The synthesis of pixelated metamaterial cross polarizer using binary wind driven optimization algorithm

Microsystem Technologies - In this paper synthesis of two wideband Metamaterial Cross Polarizer (MCPs) is proposed. The synthesis of proposed MCPs is done by using Binary Wind Driven Optimization...     

Experimental investigations in powder mixed electric discharge machining of Ti–35Nb–7Ta–5Zrβ-titanium alloy

The present research is the first type of study in which the application of powder mixed electrical discharge machining (PMEDM) for the machining of β-phase titanium (β-Ti) alloy has been proposed. β-Ti alloys are new range of titanium alloys, which has a wide-spread application in dental, orthopedics, shape memory, and stents. The aim of the present study is to fabricate submicro- and nanoscale topography by PMEDM process to enhance the biocompatibility without affecting machining efficiency. The effect of Si powder concentration along with pulse current and duration on the surface and machining characteristics has been investigated. A significant decrease in surface crack density on the machined surface with 4 g/l Si powder concentration was observed. When β-Ti alloy was modified at 15 A pulse current, longer pulse interval with 8 g/l concentration of Si powder particles, the interconnected surface porosities with pore size 200–500 nm was observed. Moreover, at Si powder concentrations of 2 g/l and 4 g/l, the recast layer thickness is 8 µm and 2–3 µm, respectively. Elemental mapping analysis confirmed that PMEDM also generated carbides and oxides enriched surface, a favorable surface chemistry to enhance the biocompatibility of β-Ti alloy. Furthermore, PMEDM also enhances the machining performance by improving material removal rate and reducing tool wear rate.     

A novel application of micro-EDM process for the generation of nickel nanoparticles with different shapes

This article explains production of nickel nanoparticles through a micro-electrical discharge machining (EDM) process with a combination of different process parameters. The production of nickel nanoparticles was carried out in a dielectric medium (deionized water) with developed micro-EDM while polyvinyl alcohol worked as the stabilizing agent. The characterization of nickel nanoparticle was done by scanning electron microscope (SEM), Energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), UV–Vis spectroscopy, and Fourier transform infrared (FTIR) analysis. From this investigation, the mean crystal size of the nickel nanoparticles was found to be in the range of 15–20?mm for a pulse-on time variation of 2–0.3?µs and the crystal size was found to decrease with the decrease of pulse-on time. It was also observed that with this decrease, the shape and size of nickel nanoparticles change from spherical to needle-like. The dispersion stability of nickel nanofluid was determined by viscosity measurements and the dynamic viscosity was noted to decrease by decreasing the pulse duration. From the FTIR spectrum results, it was confirmed that the synthesized nickel nanoparticles in deionized water were pure and monolithic. UV–Vis–NIR spectroscopy depicted that the band gap energy increases with a reduction in the pulse-on time and obtains a higher band gap (5.31?eV) for 0.3?µs pulse-on time.     

Optical detection of CA 15.3 breast cancer antigen using CdS quantum dot

The present study focus on optical sensing of breast cancer antigen 15.3 (CA 15.3) using cadmium sulphide quantum dot (CdS‐QD) in saline and serum samples spiked with antigen. The surface of CdS‐QD was modified by cysteamine capping followed by tagging of CA 15.3 antibody. The samples were characterised using UV‐visible absorption spectroscopy (UV‐VIS Spectroscopy), Fourier transform infrared spectroscopy (FTIR), high‐resolution transmission electron microscopy (HRTEM) attached with energy‐dispersive X‐ray spectroscopy, phase contrast inverted epi‐fluorescence microscopy and photoluminescence (PL) spectrophotometry (EDS). The CdS‐QD showed a mean diameter of 3.02 ± 0.6 nm. The complex formed after antigen‐antibody interaction resulted in distinguishable optical and fluorescence intensity with respect to varying concentration of antigen. The PL study revealed that CA 15.3 antibody labelled CdS QD can detect CA 15.3 tumour marker even at very low concentration of 0.002 KU/L with a constant response time of 15 min. This study clearly indicates that detection of CA 15.3 at low concentration is possible using surface modified CdS QD in serum samples and can find immense applications in biosensor development for detection of breast cancer marker similar to various automated detection kits available in market.Inspec keywords: semiconductor quantum dots, cadmium compounds, II‐VI semiconductors, wide band gap semiconductors, cancer, tumours, optical sensors, biosensors, biomedical equipment, visible spectra, ultraviolet spectra, Fourier transform infrared spectra, transmission electron microscopy, X‐ray chemical analysis, fluorescence, optical microscopy, photoluminescence, proteins, molecular biophysics, nanosensors, nanomedicine, nanoparticlesOther keywords: optical detection, CA 15.3 breast cancer antigen, optical sensing, cadmium sulphide quantum dot, saline samples, serum samples, cysteamine capping, CA 15.3 antibody, UV‐visible absorption spectroscopy, Fourier transform infrared spectroscopy, high‐resolution transmission electron microscopy, energy dispersive X‐ray spectroscopy, phase contrast inverted epifluorescence microscopy, photoluminescence spectrophotometry, antigen‐antibody interaction, fluorescence intensity, optical intensity, CA 15.3 tumour marker, surface modified CdS QD, biosensor development, time 15 min, CdS     

Effect of friction stir processing and hybrid reinforcements on copper

In this research, a copper based surface composite was fabricated through dispersing hybrid composite particles onto its surface through friction stir processing (FSP) technique. Optical micrographs and scanning electron microscopy images indicates finer refinement of grains and particles dispersion into matrix along with its bonding and particle separation. As per the outcomes of microhardness analysis, hardness of the developed surface composite shows increment with increase in dispersion of volume fraction of hybrid particles. Strength of the developed copper surface composite exhibited a positive trend with introduction of hybrid reinforcement particle onto the surface of the composite but yet again ductility reduced. Wear resistance of the composite increased with reinforcement addition and the same was supported through worn out surface morphology. Fluctuations in friction coefficient value reduced with increase in particles, as for the presence in BN particles while the average frictional coefficient value was observed increasing. A reduction in corrosion rate was observed with increase in reinforcement particle dispersion onto copper matrix through FSP.     

