Morphological properties of Ag₂SeTe nano thin films prepared by thermal evaporation

Semiconducting silver selenide telluride (Ag₂SeTe) thin films were prepared with different thicknesses onto glass substrates at room temperature using thermal evaporation technique. The structural properties were determined as a function of thickness by X‐ray diffraction exhibiting no preferential orientation along any plane; however, the films are found to have peaks corresponding to mixed phase. The morphology of these films was studied using scanning electron microscope and atomic force microscopy respectively, and is reported. The morphological properties are found to be very sensitive to the thin film thickness. The composition of the films is also estimated using energy dispersive analysis using X‐rays and are also reported.     

Power quality analysis using Discrete Orthogonal S-transform (DOST)

Power quality is one of the major issues in the modern electrical power world. The widespread usage of power electronic devices and non-linear loads make the power system more vulnerable to the power quality disturbances. As the power grids are expanding more and more because of the renewable sources, it necessitates responsive detection and accurate classification of power quality disturbances for corrective measures. This paper presents a new approach for power quality analysis using an orthogonal time–frequency representation of S-transform called Discrete Orthogonal S-transform (DOST). These power quality disturbances are generated on EHV transmission line under different fault and load condition. Different power quality disturbances have been analyzed using the short time Fourier transform (STFT), discrete wavelet transform (DWT), S-transform (ST) and DOST. Different case studies validate the superiority of DOST over other transforms in a more efficient way to monitor the power quality disturbances.     

A 2-D microcantilever array for multiplexed biomolecular analysis

An accurate, rapid, and quantitative method for analyzing variety of biomolecules, such as DNA and proteins, is necessary in many biomedical applications and could help address several scientific issues in molecular biology. Recent experiments have shown that when specific biological reactions occur on one surface of a microcantilever beam, the resulting changes in surface stress deflect the cantilever beam. To exploit this phenomenon for high-throughput label-free biomolecular analysis, we have developed a chip containing a two-dimensional (2-D) array of silicon nitride cantilevers with a thin gold coating on one surface. Integration of microfluid cells on the chip allows for individual functionalization of each cantilever of the array, which is designed to respond specifically to a target analyte. An optical system to readout deflections of multiple cantilevers was also developed. The cantilevers exhibited thermomechanical sensitivity with a standard deviation of seven percent, and were found to fall into two categories-those whose deflections tracked each other in response to external stimuli, and those whose did not due to drift. The best performance of two "tracking" cantilevers showed a maximum difference of 4 nm in their deflections. Although "nontracking" cantilevers exhibited large differences in their drift behavior, an upper bound of their time-dependent drift was determined, which could allow for rapid bioassays. Using the differential deflection signal between tracking cantilevers, immobilization of 25mer thiolated single-stranded DNA (ssDNA) on gold surfaces produced repeatable deflections of 80 nm or so on 0.5-/spl mu/m-thick and 200-/spl mu/m-long cantilevers.     

A Coating‐Free Nonfouling Polymeric Elastomer

Medical devices face nonspecific biofouling from proteins, cells, and microorganisms, which significantly contributes to complications and device failure. Imparting these devices with nonfouling capabilities remains a major challenge, particularly for those made from elastomeric polymers. Current strategies, including surface coating and copolymerization/physical blending, necessitate compromise among nonfouling properties, durability, and mechanical strength. Here, a new strategy is reported to achieve both high bulk mechanical strength and excellent surface nonfouling properties, which are typically contradictory, in one material. This is realized through a nonfouling polymeric elastomer based on zwitterionic polycarboxybetaine derivatives. By hiding both charged moieties of the zwitterionic compounds with hydrocarbon ester and tertiary amine groups, the bulk polymer itself is elastomeric and hydrophobic while its superhydrophilic surface properties are restored upon hydrolysis. This coating‐free nonfouling elastomer is a highly promising biomaterial for biomedical and engineering applications.     

Optimised microwave-assisted biosynthesis of silver nanoparticles from Nothapodytes foetida leaf extracts and its anti-microbial activities

The present investigation reports the biogenesis of silver nanoparticles (Ag NPs) using extracts of a medicinal plant Nothapodytes foetida. Total phenolic content (TPC) and ferric reducing antioxidant power (FRAP) assay were carried out for the microwave-assisted extract (MAE) of N. foetida using methanol as solvent and the conditions for extraction were optimised by response surface methodology (RSM). The effects of operating variables such as extraction time, temperature and ratio of sample to solvent were studied using central composite design (CCD). A mathematical model with a high determination coefficient (R²) for TPC (0.991) and FRAP (0.995) was obtained. The optimal conditions of extraction for TPC were 48.6 ºC, 23.15 min and 2.04:30 (g/mL) and for FRAP 52.31ºC, 12.32 min and 1.67: 30 (g/mL). Under these conditions, the experimental yields of TPC and FRAP were 2.426 mg gallic acid equivalents (GAE)/g dry powder and 14.985mg of FeSO₄·7H₂O/g of dry powder, respectively. Ag NPs were characterised using UV–Vis spectroscopy, transmission electron microscopy (TEM), X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy. The synthesised Ag NPs have also shown potent activity against the human pathogenic Staphylococcus aureus.     

