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Thermal stability and electrochemical properties of PVP-protected Ru nanoparticles synthesized at room temperature
No full textStable ruthenium nanoparticles (RuNPs) have been synthesized by the chemical reduction of ruthenium trichloride trihydrate (RuCl3 centerdot 3H2O) using sodium borohydride (NaBH4) as a reductant and polyvinylpyrrolidone (PVP) as a protecting agent in the aqueous medium at room temperature. The nanoparticles thus prepared were characterized by their morphology and structural analysis from transmission electron microscopy (TEM), X-ray powder diffraction (XRD), UV–vis spectroscopy, Fourier transformation infrared and thermogravimetric analysis (TGA) techniques. The TEM image suggested a homogeneous distribution of PVP-protected RuNPs having a small average diameter of 2–4 nm with a chain-like network structure. The XRD pattern also confirmed that a crystallite size is around 2 nm of PVP-protected RuNPs having a single broad peak. The thermal stability studied using TGA, indicated good stability and the electrochemical properties of these nanoparticles revealed that saturation current increases for PVP-protected RuNPs/GC
Ultrasensitive and Selective Sensing of Selenium Using Nitrogen-Rich Ligand Interfaced Carbon Quantum Dots
No full textThis work reports a label-free, ultrasensitive, and selective optical chemosensory system for trace level detection of selenite (SeO32-), the most toxic form of selenium, in water. The probe, i.e., carbon quantum dots (CQDs), is designed from citric acid by means of pyrolysis and is interfaced with a newly synthesized nitrogen-rich ligand to create a selective sensor platform (functionalized CQDs, fCQDs) for selenite in a water matrix. Spectral (NMR, UV-vis, photoluminescence, Raman, and Fourier transform infrared analyses) and structural (high-resolution transmission electron microscopy) characteristics of the designed new probe were investigated. The developed sensor exhibits high sensitivity (limit of detection = 0.1 ppb), a wide detection range (0.1-1000 ppb range, relative standard deviation: 3.2%), and high selectivity even in the presence of commonly interfering ions reported to date, including Cl-, NO3-, NO2-, Br-, F-, As(V), As(III), Cu2+, Pb2+, Cd2+, Zn2+, Sr2+, Rb2+, Na+, Ca2+, Cs+, K+, Mg2+, Li+, NH4+, Co2+, etc. The observed selectivity is due to designed ligand characteristics in terms of strong Se-N chemistry. Ultrafast spectroscopic analysis of the fCQDs in the absence and presence of selenite was studied to understand the sensing mechanism. The sensor was successfully exemplified for real water samples and exhibits comparative performance to conventional ion channel chromatography as well as flame atomic absorption spectroscopy for selenite analysis. The promising results pave ways for realization of a field deployable device based upon a developed probe for selenite quantification in water
A pre-processing based optimized edge weighting method for colour constancy
No full textAn improvement in the existing weighted grey-edge (GE) framework for colour constancy is proposed. The acquired images are denoised by vector filtering and then, a two-step colour correction process is performed. In the first step, the GE method is used for estimating the global illuminant and perform the initial level of colour correction. The computed illuminant as well as the initial corrected image are used in the second step, which employs the weighted GE method to iteratively compute the final illuminant for obtaining the final colour corrected image. One hundred sixty-five standard test images from a publicly available colour constancy dataset were used to study the efficacy of the proposed algorithm. The results obtained indicate a significant improvement in the colour correction process as compared to the state-of-the-art colour constancy methods. The proposed algorithm reduced the mean angular error by approximately 67.85% compared to the existing weighted GE method
Understanding the gas sensing properties of polypyrrole coated tin oxide nanofiber mats
No full textTin oxide-polypyrrole composites have been widely studied for their enhanced sensing performance towards ammonia vapours, but further investigations are required for an understanding of the interaction mechanisms with different target analytes. In this work, polypyrrole coated tin oxide fibers have been synthesized using a two-step approach of electrospinning and vapour phase polymerization for the sensing of ammonia, ethanol, methanol, 2-propanol and acetone vapours. The resistance variation in the presence of these vapours of different nature and concentration is investigated for the determination of sensor response. A decrease in resistance occurred on interaction of tin oxide-polypyrrole with ammonia, as opposed to previous reported works. Partial reduction of polypyrrole due to interfacial interaction with tin oxide has been proposed to explain this behavior. High sensitivity of 7.45 is achieved for 1 ppm ammonia concentration. Furthermore, the sensor exhibited high sensitivity and a faster response towards ethanol vapours although methanol has the highest electron donating capability. The catalytic mechanism has been discussed to explain this interesting behavior. The results reveal that interaction between tin oxide and polypyrrole is crucial to control the predominant sensing mechanism
Photocatalytic and antibacterial biomimetic ZnO nanoparticles
No full textThe synthesis of nanoscale materials has gained considerable attention due to their excellent properties in photocatalysis and also as antimicrobials. More recently, bio-reduction mediated synthesis of such nanostructures has emerged as an environmentally friendly and economical alternative to traditional chemical synthesis. This study describes a strategy for extracellular bio-fabrication of highly stable ZnO nanoparticles from Saccharomyces cerevisiae fungus. The synthesized ZnO nanoparticles were characterized using UV-vis spectroscopy, Raman spectroscopy, X-ray diffraction (XRD), transmission electron microscopy (TEM) and Fourier transform infrared spectroscopy (FTIR). The obtained nanoparticles were then assessed for their antibacterial activity against E. Coli MTCC 1302. The photocatalytic performance of these nanoparticles was analyzed by reduction of model dye pollutant, i.e., 4-nitrophenol (4-NP). This study revealed excellent bactericidal and photocatalytic activity of bio-synthesized ZnO nanoparticles. Finally, a potential mechanism for their photocatalytic property is proposed
