Polymer electrolyte membrane modification in direct ethanol fuel cells: An update

Direct ethanol fuel cells (DEFCs) offer a high degree of design flexibility, ranging from a single cell to a massive multi-cell that can be used in various applications, including portable devices, transportation, and stationary applications. Unfortunately, the most significant barrier to the commercialization of DEFCs is getting low-cost and ethanol permeability, high conductivity performance, and extended durability of polymer electrolyte membranes, as key components that highly influence the overall performance. In this paper, the recent progress in developing the polymer electrolyte membrane for the application of DEFCs has been comprehensively reviewed. Focusing on an updated modification of polymeric materials in the last 5 years, including Nafion-based membrane, polyvinyl alcohol-based membrane, polybenzimidazoles-based membrane, chitosan-based membrane, and sodium alginate-based membrane, as well as factors and challenges that affected the performance of polymer electrolyte membranes have been discussed, including the main characterization, catalyst selection, cell design, and work in membrane and cell performance of DEFCs. All discussion addresses the strategy to improve the performance of polymer electrolyte membranes in DEFCs in order to penetrate the commercialization stages.     

Optimizing natural rubber blends for examination gloves: Vacuum radiation for mechanical strength and solvent barrier

Natural rubber (NR) is emblematic of sustainability compared to synthetic rubber. However, the tradition of adding sulfur as a vulcanization ingredient results in the release of toxic substances and the potential for health issues. In this study, a feasible strategy was proposed to replace sulfur and discover a safe bulk modification process for NR films. The results have shown that the NR particle size was disintegrated to below 10 nm by gamma irradiation. High tension strength up to 24.45 MPa was observed in the vulcanized NR blend film, which could be elongated up to 800% strain after exposure to an optimum dose of 14 kGy. In comparison to commercial NR latex and nitrile gloves, the vulcanized NR/ SIS films exhibited better chemical resistance ability against hexane, methanol, toluene, and acetone, as revealed by the permeation test. The appearance of amorphous regions and highly oriented NR crystallites was observed through transmission electron microscopy. Findings from this study propose the vacuum radiation strategy that can replace conventional vulcanization methods, resulting in NR films with high mechanical and barrier performance. Furthermore, the emission of toxic substances is reduced by this green process, making it practically useful for potential chemical-resistant examination glove applications.     

Analyzing CT images for detecting lung cancer by applying the computational intelligence-based optimization techniques

Lung cancer is the most critical disease because it affects both men and women. Most of the time, lung cancer leads to death due to less health care and medical attention. In addition, lung cancer is difficult to identify in earlier stages due to the low-level symptoms and risk factors. To overcome the complexity, effective techniques must predict lung cancer earlier. To attain the problem statement, an lung cancer identification system is developed with the help of a meta-heuristic algorithm. The CT imageries obtained from the CIA database are analyzed step by step. The gathered image noise is removed by applying the mean filter, and the affected regions are segmented with the help of the Butterfly Optimization Algorithm-based K-Means Clustering (BOAKMC) algorithm. Afterward, various statistical features are derived, and the Supervised Jaya Optimized Rough Set related Feature Selection (SJORSFS) process is used to select the lung features. Finally, the lung cancer is identified using Autoencoder based Recurrent Neural Network (ARNN) classification algorithm, successfully recognizing the lung cancer features. Then the system's efficiency is evaluated using a MATLAB setup; here, 3000 are treated as training images and 2043 for testing images. The effective training enhances overall lung cancer prediction accuracy by up to 99.15%.     

Changes in selected quality characteristics of minimally processed carambola (Averrhoa carambola L.) when treated with ascorbic acid