Life cycle energy and carbon footprint analysis of photovoltaic battery microgrid system in India

Electricity supply in India is from a centralized grid. Many parts of the country experience grid interruptions. Life cycle energy and environmental analysis has been done for a 27 kWp photovoltaic system which acts as grid backup for 3 h outage in an Indian urban residential scenario. This paper discusses energy requirements and carbon emission for a PV storage system for five different battery technologies in Indian context. This can be used as a metric for comparative analysis for new batteries, with an undeveloped market. The energy requirements for the components are quantified and are compared in terms of energy payback time (EPBT) and Net Energy Ratio (NER). All the calculations are done for Indian context. EPBT is found to be in the range of 2–4.5 years for all the systems, while NER is in the range of 6.6–2.52. NaS has the highest emission factor of 0.67 kgCO₂/kWh and the least for NiCd (0.091 kgCO₂/kWh). These factors can be used to select a PV battery option and to target selection of materials and systems based on the reported values.     

The cost of sex revisited: effects of male gamete output of hermaphrodites that are asexual in their female capacity

The genetic cost of sexual reproduction has been attributed to two causes in mathematical formulations: male function or genome dilution. We develop and analyse a genetic model that shows that both costs occur, depending upon the conditions. The model differs from previous formulations in that the level of output and fertilization success of male gametes produced by hermaphrodites that are asexual in their female function (henceforth "parthenogenetic hermaphrodites") are treated as variables, rather than constants fixed at 0 or 1, as has previously been the case. By expressing the cost of sex in terms of per capita egg loss of sexual individuals and parthenogenetic hermaphrodites, we partition the cost into components due to male function and genome dilution. Which component dominates the cost of sex depends upon the relative male gamete output of the parthenogenetic hermaphrodites. The cost of sex is observed to increase, or remain unchanged in some marginal cases, with increases in (i) frequency of parthenogenetic hermaphrodites, (ii) fertilization success of male gametes produced by parthenogenetic hermaphrodites and (iii) potential eggs lost by diverting resources to male gamete production. In certain situations, parthenogenetic hermaphrodites with an intermediate level of male gamete output have the greatest fitness advantage over sexual individuals. If heritable variation for levels of male gamete output exists among parthenogenetic hermaphrodites, this raises the possibility of the evolution of optimal levels of male gamete production by parthenogenetic hermaphrodites through natural selection, in situations of recurring invasion of asexual populations by propagules from sexual populations, a scenario that is increasingly being appreciated as potentially fairly likely to occur in nature.     

Optimizing functionally graded nickel–zirconia coating profiles for thermal stress relaxation

The investigations on optimization of composite composition of nickel–zirconia for the functionally graded layered thermal barrier coating for the lowest but uniform stress field under thermal loading is presented. The procedure for obtaining temperature- and composition-dependent thermal and mechanical properties of various coating compositions is discussed. These material parameters were used in thermo-mechanical finite element stress analyses of a nickel substrate with the coating. The results showed that the Von-Mises stresses in the substrate and the interfaces were the lowest with the coating profile that followed a concave power law relationship with the index n ≈ 2.65.     

Non-Parametric Mixture Model Based Evolution of Level Sets and Application to Medical Images

We present a novel region-based curve evolution algorithm which has three primary contributions: (i) non-parametric estimation of probability distributions using the recently developed NP windows method; (ii) an inequality-constrained least squares method to model the image histogram with a mixture of nonparametric probability distributions; and (iii) accommodation of the partial volume effect, which is primarily due to low resolution images, and which often poses a significant challenge in medical image analysis (our primary application area). We first approximate the image intensity histogram as a mixture of non-parametric probability density functions (PDFs), justifying its use with respect to medical image analysis. The individual densities in the mixture are estimated using the recent NP windows PDF estimation method, which builds a continuous representation of discrete signals. A Bayesian framework is then formulated in which likelihood probabilities are given by the non-parametric PDFs and prior probabilities are calculated using an inequality constrained least squares method. The non-parametric PDFs are then learnt and the segmentation solution is spatially regularised using a level sets framework. The log ratio of the posterior probabilities is used to drive the level set evolution. As background to our approach, we recall related developments in level set methods. Results are presented for a set of synthetic and natural images as well as simulated and real medical images of various anatomical organs. Results on a range of images show the effectiveness of the proposed algorithm.     

Detection and quantification of valve stiction by the method of unknown input estimation

Valve stiction is one of the most common causes of oscillations in industrial process control loops. Such oscillations can degrade the overall performance of the loop and eventually the final product quality. The detection and quantification of valve stiction in industrial process control loops is thus important. From previous studies in the literature, a sticky valve has been shown to have a distinct signature of the stiction phenomena in its valve positioner data. However, the position of the modulating control valves is seldom available. We consider the problem of estimating the valve position as an unknown input estimation problem. In this work, we propose a novel application of the unknown input estimator in order to estimate the valve position given the process model and the data of the process variable and controller output. Using the estimated valve position, we can detect and also quantify the amount of stiction. We demonstrate the efficacy of the method through simulation examples where a sticky valve is deliberately introduced in the closed loop using a two-parameter stiction model available in the literature. Application of the proposed methodology to a laboratory scale flow control loop is presented. An industrial case study is also presented in which the algorithm accurately detects and quantifies stiction in the level control loop of a power plant.