Comparative analyses of prediction models for inactivation of Escherichia coli in carrot juice by means of pulsed electric fields
No full textThis paper reports the prediction capacity of various microbial inactivation models to prefigure the bactericidal effect using pulsed electric field (PEF) on liquid food. The aim of study was to compare the various inactivation models based on accuracy and bias factor to find out the most accurate inactivation model for Escherichia coli present in carrot juice treated with PEF. In this study, E. coli suspended in carrot juice was treated with varying pulsed electric field strength for different intervals. The obtained data were utilized for the evaluation of parameters of Bigelow, Peleg, Hülsheger and Weibull inactivation models. Furthermore, secondary models were developed for Hülsheger and Weibull to predict the microbial inactivation at any level of field strength and treatment time. The secondary model for Hülsheger exhibits 5.8% error as compared to the Weibull model having 8.5% error in prediction of death kinetics of E. coli suspended in carrot juice by means of PEF. The comparative analysis of secondary models to forecast the unknown data set unveiled the superior functioning of Hülsheger model
Evaluation of atmospheric corrections on hyperspectral data with special reference to mineral mapping
No full textHyperspectral images have wide applications in the fields of geology, mineral exploration, agriculture, forestry and environmental studies etc. due to their narrow band width with numerous channels. However, these images commonly suffer from atmospheric effects, thereby limiting their use. In such a situation, atmospheric correction becomes a necessary pre-requisite for any further processing and accurate interpretation of spectra of different surface materials/objects. In the present study, two very advance atmospheric approaches i.e. QUAC and FLAASH have been applied on the hyperspectral remote sensing imagery. The spectra of vegetation, man-made structure and different minerals from the Gadag area of Karnataka, were extracted from the raw image and also from the QUAC and FLAASH corrected images. These spectra were compared among themselves and also with the existing USGS and JHU spectral library. FLAASH is rigorous atmospheric algorithm and requires various parameters to perform but it has capability to compensate the effects of atmospheric absorption. These absorption curves in any spectra play an important role in identification of the compositions. Therefore, the presence of unwanted absorption features can lead to wrong interpretation and identification of mineral composition. FLAASH also has an advantage of spectral polishing which provides smooth spectral curves which helps in accurate identification of composition of minerals. Therefore, this study recommends that FLAASH is better than QUAC for atmospheric correction and correct interpretation and identification of composition of any object or mineral
Quantifying and modeling of stream network using digital elevation models
No full textQuantifying and modeling of stream network using DEMs is the primary objective to understand earth surface processes. In the present study, DEMs of different quality, i.e. resolution, are evaluated for stream network quantification and modeling. The results are very encouraging in terms of the shape and geometry of the stream network. They emphasize the strong control of the DEM resolution and thresholding of flow accumulation/drainage area. Further, comparisons of the various morphometric parameters are also quite promising. The study highlights different relationships between various morphometric parameters obtained from the two DEMs used, thereby paving the way for the use of DEMs of different resolutions, interchangeably
Engineered nano particles: Nature, behavior, and effect on the environment
No full textIncreased application of engineered nano particles (ENPs) in production of various appliances and consumer items is increasing their presence in the natural environment. Although a wide variety of nano particles (NPs) are ubiquitously dispersed in ecosystems, risk assessment guidelines to describe their ageing, direct exposure, and long-term accumulation characteristics are poorly developed. In this review, we describe what is known about the life cycle of ENPs and their impact on natural systems and examine if there is a cohesive relationship between their transformation processes and bio-accessibility in various food chains. Different environmental stressors influence the fate of these particles in the environment. Composition of solid media, pore size, solution chemistry, mineral composition, presence of natural organic matter, and fluid velocity are some environmental stressors that influence the transformation, transport, and mobility of nano particles. Transformed nano particles can reduce cell viability, growth and morphology, enhance oxidative stress, and damage DNA in living organisms
A hybrid fabrication approach and profile error compensation for silicon aspheric optics
No full textAspheric optics is widely used for many optical applications due to their advantages, that is, light weight, cost-effectiveness and efficiency. There are many fabrication challenges which affect the quality of aspheric optics used for infrared-based applications. Diamond turning is one of the most suitable techniques for fabrication of infrared aspheric lens with high profile accuracies, due to its deterministic approach. However, for optics with large sag value, multiple machining cycles are required to make the best fit surface. Repeated machining cycles result in generation of inherent stresses leading to subsurface deformation and poor quality. In this study, hybrid approach of grinding and machining is proposed for fabrication of silicon infrared optics in large volume. The proposed approach results in reduced fabrication time and subsurface deformation with improved surface quality and tool life. The profile accuracy after compensation of profile error (Pt) is 0.21 µm and surface roughness (Ra) 10.5 nm is achieved