‘B 10’ carambola of ripening stage (RS) 3 and 4 were minimally processed (MP) and then dipped in 0, 15 and 30 mg L^?1 ascorbic acid (AA). The 1‐cm‐thick slices were then dried, packed into cling‐wrapped‐foam tray and stored at 7 °C for 0, 3 and 5 days. Skin colour (L*, C* and h°), flesh firmness, soluble solids concentration, vitamin C content, titratable acidity, pH, degree of browning, polyphenoloxidase (PPO) activity and sensory attributes of MP carambola treated with AA were determined. AA treatment had significant effect in decreasing cut surface browning degree but no significant effect on all the selected quality characteristics of the MP carambola. In the sensory evaluation, flesh colour, sweetness, flavour and overall taste were significantly affected by AA treatment especially at 15 mg L^?1. The RS of fruit significantly affected skin colour (C* and h°), pH and sensory attributes of colour and flavour of the MP carambola. As storage day (SD) progressed, skin colour (C* and h°), flesh firmness and vitamin C content, cut surface browning, PPO activity and all the sensory attributes of MP carambola decreased significantly. Flesh firmness of the MP carambola was affected by the interaction between AA × SD. Sensory attributes of MP carambola were affected significantly by AA × RS. All the sensory attributes of MP carambola positively correlated to each other but negatively correlated with browning degree. PPO activity positively correlated with browning degree. Copyright © 2007 Society of Chemical Industry     

Monte Carlo simulation of diffusive-to-ballistic transition in phonon transport

Heat conduction properties in Si nanostructures are analyzed using a Monte Carlo method developed for solving the phonon Boltzmann transport equation. The thermal resistances are evaluated for the systems with various sizes, and the transition from the diffusive to the ballistic heat conduction are investigated. We compare the two different phonon dispersion models (the realistic dispersion relation based on the adiabatic bond charge model and the analytically approximated model), and it is shown that the correct implementation of the phonon dispersion relation is essential to accurately simulate the quasi-ballistic heat conduction properties, which becomes obvious in the structures smaller than the phonon mean free path.     

Synthesis and Characterization of Silver Nanoparticles and Silver Inks: Review on the Past and Recent Technology Roadmaps

The synthesis of silver nanoparticles for silver ink formation has attracted broad interest in the electronic part printing and semiconductor chip industry due to the extraordinary electrical and mechanical properties of these materials. The preparation of silver nanoparticles through a physical or chemical reduction process is the most common methodology applied to obtain nanoparticles with the required size, shape and surface morphology. The chemical solution or solvent carrier applied for silver ink formulation must be applied simultaneously with the direct writing technique to produce the desired adherence, viscosity, and reliable performance. This review paper discusses the details concerning the past and recent advancement of the synthesis and characterization of silver nanoparticles and silver ink formation. A review on the advantages of various sintering techniques, which aim to achieve the electrical and mechanical properties of the required printed structure, is also included. A brief summary concerning the recent challenges and improvement approaches is presented at the end of this review.     

Formulation Optimization of a Palm-Based Nanoemulsion System Containing Levodopa

Response surface methodology (RSM) was utilized to investigate the influence of the main emulsion composition; mixture of palm and medium-chain triglyceride (MCT) oil (6%–12% w/w), lecithin (1%–3% w/w), and Cremophor EL (0.5%–1.5% w/w) as well as the preparation method; addition rate (2–20 mL/min), on the physicochemical properties of palm-based nanoemulsions. The response variables were the three main emulsion properties; particle size, zeta potential and polydispersity index. Optimization of the four independent variables was carried out to obtain an optimum level palm-based nanoemulsion with desirable characteristics. The response surface analysis showed that the variation in the three responses could be depicted as a quadratic function of the main composition of the emulsion and the preparation method. The experimental data could be fitted sufficiently well into a second-order polynomial model. The optimized formulation was stable for six months at 4 °C.     

Using tchebichef moment for fast and efficient image compression

Orthogonal moment is known as better moment functions compared to the non-orthogonal moment. Among all the orthogonal moments, Tchebichef Moment appear to be the most recent moment functions that still attract the interest among the computer vision researchers. This paper proposes a novel approach based on discrete orthogonal Tchebichef Moment for an efficient image compression. The image compression is useful in many applications especially related to images that are needed to be seen in small devices such as in mobile phone. Meanwhile, the method incorporates simplified mathematical framework techniques using matrices, as well as a block-wise reconstruction technique to eliminate possible occurrences of numerical instabilities at higher moment orders. In addition, a comparison between Tchebichef Moment compression and JPEG compression is conducted. The result shows significant advantages for Tchebichef Moment in terms of its image quality and compression rate. Tchebichef moment provides a more compact support to the image via sub-block reconstruction for compression. Tchebichef Moment Compression is able to perform potentially better for a broader domain on real digital images and graphically generated images.