to improve substantially the energy efficiency in electron devices. For instance thermoelectric nanogenerators able to recycle the huge amount of energy wasted by heat engines or electronic circuits are particularly promising. The use of liquid flux energy to supply embedded systems (a kind of electromechanical conversion) should also emerge as a very effective energy conversion mechanism, typically in a biological environment. The optimization of power efficiency in such energy converters based on nanostructures requires a good understanding of electronic and thermal transport at the nanoscale. Unfortunately, the standard macroscopic models, i.e. the Fourier heat diffusion equation and drift diffusion equations, do not provide an accurate response to the thermal problem in nanodevices which are smaller than the charge and thermal carrier mean free path. Including the influence of both out-of-equilibrium and quantum phenomena requires the development of advanced models. To fully achieve the efficiency optimization, all aspects must be considered, from the material issue to the device architecture and its final performance in a realistic environment at the circuit level. The scientific aim of the Noé project is to investigate, at a fundamental level, the physics of coupled electrons and phonons transport in nanostructures, and to propose novel structures providing efficient energy conversion. On the one hand, the thermoelectric performance of Si/SiGe nanowires will be evaluated and design guidelines will be proposed. On the other hand, a more fundamental prospect of energy conversion using graphene nanostructures will be investigated. The thermoelectric conversion and also the more unique electromechanical conversion will be explored. To investigate low power generator using recycled energy, a software chain will be implemented from atoms to circuits. Atomistic semi empirical approach will be used to capture energy dispersions and scattering mechanisms. Two kinds of transport formalisms - Boltzmann and Green - will be used to simulated nanowire and graphene nanostructures, respectively. On the one hand a fully coupled electron-phonon Monte Carlo simulator will be built. On the other hand a device simulator based on atomistic NEGF formalism including relevant scattering mechanism will be developed. Finally, these advanced device simulators self-consistently coupled with Poisson's equation will be used to calibrate semi-analytical circuit models to assess the actual performance of the tested nanostructures. The success of the Noé project, which intends to provide guidelines to nano-energy converter, will open many commercial applications (providing e.g. alternatives to the micro-batteries of embedded systems that work in biological environment) and will contribute to the sustainable use of electrical energy. Moreover, since they are useful for the nanotechnology community, all the codes developed in the project will be diffused under an open source license. Additionally, since this Noé software platform will certainly require a lot of computational resources in its research release, a "light" release will be developed to be used in Master’s level classes and within the "nano-société" program from the LAbex NanoSaclay in order to familiarize a large audience to some nanotechnology issues.

One of the most active recent developments in computer vision has been the analysis of crowded scenes. The interest that this specific field has raised may be explained from two different perspectives. In terms of applicability, continuous surveillance of public and sensitive areas has benefited from the advancements in hardware and infrastructure, and the bottleneck moved towards the processing level, where human supervision is a laborious task which often requires experienced operators. Other circumstances involving the analysis of dense crowds are represented by large scale events (sport events, religious or social gatherings) which are characterized by very high densities (at least locally) and an increased risk of congestions. From a scientific perspective, the detection of pedestrians in different circumstances, and furthermore the interpretation of their actions involve a wide range of branches of computer vision and machine learning. Single camera analysis This represents the typical setup for a broad range of applications related to prevention and detection in public and private environments. Although some camera networks may contain thousands of units, it is quite common to perform processing tasks separately in each view. However, single view analysis is limited by the field of view of individual cameras and furthermore by the spatial layout of the scene; also, frequent occlusions in crowded scenes hamper the performance of standard detection algorithms and complexify tracking. Multiple camera analysis Multiple camera analysis has the potential to overcome problems related to occluded scenes, long trajectory tracking or coverage of wider areas. Among the main scientific challenges, these systems require mapping different views to the same coordinate system; also, solutions for the novel problems they address (detection in dense crowds, object and track association, re-identification etc.) may not be obtained simply by employing and extending previous strategies used in single camera analysis. In our study, we focus on solving the problem of analyzing the dynamics of a high-density crowd. The goal of the present proposal is to tackle the major challenge of detecting and tracking simultaneously as particles thousands of pedestrians forming a high-density crowd, and based on real data observations, to assist in proposing and validating a particle interaction model for crowd flow. Our project is original in its aim of performing particle level analysis, as well as through its emphasis on wide area multiple camera tracking. The strategy we intend to follow is based on a feedback loop involving particle segmentation and tracking, which aims to address the main difficulty of this problem, the uncertainty of data association. The value of such a study rests on the need for better solutions for human urban environments and for transport infrastructures, that not only improve the efficiency of the flows involved, but also do it in such a way as to increase and not diminish the quality of life. Another important prerogative of such research is to prevent fatalities during large scale events and gatherings. Toward the end of the project, we intend to propose a methodology for the analysis of highly-dense crowds which benefits from the recent developments in single camera tracking, and also proposes effective data association solutions among multiple cameras. Secondly, we intend to support the research community by providing a multi-camera dataset which would also allow for a stronger implication of additional fields involved in the general study of crowds, mainly physics, control, simulations and sociology.

