An investigation over the effect of the reducing agent on the properties of the ZnO-reinforced Ni–P coatings

Journal of Materials Science: Materials in Electronics - Electroless ZnO-reinforced Ni–P coatings are developed on mild steel substrates in the Electroless bath, which contains an optimum...     

A Review of Transmission Rate over Wireless Fading Channels: Classifications,Applications, and Challenges

To address the explosive traffic demands, the capacity of the fading channel is increasingly becoming a prime concern in the designing of the wireless communication system. The channel capacity is an extremely important quantity, since it allows the transmission of the data through the channel with an arbitrarily small probability of error. In other words, capacity dictates the maximum rate of information transmission, called as ‘capacity’ of channel, determined by the intrinsic properties of the channel and is independent of the content of the transmitted information. In this paper, we present a comprehensive survey of the existing work related to the channel capacity model over various fading channels. With an elaborated explanation of the theory of channel capacity, definitions of channel capacity based on the channel state information are reviewed. To compliment this, review of the technique to enhance the channel capacity is discussed and reviewed. An effective capacity model to overcome the channel capacity limitation is also explained. Furthermore, as the secure transmission of data is of utmost importance, to address this physical layer security model is also reviewed. We also summarize the work related to channel capacity in various types of wireless networks. We finally cover the future research directions, including less explored aspects of the channel capacity that can be studied to design efficient communication systems.

     

Adaptive Group Teaching Based Clustering and Data Aggregation with Routing in Wireless Sensor Network

Wireless Personal Communications - Nowadays, Wireless Sensor Networks (WSNs) is enhancing for different applications. Simultaneously, energy consumption for processing the tasks in most of the...     

Extrinsic parameter's adjustment and potential implications in Plasmodium falciparum malaria diagnosis

Malaria is a major public health concern, affecting over 3.2 billion people in 91 countries. The advent of digital microscopy and Machine learning with the aim of automating Plasmodium falciparum diagnosis extensively depends on the extracted image features. The color of the cells, plasma, and stained artifacts influence the topological, geometrical, and statistical parameters being used to extract image features. During microscopic image acquisition, custom adjustments to the condenser and color temperature controls often have an influence on the extracted statistical features. But, our human visual system sub-consciously adjusts the color and retains the originality in a different lighting environment. Despite the use of appropriate image preprocessing, findings from the literature indicate that statistical feature variations exist, allowing the risk of P. falciparum misinterpretation. In order to eliminate this pervasive variation, the current work focuses on preprocessing the extracted statistical features rather than the prepossessing of the source image. It begins with the augmentation of series images for a microscopic field by inducing illumination variations during the microscopic image acquisition stage. A set of such image series is analyzed using a Nonlinear Regression Model to generalize the relationship between microscopic images acquired with variable ambient brightness and a specific feature. The projection point of the centroid feature onto the brightness parameter is identified in the model and it is denoted as the optimum brightness factor (OBF). Using the model, the feature correction factor (CF) is calculated from the rate of change of feature values over the interval OBF, and the brightness of the test image is processed. The present work has investigated OBF for selected image textural features, namely Contrast, Homogeneity, Entropy, Energy, and Correlation individually from its co-occurrence matrices. For performance analysis, the best state-of-the-art method uses selected texture as a subset feature to evaluate the effectiveness of P. falciparum malaria classification. Then, the impact of proposed feature processing is evaluated on 274 blood smear images with and without Feature Correction (FC). As a result, the “p” value is less than .05, which leads to the result that it is highly significant and the classification accuracy and F-score of P. falciparum malaria are increased.     

Facile Synthesis of Fluorine Doped Rutile TiO2 Nanorod Arrays for Photocatalytic Removal of Formaldehyde

Catalysis Letters - It is crucial to explore a facile synthesis of rutile TiO2 nanorods anchored at carbon cloth at low temperature for applicable air purifier. Herein, antler-like TiO2 rectangular...     

