PVDF-based composites containing PZT particles: How processing affects the final properties

Poly(vinylidene fluoride) (PVDF)-based composites containing up to 30 vol % of lead zirconate titanate (PZT) particles were prepared by: (a) different techniques, melt blending and solvent casting; and (b) different molding procedures, a single-step and a two-step hot-pressing method. The obtained samples were characterized in order to study how the processing affects their final properties. Results indicate that the different molding processes have a strong effect on polymorphism and molecular relaxations of PVDF as well as on dielectric response of the composite materials, that results enhanced by the two-step molding. The preparation technique influences the filler dispersion and, consequently, the elastic modulus of the composites, but without remarkably impacting on other properties. This suggests the possibility of preparing performing composites by a solvent-free and easily scalable technique (i.e., melt blending) and obtaining suitable dielectric characteristics, very important for application of such kind of materials, just by tuning the molding conditions. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 137, 48871.     

A Context-Sensitive Technique for Unsupervised Change Detection Based on Hopfield-Type Neural Networks

In this paper, we propose a context-sensitive technique for unsupervised change detection in multitemporal remote sensing images. This technique is based on a modified Hopfield neural network architecture designed to model spatial correlation between neighboring pixels of the difference image produced by comparing images acquired on the same area at different times. Each spatial position in the considered scene is represented by a neuron in the Hopfield network that is connected only to its neighboring units. These connections model the spatial correlation between neighboring pixels and are associated with a context-sensitive energy function that represents the overall status of the network. Change detection maps are obtained by iteratively updating the output status of the neurons until a minimum of the energy function is reached and the network assumes a stable state. A simple heuristic thresholding procedure is presented and adopted for initializing the network. The proposed change detection technique is unsupervised and distribution free. Experimental results carried out on two multispectral and multitemporal remote sensing images confirm the effectiveness of the proposed technique     

Fusion of Hyperspectral and LIDAR Remote Sensing Data for Classification of Complex Forest Areas

In this paper, we propose an analysis on the joint effect of hyperspectral and light detection and ranging (LIDAR) data for the classification of complex forest areas. In greater detail, we present: 1) an advanced system for the joint use of hyperspectral and LIDAR data in complex classification problems; 2) an investigation on the effectiveness of the very promising support vector machines (SVMs) and Gaussian maximum likelihood with leave-one-out-covariance algorithm classifiers for the analysis of complex forest scenarios characterized from a high number of species in a multisource framework; and 3) an analysis on the effectiveness of different LIDAR returns and channels (elevation and intensity) for increasing the classification accuracy obtained with hyperspectral images, particularly in relation to the discrimination of very similar classes. Several experiments carried out on a complex forest area in Italy provide interesting conclusions on the effectiveness and potentialities of the joint use of hyperspectral and LIDAR data and on the accuracy of the different classification techniques analyzed in the proposed system. In particular, the elevation channel of the first LIDAR return was very effective for the separation of species with similar spectral signatures but different mean heights, and the SVM classifier proved to be very robust and accurate in the exploitation of the considered multisource data.     

Fate of Antimony and Arsenic in Contaminated Waters at the Abandoned Su Suergiu Mine (Sardinia,Italy)

Mine Water and the Environment - We investigated the fate of Sb and As downstream of the abandoned Su Suergiu mine (Sardinia, Italy) and surrounding areas. The mined area is a priority in the...     

Electrostatic Control of the Thermoelectric Figure of Merit in Ion-Gated Nanotransistors

Semiconductor nanostructures have raised much hope for the implementation of high-performance thermoelectric generators. Indeed, they are expected to make available reduced thermal conductivity without a heavy trade-off on electrical conductivity, a key requirement to optimize the thermoelectric figure of merit. Here, a novel nanodevice architecture is presented in which ionic liquids are employed as thermally-insulating gate dielectrics. These devices allow the field-effect control of electrical transport in suspended semiconducting nanowires in which thermal conductivity can be simultaneously measured using an all-electrical setup. The resulting experimental data on electrical and thermal transport properties taken on individual nanodevices can be combined to extract ZT, guide device optimization and dynamical tuning of the thermoelectric properties.     

Stray Capacitance in a Plasma Focus Device: Implications on the Current Derivative Calibration and the Effective Discharge Current

The notion that PF discharge circuits should be represented by an equivalent circuit having two loops instead of the traditional single one is presented. This implies that two frequencies must be expected in the currents and voltages in these devices. Also, that the current flowing into the plasma is not the same as the current flowing from the capacitor bank. Finally, the difficulties for calibrating in situ a Rogowski coil are discussed.