Nanocrystalline cellulose reinforced PVDF-HFP membranes for membrane distillation application

Polyvinylidenefluoride-co-hexafluoropropylene (PVDF-HFP) membranes containing different amounts of nanocrystalline cellulose (NCC) were fabricated by electrospining technique for application in membrane distillation (MD). The effect of incorporating NCC on the mechanical strength, morphology, pore size distribution, and liquid entry pressure (water) of the fibrous was investigated. Incorporation of NCC in PVDF-HFP matrix improved the tensile strength and Young's modulus and narrowed down the pore size distribution of the fabricated membranes. Liquid entry pressure, which is an important parameter to ensure high salt rejection of the membranes in MD, was improved from ~ 19 psi to ~ 27 psi with the addition of 2 wt.% NCC. Fabricated membranes were tested in direct contact membrane distillation (DCMD). MD operation data revealed water flux of 10.2–11.5 Lh^− 1 m^− 2 with salt rejection of 99% for these NCC-incorporated membranes.     

Sensitivity analysis of the uncertainties of the mechanical design parameters: Stochastic study performed via a numerical design of experiment

As the GDL (Gas diffusion layer) is the most sensitive component in the fuel cell, any change in its structure causes a change in its porosity, which strongly influences the contact between the components of the fuel cell. Note that the state of contact depends on the applied clamping pressure, the thickness and the porosity of the GDL, and the geometry of the rib (bending radius) of the BPP (Bipolar plates). These components can be subject to variations coming from very high compression, so it is necessary to consider the reliability of their dimension via modeling/simulation by the integration of uncertainties. In this article, we will study the influence on the contact pressure of the uncertainties of the mechanical design parameters. A probabilistic approach (Gauss's law) is applied to evaluate the effect of the mechanical uncertainties parameter on the contact pressure between GDL/MEA and GDL/BPP.     

Cooperative decode-and-forward quadrature spatial modulation over correlated and imperfect η–μ fading channels

Wireless Networks - This paper analyzes the performance of quadrature spatial modulation (QSM) multiple-input multiple-output (MIMO) system in cooperative decode and forward (DF) networks over...     

Influence of filler/matrix interactions on resin/hardener stoichiometry,molecular dynamics,and particle dispersion of silicon nitride/epoxy nanocomposites

The addition of nanofillers can have a significant influence on the resin stoichiometry of thermosetting polymer systems. Based on differential scanning calorimetry (DSC) results, it is estimated that the inclusion of 2 and 5 wt% of silicon nitride nanofiller displaces the resin/hardener stoichiometry of an epoxy/amine network by 6.5 and 18%, respectively. Dielectric spectroscopy results confirm the above findings, in that the spectra of the nanocomposite samples were found to be equivalent to the spectra of unfilled samples when the above stoichiometric effect was taken into account. Therefore, this study provides clear evidence that the presence of a nanofiller can directly and significantly affect the curing process of an epoxy network. Consequently, this should always be considered when introducing nanofillers into thermosetting matrices. These results indicate the presence of covalent bonding between the nanoparticles and the surrounding polymer and, therefore, provide an opportunity to explore the influence of this bonding on the molecular dynamics of the polymer layer around the particles. However, the obtained DSC and dielectric spectroscopy results suggest that, in the system considered here, either the covalent bonding does not have an appreciable influence on the segmental dynamics of the polymer, as revealed by these techniques, or that the thickness of the affected layer is less than 1 nm and therefore too small to be distinguished from experimental uncertainties.     

Assisstive technology application for enhancing social and language skills of young children with autism

In this paper we present an assistive system designed for supporting young children affected by autism in their process of learning pronunciation and meaning of new words. The system is built-up of a mobile application and objects identifiers which in our case were Estimote Beacon sensors. The system requires active participation of a parent who selects words to learn, records pronunciation of object names, selects illustrations, and activates and turns off the application. The entire process is designed to extend parents’ care and to support autistic children with an instant repetition of pronounced object’s names when those items are met during playing or moving around the house. An experimental part of our project consists of a report where we compare collected results of two autistic children using our application installed on a smart watch and on a smart phone. In both reported cases autistic children made a visible progress in speed of learning new words when compared to an equivalent period of time without assistive application support.

