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Role of particle aggregation on the structure of dried colloidal silica layers
No full textInternational audienceThe process of colloidal drying gives way to particle self-assembly in numerous elds including photonics or biotechnology. Yet, the mechanisms and conditions driving the nal particle arrangement in dry colloidal layers remain elusive. Here, we examine how the drying rate selects the nanostructure of thick dried layers in four dierent suspensions of silica nanospheres. Depending on particle size and dispersity, either an amorphous arrangement, a crystalline arrangement, or a rate-dependent amorphous-to-crystalline transition occurs at the drying surface. Amorphous arrangements are observed in the two most polydisperse suspensions while crystallinity occurs when dispersity is lower. Counter-intuitively in the latter case, a higher drying rate favors ordering of the particles. To complement these measurements and to take stock of the bulk properties of the layer, tests on the layer porosity were undertaken. For all suspensions studied herein, faster drying yields denser dry layers. Crystalline surface arrangement implies large bulk volume fraction (∼ 0.65) whereas amorphous arrangements can be observed in layers with either low (down to ∼ 0.53) or high (∼ 0.65) volume fraction. Lastly, we demonstrate via targeted additional experiments and SAXS measurements, that the packing structure of the layers is mainly driven by the formation of aggregates and their subsequent packing, and not by the competition between Brownian diusion and convection. This highlights that a second dimensionless ratio in addition to the Peclet number should be taken into account, namely the aggregation over evaporation timescale
Solving unconstrained 0-1 polynomial programs through quadratic convex reformulation
No full textInternational audienceWe propose a solution approach for the problem (P) of minimizing an unconstrained binary polynomial optimization problem. We call this method PQCR (Polynomial Quadratic Convex Reformulation). The resolution is based on a 3-phase method. The first phase consists in reformulating (P) into a quadratic program (QP). For this, we recursively reduce the degree of (P) to two, by use of the standard substitution of the product of two variables by a new one. We then obtain a linearly constrained binary program. In the second phase, we rewrite the quadratic objective function into an equivalent and parametrized quadratic function using the equality x 2 i = x i and new valid quadratic equalities. Then, we focus on finding the best parameters to get a quadratic convex program which continuous relaxation's optimal value is maximized. For this, we build a semidefinite relaxation (SDP) of (QP). Then, we prove that the standard linearization inequalities, used for the quadratization step, are redundant in (SDP) in presence of the new quadratic equalities. Next, we deduce our optimal parameters from the dual optimal solution of (SDP). The third phase consists in solving (QP *), the optimal reformulated problem, with a standard solver. In particular, at each node of the branch-and-bound, the solver computes the optimal value of a continuous quadratic convex program. We present computational results on instances of the image restoration problem and of the low autocorrelation binary sequence problem. We compare PQCR with other convexification methods, and with the general solver Baron 17.4.1 [39]. We observe that most of the considered instances can be solved with our approach combined with the use of Cplex [24]
Generation of terawatt, attosecond pulses from relativistic transition radiation
No full textInternational audienceWhen a femtosecond duration and hundreds of kiloampere peak current electron beam traverses the vacuum and high-density plasma interface, a new process, that we call relativistic transition radiation (RTR), generates an intense ∼100 as pulse containing ∼1 terawatt power of coherent vacuum ultraviolet (VUV) radiation accompanied by several smaller femtosecond duration satellite pulses. This pulse inherits the radial polarization of the incident beam field and has a ring intensity distribution. This RTR is emitted when the beam density is comparable to the plasma density and the spot size much larger than the plasma skin depth. Physically, it arises from the return current or backward relativistic motion of electrons starting just inside the plasma that Doppler up shifts the emitted photons. The number of RTR pulses is determined by the number of groups of plasma electrons that originate at different depths within the first plasma wake period and emit coherently before phase mixing
The Laser Lightning Rod project
No full textInternational audienceLightning is highly destructive due to its high power density and unpredictable character. Directing lightning away would allow to protect sensitive sites from its direct and indirect impacts (electromagnetic perturbations). Up to now, lasers have been unable to guide lightning efficiently since they were not offering simultaneously terawatt peak powers and kHz repetition rates. In the framework of the Laser Lightning Rod project, we develop a laser system for lightning control, with J-range pulses of 1ps duration at 1kHz. The project aims at investigating its propagation in the multiple filamentation regime and its ability to control high-voltage discharges. In particular, a field campaign at the S ̈antis mountain will assess the laser ability to trigger upward lightning
One-Class based learning for Hybrid Spectrum Sensing in Cognitive Radio
No full textInternational audienceThe main aim of the Spectrum Sensing (SS) in a Cognitive Radio system is to distinguish between the binary hypotheses H0: Primary User (PU) is absent and H1: PU is active. In this paper, Machine Learning (ML)-based hybrid Spectrum Sensing (SS) scheme is proposed. The scattering of the Test Statistics (TSs) of two detectors is used in the learning and prediction phases. As the SS decision is binary, the proposed scheme requires the learning of only the boundaries of H0-class in order to make a decision on the PU status: active or idle. Thus, a set of data generated under H0 hypothesis is used to train the detection system. Accordingly, unlike the existing ML-based schemes of the literature, no PU statistical parameters are required. In order to discriminate between H0-class and elsewhere, we used a one-class classification approach that is inspired by the Isolation Forest algorithm. Extensive simulations are done in order to investigate the efficiency of such hybrid SS and the impact of the novelty detection model parameters on the detection performance. Indeed, these simulations corroborate the efficiency of the proposed one-class learning of the hybrid SS system
