Encapsulation of phase change materials with alginate modified by nanostructured sodium carbonate and silicate

The encapsulation of phase change materials (PCMs) as thermal energy storage materials is a big issue. PCM is usually encapsulated to avoid spillage, flammability and its reaction with the surrounding environment to improve its application. In the last decade, various methods have been employed and all kinds of microencapsulated PCM are produced. In this paper, we present a facile route to produce an encapsulated PCM with an organic and inorganic shell. The encapsulated phase change material (PCM) was prepared using a coaxial micro-fluidic system combined with an ionic cross-linking process. The alginate was used as the basic shell and a range of capsules was obtained by modifying the original shell using two inorganic components such as sodium carbonate and sodium silicate. Various samples, each with a different surrounding layer, were prepared by combining alginate calcium (Alg–Ca) as an organic shell with an inorganic component such as alginate calcium carbonate (Alg–CaCO3) and alginate calcium silicate (Alg–CaSiO3). In these experimental works, we have investigated the compatibility and the stability of capsules modified with the inorganic component. The scanning electron microscopy (SEM) technique and optical microscopy were utilized to study the capsule morphology. The chemical composition of the shell was evaluated by Fourier transform infrared spectroscopy (ATR-FTIR), thermogravimetry analysis and SEM coupled with the EDX analysis, and the capsule stability was estimated under an accelerated thermal cycling.     

Mesoscopic approach for steady‐state free convection in a diamond array

The purpose of the present paper is testing an in‐house efficiency algorithm based on lattice Boltzmann method (LBM) and using it to resolve the obtained coupled nondimensional governing equations to analyze two‐dimensional free convection inside a cold outer cavity subjected to a heated cylindrical diamond array. Steady state or oscillatory results are obtained using the Bhatnagar‐Gross‐Krook collision model associated to the thermal LBM. Both the velocity and temperature fields are solved using the D2Q9 models. With different Rayleigh numbers (Ra), the tested free convection can either achieve to steady state or oscillatory. We extended our in house Fortran 90 code using curved boundary conditions and implemented them into a cavity with a diamond array. The numerical simulations were done using distinct Ra (10⁶ and 10 ⁷) and distances between the four neighboring circular cylinders aligned in a diamond array. The effects of several physical parameters, including Ra and position of the hot body array on flow and heat transfer characteristics are investigated. The obtained results are highlighted in the form of streamlines, isotherms, and velocities plots. We show in this paper the stability and the efficiency of the LBM to deal with a complex geometry and its ability to reach suitable convergence criteria for high Ra (10 ⁶ and 10 ⁷). The numerical results indicate that LBM can simulate numerical problems with a high Ra reaching a steady state where we can depict the change of the flow pattern and enhancement of the heat transfer in the presence of heated diamond array.     

Electrochemical degradation of waters containing O-Toluidine on PbO2 and BDD anodes

Electrochemical oxidation of O-Toluidine (OT) was studied by galvanostatic electrolysis using lead dioxide (PbO₂) and boron-doped diamond (BDD) as anodes. The influence of operating parameters, such as current density, initial concentration of OT and temperature was investigated. Measurements of chemical oxygen demand were used to follow the oxidation. The experimental data indicated that on PbO₂ and BDD anodes, OT oxidation takes place by reaction with electrogenerated hydroxyl radicals and is favoured by low current density and high temperature. Furthermore, BDD anodes offer significant advantages over PbO₂ in terms of current efficiency and oxidation rate.     

A new generalised α scale spaces quadrature filters

The α   scale spaces is a recent theory that open new possibilities of phase-based image processing. It is a parameterised class (α∈]0,1])$(\alpha \in ]0,1\left]\right)$ of linear scale space representations, which allows a continuous connection beyond the well-known Gaussian scale space (α=1$\alpha =1$). In this paper, we make use of this unified representation to derive new families of band pass quadrature filters, built from derivatives and difference of the α scale space generating kernels. This construction leads to generalised α kernel filters including the commonly known families derived from the Gaussian and the Poisson kernels. The properties of each family are first studied and then experiments on one- and two-dimensional signals are shown to exemplify how the suggested filters can be used for edge detection. This work is complemented by an experimental evaluation, which demonstrates that the new proposed filters are a good alternative to the commonly used Log-Gabor filter.     

UniformL 1-distance large deviations in nonparametric density estimation

In this paper, we are concerned with uniform large deviations probabilities for theL ₁-error in kernel density estimation. Several results are stated taking into account uniformity over classes of density functions as well as over families of kernels and intervals of smoothing parameters. Some limits are well-identified and are universal in the sense that they do not depend neither on the distribution of the observations nor on the estimation kernel. Our results allow to compare performances of the test based on theL ₁-deviation of the kernel density estimator to that of the Kolmogorov-Smirnov test when testing goodness-of-fit of composite hypotheses.     

Local maximum likelihood segmentation of echocardiographic images with Rayleigh distribution

In order to interpret ultrasound images, it is important to understand their formation and the properties that affect them, especially speckle noise. This image texture, or speckle, is a correlated and multiplicative noise that inherently occurs in all types of coherent imaging systems. Indeed, its statistics depend on the density and on the type of scatterers in the tissues. This paper presents a new method for echocardiographic images segmentation in a variational level set framework. A partial differential equation-based flow is designed locally in order to achieve a maximum likelihood segmentation of the region of interest. A Rayleigh probability distribution is considered to model the local B-mode ultrasound images intensities. In order to confront more the speckle noise and local changes of intensity, the proposed local region term is combined with a local phase-based geodesic active contours term. Comparison results on natural and simulated images show that the proposed model is robust to attenuations and captures well the low-contrast boundaries.     

Feature selection on probabilistic symbolic objects

In data analysis tasks, we are often confronted to very high dimensional data. Based on the purpose of a data analysis study, feature selection will find and select the relevant subset of features from the original features. Many feature selection algorithms have been proposed in classical data analysis, but very few in symbolic data analysis （SDA） which is an extension of the classical data analysis, since it uses rich objects instead to simple matrices. A symbolic object, compared to the data used in classical data analysis can describe not only individuals, but also most of the time a cluster of individuals. In this paper we present an unsupervised feature selection algorithm on probabilistic symbolic objects （PSOs）, with the purpose of discrimination. A PSO is a symbolic object that describes a cluster of individuals by modal variables using relative frequency distribution associated with each value. This paper presents new dissimilarity measures between PSOs, which are used as feature selection criteria, and explains how to reduce the complexity of the algorithm by using the discrimination matrix.     

Parallelised production of fine and calibrated emulsions by coupling flow-focusing technique and partial wetting phenomenon

The capacity of microfluidic technology to fabricate monodisperse emulsion droplets is well established. Parallelisation of droplet production is a prerequisite for using such an approach for making high-quality materials for either fundamental or industrial applications where product quantity matters. Here, we investigate the emulsification efficiency of parallelised drop generators based on a flow-focusing geometry when incorporating the role of partial wetting in order to make emulsion droplets with a diameter below 10 μm. Confinement intrinsically encountered in microsystems intensifies the role played by interfaces between liquids and solids. We thus take advantage of partial wetting to enhance the maximum confinement accessible due to liquid flow focusing. We compare the performances brought by partial wetting to more established routes such as step emulsification. We show that the step configuration and the partial wetting regime are both well suited for being parallelised and thus open the way to the production of fine and calibrated emulsions for further applications. Finally, this new route of emulsification that exploits partial wetting between the fluids and the channel walls opens possibilities to the formation of substantially smaller droplets, as required in many fields of application.