     

Enhancement of electrical parameters of PANI—A conducting polymer with low concentration nanofiller for optoelectronic and electrical application

Electrical conductivity is emerging as one of the most essential material's qualities of the 21st century due to the lightning-fast advancements in the electronics sector and the continuously improving electrical goods. As conductive materials are used in the majority of the modern items we use, including power sources, energy generating systems, electrical circuits, sensors, and many others, continuing advancement in this field is very crucial. The novelty of this work lies in the dispersion of ferrite nanoparticles, which was synthesized using egg albumen to enhance the electrical behavior of PANI polymer films. In this research work, a simple casting approach was used to ex situ polymerize aniline to fabricate ultrathin and flexible CuFe₂O₄ distributed PANI films for electrical conductivity applications. The combustion approach was used to produce the copper ferrite nanoparticles, while egg albumen was not only used as the fuel but also it was used a capping agent to control the size of ferrite NPs with a size much lower than that already reported. Studies on the structural, morphological, and electrical properties of pure and various weight percent of (1 , 3 , and 5 wt%) CuFe₂O₄ loaded PANI films were performed. Comparing the different films, the 5 wt% CuFe₂O₄ dispersed PANI films exhibited remarkable and greatly improved permittivity and electrical conductivity with low dielectric loss. This indicates the 5 wt% CuFe₂O₄ dispersed PANI films have the prospective uses in high-tech industries where there is a need for flexible, thin, and lightweight high electrical conducting materials with lesser loss factor.     

Influence of local porosity and local permeability on the performances of a polymer electrolyte membrane fuel cell

In the literature, many models and studies focused on the steady-state aspect of fuel cell systems while their dynamic transient behavior is still a wide area of research. In the present paper, we study the effects of mechanical solicitations on the performance of a proton exchange membrane fuel cell as well as the coupling between the physico-chemical phenomena and the mechanical behavior. We first develop a finite element method to analyze the local porosity distribution and the local permeability distribution inside the gas diffusion layer induced by different pressures applied on deformable graphite or steel bipolar plates. Then, a multi-physical approach is carried out, taking into account the chemical phenomena and the effects of the mechanical compression of the fuel cell, more precisely the deformation of the gas diffusion layer, the changes in the physical properties and the mass transfer in the gas diffusion layer. The effects of this varying porosity and permeability fields on the polarization and on the power density curves are reported, and the local current density is also investigated. Unlike other studies, our model accounts for a porosity field that varies locally in order to correctly simulate the effect of an inhomogeneous compression in the cell.     

Networked cellulose entrapped and reinforced PEO‐based solid polymer electrolyte for moderate temperature applications

A novel solid polymer electrolyte (SPE) composed of poly (ethylene oxide) (PEO) and networked cellulose (NC) is developed for moderate temperature applications typically 50 to 100°C. The SPE thus formed demonstrates enhanced strength; high thermal and appropriate electrochemical stability. NC is a high strength polymeric material with a network structure possessing open spaces in its construction. The NC open spaces shrink on drying. The SPEs are formed by solution casting different amounts of NC in dissolved PEO. NC was formed by the acid hydrolysis and regeneration of microcrystalline cellulose (MCC). SEM, TEM and in‐situ optical images revealed that the dissolved PEO solidified around the suspended NC and the open structure of NC entraps PEO upon drying. NC provides structural and thermal stability to the SPE. With an addition of 15wt% NC in SPE there was about five‐time increase in both tensile as well as storage modulus measured via tensile testing and Dynamic mechanical analysis (DMA) respectively. The enhancement of mechanical strength is explained using the Zener model. Cyclic voltammetry (CV) and linear sweep voltammetry (LSV) studies validated that the electrochemical stability window of PEO+15 wt %NC with salt and that of neat PEO with salt are analogous. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013     

Remote Sensing Image Encryption Using Optimal Key Generation-Based Chaotic Encryption

The Internet of Things (IoT) offers a new era of connectivity, which goes beyond laptops and smart connected devices for connected vehicles, smart homes, smart cities, and connected healthcare. The massive quantity of data gathered from numerous IoT devices poses security and privacy concerns for users. With the increasing use of multimedia in communications, the content security of remote-sensing images attracted much attention in academia and industry. Image encryption is important for securing remote sensing images in the IoT environment. Recently, researchers have introduced plenty of algorithms for encrypting images. This study introduces an Improved Sine Cosine Algorithm with Chaotic Encryption based Remote Sensing Image Encryption (ISCACE-RSI) technique in IoT Environment. The proposed model follows a three-stage process, namely pre-processing, encryption, and optimal key generation. The remote sensing images were preprocessed at the initial stage to enhance the image quality. Next, the ISCACE-RSI technique exploits the double-layer remote sensing image encryption (DLRSIE) algorithm for encrypting the images. The DLRSIE methodology incorporates the design of Chaotic Maps and deoxyribonucleic acid (DNA) Strand Displacement (DNASD) approach. The chaotic map is employed for generating pseudorandom sequences and implementing routine scrambling and diffusion processes on the plaintext images. Then, the study presents three DNASD-related encryption rules based on the variety of DNASD, and those rules are applied for encrypting the images at the DNA sequence level. For an optimal key generation of the DLRSIE technique, the ISCA is applied with an objective function of the maximization of peak signal to noise ratio (PSNR). To examine the performance of the ISCACE-RSI model, a detailed set of simulations were conducted. The comparative study reported the better performance of the ISCACE-RSI model over other existing approaches.