Excellent rectifying characteristics in Au/n-CdTe diodes upon exposure to rf nitrogen plasma

Nitrogen plasma exposure (NPE) effects on indium doped bulk n-CdTe are reported here. Excellent rectifying characteristics of Au/n-CdTe Schottky diodes, with an increase in the barrier height, and large reverse breakdown voltages are observed after the plasma exposure. Surface damage is found to be absent in the plasma exposed samples. The breakdown mechanism of the heavily doped Schottky diodes is found to shift from the Zener to avalanche after the nitrogen plasma exposure, pointing to a change in the doping close to the surface which was also verified by C-V measurements. The thermal stability of the plasma exposure process is seen up to a temperature of 350 degrees C, thereby enabling the high temperature processing of the samples for device fabrication. The characteristics of the NPE diodes are stable over a year implying excellent diode quality. A plausible model based on Fermi level pinning by acceptor-like states created by plasma exposure is proposed to explain the observations.

Fuzzy optimization model for water quality management of a river system - Closure

A fuzzy waste-load allocation model, FWLAM, is developed for water quality management of a river system using fuzzy multiple-objective optimization. An important feature of this model is its capability to incorporate the aspirations and conflicting objectives of the pollution control agency and dischargers. The vagueness associated with specifying the water quality criteria and fraction removal levels is modeled in a fuzzy framework. The goals related to the pollution control agency and dischargers are expressed as fuzzy sets. The membership functions of these fuzzy sets are considered to represent the variation of satisfaction levels of the pollution control agency and dischargers in attaining their respective goals. Two formulations—namely, the MAX-MIN and MAX-BIAS formulations—are proposed for FWLAM. The MAX-MIN formulation maximizes the minimum satisfaction level in the system. The MAX-BIAS formulation maximizes a bias measure, giving a solution that favors the dischargers. Maximization of the bias measure attempts to keep the satisfaction levels of the dischargers away from the minimum satisfaction level and that of the pollution control agency close to the minimum satisfaction level. Most of the conventional water quality management models use waste treatment cost curves that are uncertain and nonlinear. Unlike such models, FWLAM avoids the use of cost curves. Further, the model provides the flexibility for the pollution control agency and dischargers to specify their aspirations independently.

Role of predictors in downscaling surface temperature to river basin in India for IPCC SRES scenarios using support vector machine

In this paper, downscaling models are developed using a support vector machine (SVM) for obtaining projections of monthly mean maximum and minimum temperatures (T-max and T-min) to river-basin scale. The effectiveness of the model is demonstrated through application to downscale the predictands for the catchment of the Malaprabha reservoir in India, which is considered to be a climatically sensitive region. The probable predictor variables are extracted from (1) the National Centers for Environmental Prediction (NCEP) reanalysis dataset for the period 1978-2000, and (2) the simulations from the third-generation Canadian Coupled Global Climate Model (CGCM3) for emission scenarios A1B, A2, B1 and COMMIT for the period 1978-2100. The predictor variables are classified into three groups, namely A, B and C. Large-scale atmospheric variables Such as air temperature, zonal and meridional wind velocities at 925 nib which are often used for downscaling temperature are considered as predictors in Group A. Surface flux variables such as latent heat (LH), sensible heat, shortwave radiation and longwave radiation fluxes, which control temperature of the Earth's surface are tried as plausible predictors in Group B. Group C comprises of all the predictor variables in both the Groups A and B. The scatter plots and cross-correlations are used for verifying the reliability of the simulation of the predictor variables by the CGCM3 and to Study the predictor-predictand relationships. The impact of trend in predictor variables on downscaled temperature was studied. The predictor, air temperature at 925 mb showed an increasing trend, while the rest of the predictors showed no trend. The performance of the SVM models that are developed, one for each combination of predictor group, predictand, calibration period and location-based stratification (land, land and ocean) of climate variables, was evaluated. In general, the models which use predictor variables pertaining to land surface improved the performance of SVM models for downscaling T-max and T-min

Comments on "Room temperature interfacial reactions in electrodeposited Au/Sn couples"

Recently, Tang et al. (Acta Mater. 56 (2008) 5818) published a paper explaining room temperature growth of the phases in the Au/Sn system. In their analysis, they considered Au as the only mobile species for all the product phases, and Sn as virtually immobile. It is shown here that this analysis is not correct, since Sn has a higher diffusion rate through the AuSn4 phase. On the other hand, the mobilities of species in the AuSn2 phase are as yet unknown.

Surface-enhanced Raman scattering of molecules adsorbed on nanocrystalline Au and Ag films formed at the organic-aqueous interface

Surface-enhanced Raman scattering (SERS) of pyridine adsorbed on ultrathin nanocrystalline Au and Ag films generated at the liquid-liquid interface has been investigated. The shifts and intensification of bands formed with these films comprising metal nanoparticles are comparable to those found with other types of Au and Ag substrates. SERS of rhodamine 6G adsorbed on Ag films has also been studied. The results demonstrate that nanocrystalline metal films prepared by the simple method involving the organic-aqueous interface can be used effectively for SERS investigations.