ESco: Eligibility Score-based Strategy for Sensors Selection in CR-IoT: Application to LoRaWAN
No full textInternational audienceIn this paper, a battery-powered Internet of Things assisting Cognitive Radio (CR-IoT) network is considered. In CR-IoT network, a set of IoT End Nodes (ENs) are assumed to cooperatively sense the channel. Each EN performs a Spectrum Sensing (SS) and reports its decision to a Fusion Center in order to reach the decision on the PU status. Such monitoring of PU comes at the cost of additional energy resources consumed by the EN to perform SS and reporting, and raises the need to set a suitable protocol to manage the data exchange. The extra operations may exhaust the energy of the EN battery, especially when Low Power Wide Area Networks (LPWAN) technology is used. In this paper, an Eligibility Score-based (ESco) Strategy is defined to reflect the eligibility of an EN to make a reliable SS taking into consideration its battery level. Our strategy is adapted to LoRaWAN Class-B protocol in order to handle real world scenarios. Necessary modifications are introduced to the existing protocol protocol in order to support the synchronization between the ENs and the Application Server, (which the SS need is identified), and the on-demand nature of the SS requests. To evaluate our strategy, LoRa sensors' parameters are considered in our simulations. The numerical results highlight the efficiency of the proposed strategy by showing the extension of the ENs' lifetime compared to classical strategies
Measurements and Modeling of High-Pressure O 2 and CO 2 Solubility in Brine (H 2 O + NaCl) between 303 and 373 K and Pressures up to 36 MPa
No full textInternational audienceKnowledge of the solubility of oxygen in natural water, which is generally saline, is important for several scientific and engineering fields. Applications such as geological storage of gas (containing O2, e.g., flue gas) or energy (compressed air energy storage) operate at high pressure. However, to date, there is no high-pressure O2 solubility data in brine, which has led researchers to develop models to predict this important property. To overcome the lack of data, solubility of O2 in brine has been measured using two different techniques, at molalities between 0.5 and 4 mol/kgw (NaCl), temperatures between 303 and 373 K, and pressures up to 36 MPa. In order to validate the experimental methods, measurements of the solubility of CO2 in a highly concentrated brine (6 mol/kgw of NaCl) at temperatures between 303 and 373 K and pressures up to 39.5 MPa were performed also in this work. These measurements allowed the evaluation of existing models such as the well-known Geng and Duan model and the model recently developed by Zheng and Mao (ZM). The e-PR-CPA, Søreide–Whitson, and geochemical models used in our previous work were also used to process the new data. These last three models have been parameterized on measured and reported literature O2 solubility data, and new optimized parameters of the ZM model have been proposed. These models reproduce the effect of temperature, pressure, and NaCl concentration on solubility with an average absolute deviation less than 5% from the measured data
Comparison of methods employed to extract information contained in seafloor backscatter
No full textInternational audienceSeabed maps are based on quantities extracted from measurements of the seafloor‘s acoustic response by sonar systems such as single-beam echo-sounders (SBES), multibeam echo-sounders (MBES) or sidescan sonars (SSS). In this paper, a comparison of various strategies to estimate the backscattering strength (BS) from recorded time-series, i.e. seabed echoes extracted from pings, is presented. The work hypotheses are based on processed data from a SBES designed to be tilted mechanically. Ideal survey conditions are taken into account and the seafloor is supposed to be rough so that BS is assumed to be equivalent to the Rayleigh probability density function parameter. Classical methods such as averaging corrected (sonar equation) backscattered single values over a set of pings to estimate BS are compared to other methods exploiting several time-samples being part of pings. Simulated data is considered to estimate BS in different situations (several estimators, natural/squared values, number of samples and pings). The best estimator to reach a 0.1dB uncertainty is proposed, and a formula governing the number of time-samples and pings needed to reach an accurate BS estimation according to the measurement conditions is derived
Distinguishing Self, Other, and Autonomy From Visual Feedback: A Combined Correlation and Acceleration Transfer Analysis
No full textInternational audienceIn cognitive science, Theory of Mind (ToM) is the mental faculty of assessing intentions and beliefs of others and requires, in part, to distinguish incoming sensorimotor (SM) signals and, accordingly, attribute these to either the self-model, the model of the other, or one pertaining to the external world, including inanimate objects. To gain an understanding of this mechanism, we perform a computational analysis of SM interactions in a dual-arm robotic setup. Our main contribution is that, under the common fate principle, a correlation analysis of the velocities of visual pivots is shown to be sufficient to characterize "the self" (including proximo-distal arm-joint dependencies) and to assess motor to sensory influences, and "the other" by computing clusters in the correlation dependency graph. A correlational analysis, however, is not sufficient to assess the non-symmetric/directed dependencies required to infer autonomy, the ability of entities to move by themselves. We subsequently validate 3 measures that can potentially quantify a metric for autonomy: Granger causality (GC), transfer entropy (TE), as well as a novel “Acceleration Transfer” (AT) measure, which is an instantaneous measure that computes the estimated instantaneous transfer of acceleration between visual features, from which one can compute a directed SM graph. Subsequently, autonomy is characterized by the sink nodes in this directed graph. This study results show that although TE can capture the directional dependencies, a rectified subtraction operation denoted, in this study, as AT is both sufficient and computationally cheaper
Scattering of acoustic waves by a nonlinear resonant bubbly screen
No full textInternational audienceAbstrac