Conduction nature of conical pores in PET membrane

Summary The preparation of conical pores in polyethylene terepthlate (PET) membrane is described. The conical pores prepared in PET by track etching technique. For this purpose, Cl⁹⁺ ion irradiated film was placed into an electrolytic cell and etched from one side while other side of membrane was protected by a stopping medium. During etching, current was recorded as a function of time, which shows a sudden change, indicating the pores breakthrough. After breakthrough, the etch process is interrupted by replacing the etching solution. After etching, the current voltage characteristics were determined under symmetric bath conditions. The resulting conical pores show non ohmic behavior, similar to that of an electronic diode.     

Broadening of Photonic Band Gap in a One—Dimensional Superconductor Star Waveguide Structure

The present paper describes the theoretical investigation of enlarged reflection bands (photonic band gaps) in a 1D star waveguide (SWG) structure consists of superconductor and dielectric as its constituent materials. For the present study, we take the different combinations of superconductor and dielectric materials as a backbone and side branches of the SWG structure. In order to obtain the dispersion relation, Interface Response Theory (IRT) has been employed. Photonic band gaps of SWG structure having superconductor?Csuperconductor, superconductor?Cdielectric, and dielectric?Csuperconductor materials are compared with the band gaps of the conventional photonic crystal (PC) structure having superconductor?Csuperconductor and dielectric?Csuperconductor materials. Analysis of the dispersion characteristics shows that there exists no band gaps for conventional PC when both layers are made of the same superconducting materials (as the usual case) while the SWG structure shows forbidden bands of finite width even the backbone and side branches are made of same materials. Also, the SWG structure having superconductor?Cdielectric shows the wider reflection bands in comparison with the structure having dielectric?Csuperconductor as its constituent materials, while for the conventional PC structure it is same in both the cases. Further, the effect of temperature and the effect of variation of number of grafted branches on the photonic bands of SWG structure have been studied.     

Corrosion Characteristics of Ni-Based Hardfacing Alloy Deposited on Stainless Steel Substrate by Laser Cladding

Metallurgical and Materials Transactions A - In this study, corrosion characteristics of a nickel-based Ni-Mo-Cr-Si hardfacing alloy having 32Mo, 15Cr, and 3Si (wt pct) as alloying...     

Plant Nutrition: An Effective Way to Alleviate Abiotic Stress in Agricultural Crops

By the year 2050, the world’s population is predicted to have grown to around 9–10 billion people. The food demand in many countries continues to increase with population growth. Various abiotic stresses such as temperature, soil salinity and moisture all have an impact on plant growth and development at all levels of plant growth, including the overall plant, tissue cell, and even sub-cellular level. These abiotic stresses directly harm plants by causing protein denaturation and aggregation as well as increased fluidity of membrane lipids. In addition to direct effects, indirect damage also includes protein synthesis inhibition, protein breakdown, and membranous loss in chloroplasts and mitochondria. Abiotic stress during the reproductive stage results in flower drop, pollen sterility, pollen tube deformation, ovule abortion, and reduced yield. Plant nutrition is one of the most effective ways of reducing abiotic stress in agricultural crops. In this paper, we have discussed the effectiveness of different nutrients for alleviating abiotic stress. The roles of primary nutrients (nitrogen, phosphorous and potassium), secondary nutrients (calcium, magnesium and sulphur), micronutrients (zinc, boron, iron and copper), and beneficial nutrients (cobalt, selenium and silicon) in alleviating abiotic stress in crop plants are discussed.     

Determination of Thermal Parameters of Vanadium Oxide Uncooled Microbolometer Infrared Detector

Vanadium oxide thin films are the potential candidates for uncooled microbolometers due to their high temperature coefficient of resistance (TCR) at room temperature. A 2D array of 10-element test microbolometer without air-gap thermal isolation structure was fabricated with pulsed laser deposited vanadium oxide as IR sensing layer for the first time. Infrared responsivity of the uncooled microbolometer was evaluated in the spectral region 8-15 μm. The device exhibits responsivity of about 12 V/W at 30 Hz chopper frequency for 20 μA bias current. Thermal time constant (τ), Thermal conductance (G) and thermal capacitance (C) are the thermal parameters characterize the performance of the uncooled microbolometer infrared detectors are determined as 15 ms, ～10^-3 W/K and ～3.5 × 10^-5 J/K respectively. The influence of the thermal parameters on the performance of the microbolometer is discussed.     

Surface Tension Profiles under Various Microwave Radiation Modes

Surface tension of fluids is crucial for multiphase systems and is often controlled during industrial processes by introducing surfactants. In this study, effect of various microwave radiation modes on surface tension of water was investigated as an alternative physical method to manipulate the surface tension without using chemicals. It is found that surface tension decreased quickly while temperature increased during microwave. Once the radiation was turned off, the temperature returned rapidly as expected. However, surface tension did not recover so much. The minimum surface tension after microwave radiation depended on the power. Moreover, a second radiation can have additional reduction on surface tension.     

Clustering and selection of multiple criteria alternatives using unsupervised and supervised neural networks

There are decision-making problems that involve grouping and selecting a set of alternatives. Traditional decision-making approaches treat different sets of alternatives with the same method of analysis and selection. In this paper, we propose clustering alternatives into different sets so that different methods of analysis, selection, and implementation for each set can be applied. We consider multiple criteria decision-making alternatives where the decision-maker is faced with several conflicting and non-commensurate objectives (or criteria). For example, consider buying a set of computers for a company that vary in terms of their functions, prices, and computing powers. In this paper, we develop theories and procedures for clustering and selecting discrete multiple criteria alternatives. The sets of alternatives clustered are mutually exclusive and are based on (1) similar features among alternatives, and (2) preferential structure of the decision-maker. The decision-making process can be broken down into three steps: (1) generating alternatives; (2) grouping or clustering alternatives based on similarity of their features; and (3) choosing one or more alternatives from each cluster of alternatives. We utilize unsupervised learning clustering artificial neural networks (ANN) with variable weights for clustering of alternatives, and we use feedforward ANN for the selection of the best alternatives for each cluster of alternatives. The decision-maker is interactively involved by comparing and contrasting alternatives within each group so that the best alternative can be selected from each group. For the learning mechanism of ANN, we proposed using a generalized Euclidean distance where by changing its coefficients new formation of clusters of alternatives can be achieved. The algorithm is interactive and the results are independent of the initial set-up information. Some examples and computational results are presented.