This project aims at using magnetic RAM devices in an original probabilistic regime, to demonstrate low-power cognitive-type applications. In recent years, research on using memory nanodevices as “synapses” (the connections in the brain) has largely boomed, with studies both on the device and on the applications sides. This project will join this rich research dynamic, and bring a radically novel point of view that may transform this emerging field. The programming of many nanodevices, and in particular magnetic RAM (MRAM), has an intrinsic random character. Lowenergy programming pulses may program the device, but only with a finite probability. We propose to EXPLOIT this random aspect of short programming pulses to develop new ultra low power computing paradigms. Our research will focus on Spin Torque Transfer MRAMs. In these devices, the stochastic behavior is indeed controllable. Exploiting this behavior is a real reverse of way of thinking. Nondeterministic effects are normally dramatic for circuit applications, here they will allow us to perform learning with algorithms that would be complex to implement in another way. The scheme will be naturally lowpower since it involves short programming pulses. In this project, the term “synapses” is taken in its broadest meaning. We will aim bioinspired applications, where nanodevices are used similarly to biological synapses, and also other learning systems where synapses learn in ways inspired by machine learning. The final goal of this technology is to develop ultralow power embedded systems capable of extreme adaptation thanks to learning, and capable of processing natural data. The project is interdisciplinary in nature and features different kinds of research. On the device side, we will characterize different kinds of magnetic tunnel junctions in regimes that are not typically explored, but are the best for synaptic-type applications. We will model the stochastic behavior and we will program compact (VerilogA-based) models for circuit simulations, and behavioral models for system-level simulations. These models will be made open source. In parallel, we will develop different kinds of learning rules that exploit the stochastic behavior. We will assess them through simulations of systems that use large numbers of nanodevices. For this purpose, a specific simulator will be developed. We will focus on demonstrating complex real life applications (image/video, sound, olfaction and robotics). We will evaluate the robustness of our approach to technology imperfections and unpredictable environments. We will design CMOS circuits to be associated with synaptic MRAMs and validate them by simulation. Finally, we will fabricate a small demonstrator with a small number of packaged MRAMs on printed circuit board that will demonstrate stochastic learning in practice and open the way to the realization of a full-size demonstrator with CMOS/MRAM integration in the future. The project will benefit from an exceptional context. The coordinator has already led a pioneering an extremely successful preliminary study (“PEPS” project funded by CNRS), whose goal was to bring the preliminary results for the submission of the present ANR project. An excellent PhD student has already agreed to join the project. Finally, the project benefits from the exceptional expertise of IEF in nanoelectronics-based design, computer simulation and spintronics devices characterization. The results of this project can have a strong social and economic impact. It is expected that a driver for future electronic devices will be ambient and cognitive intelligent devices that should simplify people’s everyday life, assist elderly and handicapped people, and help medical doctors provide tailored and timely health-care. They will require electronic systems, which can compute efficiently with the real-life data from sensors with minimum power consumption. Our novel computing paradigm can be a key tool to achieve such systems.

For several years, silicon photonics is a very active research field, first to overcome metallic interconnects problem in CMOS microchip, and more and more to reduce component cost in telecommunications. The realization of an “optical link” involves developing basic key components, such as optical laser source, optical modulator or photodetectors, that could be easily integrated over silicon. Numerous solutions were developed (III-V, Germanium, nc-silicon), but their monolithic integration on silicon still presents difficulties, due to different materials used for optical source, modulator and detector. The use of carbon nanotubes could allow monolithic integration of these components. In this context, “Ça (Re-)Lase !” proposal aims at focus on the laser optical source, and to realize an electrically driven silicon integrated carbon nanotube laser source. Carbon nanotube is a pertinent choice for this project. Indeed, carbon nanotubes present, among other originalities, semiconductor or metallic behavior, leading to a great variety of electrical and optical properties depending on carbon nanotubes structure. This behavior generates a great interest in carbon nanotubes for nano-electronics and nano-optoelectronics. At the electronic level, carbon nanotubes based field effect transistors displays promising performances, and their compatibility with microelectronics technology is under study. ITRS, the industrial consortium defining the future of microelectronics, started to be interested in carbon nanotubes for possible use as an ultimate channel in MOSFET transistors and as metallic vias. At the optoelectronic level, carbon nanotube displays strong photo- and electro-luminescence, in the NIR-MIR range (from 1 µm to 5 µm), tunable by choosing a precise carbon nanotube diameter and chirality. The possibility to use electric pumping to generate luminescence is extremely favorable for the developing of nanotube based laser sources. Moreover, a breakthrough was recently performed at IEF by the first observation of optical gain in semiconductor carbon nanotubes, and this is an important first step towards carbon nanotubes based laser sources. Thus, the use of the same carbon nanotubes for both optical and electronic functions, as proposed by “Ça (Re-)Lase !” offers very innovatives perspectives for monolithically integration of electronic and optical function in future microchips. From the context presented above, one could see that carbon nanotubes are a very polyvalent material, displaying at the same time very rich optical and electronic properties. Carbon nanotubes are good candidates for the realization of optical light source. All of this illustrates “Ça (Re-)Lase !” pertinent choice of carbon nanotubes for the realisation of an electrically driven laser integrated on silicon. Outcomes of “Ça (Re-)Lase !” will be broader than the carbon nanotube laser source. The research theme of carbon nanotube photonics is an emerging field, and potentialities of carbon nanotubes for optical modulation, photodetection, bio-photonics or medical or environmental applications are great.