Efficiency of a dye-sensitized photoelectrochemical device using thionine and triturated zinc oxide at different potency

A new and novel material, triturated zinc oxide nanoparticles, which is eco-friendly, easily available, low in cost, has been used here for the first time for enhancement of photovoltage generation and efficiency of a dye-sensitized photoelectrochemical device. This material when diluted and strongly agitated, together termed as potentized, is used as nanomedicine for centuries. This study using this material at two different potencies (6C and 30C) shows that addition of this material to thionine dye of concentration 0.85 μM enhances photovoltage generation significantly. The efficiency obtained with the latter is ~0.41%, whereas it is ~0.003% with dye only.     

High‐Pressure Inactivation of Enzymes: A Review on Its Recent Applications on Fruit Purees and Juices

In the last 2 decades high‐pressure processing (HPP) has established itself as one of the most suitable nonthermal technologies applied to fruit products for the extension of shelf‐life. Several oxidative and pectic enzymes are responsible for deterioration in color, flavor, and texture in fruit purees and juices (FP&J). The effect of HPP on the activities of polyphenoloxidase, peroxidase, β‐glucosidase, pectinmethylesterase, polygalacturonase, lipoxygenase, amylase, and hydroperoxide lyase specific to FP&J have been studied by several researchers. In most of the cases, partial inactivation of the target enzymes was possible under the experimental domain, although their pressure sensitivity largely depended on the origin and their microenvironmental condition. The variable sensitivity of different enzymes also reflects on their kinetics. Several empirical models have been established to describe the kinetics of an enzyme specific to a FP&J. The scientific literature in the last decade illustrating the effects of HPP on enzymes in FP&J, enzymatic action on those products, mechanism of enzyme inactivation during high pressure, their inactivation kinetics, and several intrinsic and extrinsic factors influencing the efficacy of HPP is critically reviewed in this article. In addition, process optimization of HPP targeting specific enzymes is of great interest from an industrial approach. This review will give a fair idea about the target enzymes specific to FP&J and the optimum conditions needed to achieve sufficient inactivation during HPP treatment.     

An artificial neural network model to characterize porosity defects during solidification of A356 aluminum alloy

In this study, a data-driven multilayer perceptron-based neural network model has been developed to predict the percentage of total porosity and mechanical properties, namely yield strength, ultimate tensile strength and percentage of elongation during the solidification of A356 aluminum alloy. Some of the important processing parameters such as cooling rate, solidus velocity, thermal gradient and initial hydrogen content have been considered as inputs to this model. The network training architecture has been optimized using the gradient-based Broyden–Fletcher–Goldfarb–Shanno training algorithm to minimize the network training error within few training cycles. Parametric sensitivity analysis is carried out to characterize the influence of processing parameters (inputs) on the behavior of porosity formation and simultaneously, the tensile properties of A356 alloy castings. It has been observed that initial hydrogen content in the melt and cooling rate has significant influence on the porosity formation and eventually on the tensile properties of the cast product. There has been an excellent agreement between artificial neural network predictions and the target (measured) values of porosity and the tensile properties as depicted by the regression fit between these values.     

Bulk and nano‐mechanical behavior of silver and silver‐CNT‐reinforced hybrid polymer composites

The present study concerns study of the Bulk and nano‐mechanical properties of Ag‐CNT vis‐à‐vis Ag reinforced polymer composites. The Ag‐CNT hybrid powder blend was prepared by mechanical milling. Variation of the bulk and nano‐mechanical properties has been attributed to the morphological features and the degree of dispersion of the fillers. It has been found that dispersion of Ag‐CNT hybrid particle is beneficial for improvement of both the mechanical properties. POLYM. COMPOS., 37:2581–2587, 2016. © 2015 Society of Plastics Engineers     

Sol-gel derived silica-gel as a controlled delivery system of Andrographis paniculata extract and its anti-microbial efficacy

Encapsulation of herbal values into bio-compatible porous silica gel has been attempted with the aim of developing a sustainable, efficient, eco-friendly and controlled drug delivery system using greener traditional alternatives. Aqueous extraction of Andrographis paniculata and entrapment of the same into silica gel has been studied. FTIR peaks prove the presence of herbal values into the silica matrix. 27% of the herbal extract is released in the Phosphate Buffer Saline (PBS) buffer in a period of 240 hours.     

Design optimization of the 100 kV HV bushing for ITER-DNB

The 100 kV bushing of the Diagnostic Neutral Beam (DNB) injector is a cylindrical feedthrough which forms the interface between the gas insulated transmission line and the torus primary vacuum and provides all necessary services to the beam source. All conventions for safety, voltage holding requirement, vacuum compatibility and the choice of materials have been addressed in the design. Finite Element Analyses (FEAs) for the electrostatic and the structural configuration is carried out to validate the design of the High Voltage Bushing (HVB). Several iterations and optimizations of the stress shields are carried out to meet electrostatic criteria, especially at the triple point (the ceramic, metal and vacuum joint), which is critical for good voltage holding. Structural analyses is carried out to assess the stress distribution in the fiber reinforced plastic insulator, the alumina insulator and the integrated HVB for different load cases like operational orientation (horizontal), normal operation and accidental case. Design is further validated for seismic conditions for Seismic Loading-2 (SL-2).     

Dependency of Nγ on footing diameter for circular footings

By incorporating a variation in soil internal friction angle ? with mean principal stress σ_m, the dependency of bearing capacity factor N_γ with footing diameter B has been evaluated for circular footings. The evaluation has been performed by a lower bound finite element limit analysis in combination with a linear optimization. Two ?–σ_m curves, available from literature, were used. The magnitude of N_γ has been computed for several footing diameters, covering almost the entire possible range of model and field footing sizes. Factor N_γ is seen to decrease significantly with an increase in B. For B approximately greater than (i) 0.7 m for smooth footings (δ=0) and (ii) 0.35 m for rough footings (δ=?), N_γ varies almost linearly with B on a log–log scale. Once a relationship has been generated between N_γ and B, for a given design load, the required footing diameter can always be obtained.     

An application of reference point‐based NSGA‐II for power system congestion management ensuring system stability

In this paper, we formulate the power transmission congestion problem as a multiobjective optimization problem and solve it using the reference point NSGA‐II (R‐NSGA‐II) technique. Restructuring of the electric power industry has led to intensified use of the transmission grid, thereby causing more frequent power transmission congestion. Congestion threatens the power system security and reliability and is therefore a crucial issue in the unbundled power system scenario, which is usually managed by rescheduling the generators and the demand. Stability considerations should also be incorporated within the congestion management (CM) methodology so as to ensure secure stability margins post CM. In this paper, we formulate the CM problem in a pool model as a true multiobjective optimization problem with the three conflicting objectives of minimizing CM cost and maximizing the voltage stability margin and the transient stability margin. The multiobjective CM problem is solved using the R‐NSGA‐II method, which is a modification of the well‐known non‐dominated sorting genetic algorithm II (NSGA‐II) optimization algorithm. R‐NSGA‐II makes use of decision maker (DM)‐supplied preference information to guide the search for better solutions corresponding to the DM's preferences. The R‐NSGA‐II‐based CM approach is tested and verified on the IEEE‐39 bus system model, and its performance is compared with those of NSGA‐II and other reported method. The results obtained demonstrate that the proposed method is capable of obtaining Pareto‐optimal solutions as per the user's choice with fewer iterations, and therefore could be effectively used for solving the multiobjective CM problem. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.