Biogenic synthesis of silver nanoparticles from Cassia fistula (Linn.): In vitro assessment of their antioxidant,antimicrobial and cytotoxic activities

The present study reports on biogenic‐synthesised silver nanoparticles (AgNPs) derived by treating Ag ions with an extract of Cassia fistula leaf, a popular Indian medicinal plant found in natural habitation. The progress of biogenic synthesis was monitored time to time using a ultraviolet–visible spectroscopy. The effect of phytochemicals present in C. fistula including flavonoids, tannins, phenolic compounds and alkaloids on the homogeneous growth of AgNPs was investigated by Fourier‐transform infrared spectroscopy. The dynamic light scattering studies have revealed an average size and surface Zeta potential of the NPs as, −39.5 nm and −21.6 mV, respectively. The potential antibacterial and antifungal activities of the AgNPs were evaluated against Bacillus subtilis, Staphylococcus aureus, Candida kruseii and Trichophyton mentagrophytes. Moreover, their strong antioxidant capability was determined by radical scavenging methods (1,1‐diphenyl‐2‐picryl‐hydrazil assay). Furthermore, the AgNPs displayed an effective cytotoxicity against A‐431 skin cancer cell line by 3‐(4, 5‐dimethylthiazol‐2‐yl)‐2, 5‐diphenyltetrazolium bromide (MTT) assay, with the inhibitory concentration (IC₅₀) predicted as, 92.2 ± 1.2 μg/ml. The biogenically derived AgNPs could find immense scope as antimicrobial, antioxidant and anticancer agents apart from their potential use in chemical sensors and translational medicine.Inspec keywords: antibacterial activity, biomedical materials, cancer, cellular biophysics, electrokinetic effects, Fourier transform infrared spectra, light scattering, microorganisms, nanomedicine, nanoparticles, silver, skin, spectrochemical analysis, toxicology, ultraviolet spectra, visible spectraOther keywords: Ag, voltage ‐21.6 mV, size ‐39.5 nm, A‐431 skin cancer cell line, cytotoxicity, 1,1‐diphenyl‐2‐picryl‐hydrazil assay, radical scavenging methods, Trichophyton mentagrophytes, Candida kruseii, Staphylococcus aureus, Bacillus subtilis, surface zeta potential, dynamic light scattering studies, Fourier‐transform infrared spectroscopy, alkaloids, phenolic compounds, tannins, flavonoids, phytochemical effect, ultraviolet‐visible spectroscopy, Cassia fistula leaf extract, biogenic‐synthesised silver nanoparticles, cytotoxic activities, antimicrobial activities, antioxidant activities     

An improved fault detection crow search algorithm for wireless sensor network

In wireless sensor networks (WSNs), the collected data during monitoring environment can have some faulty data, and these faults can lead to the failure of a system. These faults may occur due to many factors such as environmental interference, low battery, and sensors aging etc. We need an efficient fault detection technique for preventing the failures of a WSN or an IoT system. To address this major issue, we have proposed a new nature-inspired approach for fault detection for WSNs called improved fault detection crow search algorithm (IFDCSA). IFDCSA is an improved version of the original crow search algorithm (CSA). The proposed algorithm first injects the faults into the datasets, and then the faults are classified using improved CSA and machine learning classifiers. The proposed work has been evaluated on the three real-world datasets, ie, Intel lab data, multihop labeled data, and SensorScope data, and predicts the faults with an average accuracy of 99.94%. The results of the proposed algorithm have been compared with the three different machine learning classifiers (random forest, k-nearest neighbors, and decision trees) and Zidi model. The proposed algorithm outperforms the other classifiers/models, thus generating higher accuracy and lower features without degrading the performance of the system. Index Terms—big data, crow search algorithm, IoT, machine learning, nature-inspired algorithm, wireless sensor network.     

Dynamics of controlled release of potassium nitrate from a highly swelling binary polymeric blend of alginate and carboxymethyl cellulose

Highly water absorbing and homogeneous binary biopolymeric blends in bead form were prepared of calcium alginate and carboxymethyl cellulose by solution cast method. The prepared blends were evaluated for controlled delivery of KNO₃ taking it as a model agrochemical. The beads characterized by Fourier transform infrared spectroscopy (FTIR) and Scanning electron microscopy (SEM) were used to investigate the molecular structure and morphology of beads. The swelling experiments were performed for different compositions of beads and at varying pH and temperature of the aqueous media. The release experiments were performed under static and varying experimental conditions and the release data obtained were conductometrically fitted to Ficks equation to evaluate diffusion coefficients of released KNO₃. The release results were further analyzed by Ficks power law equation, and the possible mechanisms of KNO₃ release were explored at different experimental conditions. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2007     

Detection and differentiation of Salmonella serotypes using surface enhanced Raman scattering (SERS) technique

This research was conducted to prove that developed silver biopolymer nanoparticle substrate for surface enhanced Raman scattering (SERS) technique could detect and differentiate three different serotypes of Salmonella. Nanoparticle was prepared by adding 100 mg of silver nitrate to a 2 % polyvinyl alcohol solution, then adding 1 % trisodium citrate to reduce silver nitrate and produce silver encapsulated biopolymer nanoparticles. Then, nanoparticle was deposited on a stainless steel plate and used as SERS substrate. Fresh cultures of Salmonella typhimurium, Salmonella enteritidis and Salmonella infantis were washed and suspended in 10 mL of sterile deionized water. Approximately 5 μl of the bacterial suspensions were placed on the substrate individually and exposed to 785 nm laser excitation. SERS spectral data were recorded between 400 and 1,800 cm^?1. SERS signals were collected from 15 different spots on the substrate for each sample. PCA model was developed to classify Salmonella serotypes. PC1 identified 92 % of the variation between the Salmonella serotypes, and PC2 identified 6 % and in total 98 % between the serotypes. Soft independent modeling of class analogies of validation set gave an average correct classification of 92 %. Comparison of the SERS spectra of Salmonella serotypes indicated that both isolates have similar cell walls and cell membrane structures which were identified by spectral regions between 520 and 1,050 cm^?1. However, major differences were detected in cellular genetic material and proteins between 1,200 and 1,700 cm^?1. SERS with silver biopolymer nanoparticle substrate could be a promising tool in pathogen detection and it would potentially be used to classify them.