ZnO–SnO2 nanocubes for fluorescence sensing and dye degradation applications

ZnO–SnO₂ nanocubes were used as promising material for efficient sensing of p-nitrophenol and faster photocatalytic degradations of dyes like methyl orange (MO), methylene Blue (MB) and acid orange 74 (AO74). ZnO–SnO₂ nanocubes were prepared by the facile solution process at 50 °C using Zn(NO₃)₂·6H₂O and SnCl₂·2H₂O as a precursor in the presence of ethylenediammine. The synthesized material was examined for its morphological, structural, crystalline, optical, vibrational, and compositional studies by using field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), Fourier Transform Infrared (FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS) and photoluminescence spectroscopy. FESEM studies revealed the formation of well-defined ZnO–SnO₂ nanocubes where the structural examinations revealed the formation of a crystalline tetragonal rutile phase for SnO₂ with some crystal sites doped with Zn. The as-synthesized nanocubes were explored for their photocatalytic activities towards three different dye viz. MO, MB, and AO74. Practically, complete degradation of AO74 was seen within 4 minutes of photo-irradiation in the presence of 0.05 g ZnO–SnO₂ nanocubes. However, 97.17% and 41.63% degradations were observed for MB and MO within 15 and 60 minutes, respectively. All the dye degradation processes followed the pseudo-first-order kinetic model. Moreover, the as-synthesized nanocubes were utilized to fabricate highly sensitive and selective fluorescent chemical sensor for the detection of p-nitrophenol (PNP). ZnO–SnO₂ nanocubes showed a very low detection limit of 4.09 μM for the detection of PNP as calculated according to the 3σ IUPAC criteria. Further, the as-synthesized ZnO–SnO₂ nanotubes were found to be highly selective for p-nitrophenol as compared to the other two isomers.     

Solar hydrogen generation from organic substance using earth abundant CuS–NiO heterojunction semiconductor photocatalyst

This work explores the critical role of NiO co-catalyst assembled on the surface of a CuS primary photocatalyst which effectively improves interface properties and enhances solar-to-hydrogen production by prolonging lifetime of photo-excitons generated at the CuS surface. The nanoscale CuS/NiO heterojunction is formulated using hydrothermal and wet impregnation methods. The resultant CuS/NiO composite shows optical absorbance between 380 and 780 nm region. The type-II energetic structure formed at CuS/NiO heterojunction facilitates rapid charge separation and as a result, the CuS/NiO composite exhibits 13 folds higher photocatalytic water splitting performance than CuO and NiO. The champion CuO/NiO photocatalyst is first identified by screening the catalysts using a preliminary water splitting test reaction under natural Sunlight irradiation. After the optimization of the catalyst, it was further explored for enhanced photocatalytic hydrogen production using different organic substances dispersed in water (alcohols, amine and organic acids). The champion CuS/NiO catalyst (CPN-2) exhibited the photocatalytic hydrogen production rate of 52.3 mmol h^?1.g^?1_cat in the presence of lactic acid-based aqueous electrolyte and, it is superior than hydrogen production rate obtained in the presence of other organic substances (triethanolamine, glycerol, ethylene glycol, methanol) tested under identical experimental conditions. These results indicate that the energetic structure of CuS/NiO photocatalyst is favorable for photocatalytic oxidation or reforming of lactic acid. The oxidation of lactic acid contributes both protons and electrons for enhanced hydrogen generation as well as protects CuS from photocorrosion. The modification of surface property and energetic structure of CuS photocatalyst by the NiO co-catalyst improves photogenerated charge carrier separation and in turn enhances the solar-to-hydrogen generation efficiency. The recyclability tests showed the potential of CPN-2 photocatalyst for prolonged photocatalytic hydrogen production while continuous supply of lactic acid feedstock is available.     

Synthesis and slurry spray coating of barium strontium alumino silicate on SiC substrate

Barium strontium alumino silicate (BSAS); (Ba_0.6Sr_0.4Al₂Si₂O₈) was synthesized through solid state reaction between BaCO₃, SrCO₃, Al₂O₃ and SiO₂ subjected to wet milling in isopropanol for about 24 h. The sequence of the solid state reaction was studied by subjecting to DG/DTG from room temperature to 1550 °C. The crystallographic phase evolution was confirmed by X-ray diffraction of the powders calcined in the range 1000 to 1300 °C for 2 h. The monoclinic celsian phase obtained at 1300 °C, pelletized through uniaxial pressing was sinterable to 67 to 78% density in the temperature range of 1300 to 1500 °C. The density improved to 75 to 94% after ball milling for 76 h, while ZrO₂ addition further improved the density by 2%. The celcian phase of BSAS was dispersed in isopropyl alcohol, milled for about 24 h and spray coated on to plain SiC and mullite precoated SiC substrates. Sintering of coated samples and characterization for weight gain/loss, microstructure, scratch test prove that mullite + BSAS coating is more effective than single layer coating of BSAS on SiC substrates.