Multiobjective Analysis of Irrigation Planning in River Basin Development

A river basin that is extensively developed in the downstream reaches and that has a high potential for development in the upper reaches is considered for irrigation planning. A four-reservoir system is modeled on a monthly basis by using a mathematical programing (LP) formulation to find optimum cropping patterns, subject to land, water, and downstream release constraints. The model is applied to a fiver basin in India. Two objectives, maximizing net economic benefits and maximizing irrigated cropped area, considered in the model are analyzed in the context of multiobjective planning, and the tradeoffs are discussed.

Optimal irrigation planning in river basin development: The case of the Upper Cauvery river basin

The study deals with the irrigation planning of the Cauvery river basin in peninsular India which is extensively developed in the downstream reaches and has a high potential for development in the upper reaches. A four-reservoir system is modelled on a monthly basis by using a mathematical programming (LP) formulation to find optimum cropping patterns, subject to land, water and downstream release constraints, and applied to the Cauvery basin. Two objectives, maximizing net economic benefits and maximizing irrigated cropped area, considered in the model are analysed in the context of multiobjective planning and the trade-offs discussed.

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA)problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max-min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga-Bhadra river system in India.

Road kills of amphibians in different land use areas from Sharavathi river basin, central Western Ghats, India

A survey of amphibian mortality on roads was carried out in the Sharavathi river basin in the central Western Ghats. Road kills in three different land use areas: agricultural fields, water bodies and forests were recorded for four days along three 100m stretches in each type of area. One-hundred-and-forty-four individuals belonging to two orders, eight families, 11 genera and 13 species were recorded in the survey. Kills/km observed were: in forest 55, agricultural fields 38 and water bodies 27, for an overall average of 40 kills/km. Kill species compositions varied significantly between land use areas, but not overall kill rates.

A Methanol-Tolerant Carbon-Supported Pt-Au Alloy Cathode Catalyst for Direct Methanol Fuel Cells and Its Evaluation by DFT

A Pt-Au alloy catalyst of varying compositions is prepared by codeposition of Pt and Au nanoparticles onto a carbon support to evaluate its electrocatalytic activity toward an oxygen reduction reaction (ORR) with methanol tolerance in direct methanol fuel cells. The optimum atomic weight ratio of Pt to Au in the carbon-supported Pt-Au alloy (Pt-Au/C) as established by cell polarization, linear-sweep voltammetry (LSV), and cyclic voltammetry (CV) studies is determined to be 2:1. A direct methanol fuel cell (DMFC) comprising a carbon-supported Pt-Au (2:1) alloy as the cathode catalyst delivers a peak power density of 120 mW/cm2 at 70 °C in contrast to the peak power density value of 80 mW/cm2 delivered by the DMFC with carbon-supported Pt catalyst operating under identical conditions. Density functional theory (DFT) calculations on a small model cluster reflect electron transfer from Pt to Au within the alloy to be responsible for the synergistic promotion of the oxygen-reduction reaction on a Pt-Au electrode.

Investigations on magnetron sputtered ZnO thin films and Au/ZnO Schottky diodes

Magnetron sputtering is a promising technique for the growth of oxide materials including ZnO, which allows deposition of films at low temperatures with good electrical properties. The current-voltage (I-P) characteristics of An Schottky contacts on magnetron sputtered ZnO, films have been measured over a temperature range of 278-358K. Both effective barrier height (phi(B,eff)) and ideality factor (n) are found to be a function of temperature, and this behavior has been interpreted on the basis of a Gaussian distribution of barrier heights due to barrier height inhomogeneities that prevail at the interface. Density of states (DOS) near the Fermi level is determined using a model based on the space charge limited current (SCLC). The dispersion in both real and imaginary parts of the dielectric constant at low frequencies, with increase in temperature is attributed to the space charge effect. Complex impedance plots exhibited two semicircles, which corresponds to bulk grains and the grain boundaries. (c) 2006 Elsevier B.V. All rights reserved.

Road kills of amphibians in different land use areas from Sharavathi river basin, central Western Ghats, India

A survey of amphibian mortality on roads was carried out in the Sharavathi river basin in the central Western Ghats. Road kills in three different land use areas: agricultural fields, water bodies and forests were recorded for four days along three 100m stretches in each type of area. One-hundred-and-forty-four individuals belonging to two orders, eight families, 11 genera and 13 species were recorded in the survey. Kills/km observed were: in forest 55, agricultural fields 38 and water bodies 27, for an overall average of 40 kills/km. Kill species compositions varied significantly between land use areas, but not overall kill rates.

Scaling behavior of plasmon coupling in Au and ReO3 nanoparticles incorporated in polymer matrices

Polymer nanocomposites containing different concentrations of Au nanoparticles have been investigated by small angle X-ray scattering and electronic absorption spectroscopy. The variation in the surface plasmon resonance (SPR) band of Au nanoparticles with concentration is described by a scaling law. The variation in the plasmon band of ReO3 nanoparticles embedded in polymers also follows a similar scaling law. Sistance dependence of plasmon coupling in polymer composites f metal nanoparticles. (C) 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Risk minimization in water quality control problems of a river system

Methodologies are presented for minimization of risk in a river water quality management problem. A risk minimization model is developed to minimize the risk of low water quality along a river in the face of conflict among various stake holders. The model consists of three parts: a water quality simulation model, a risk evaluation model with uncertainty analysis and an optimization model. Sensitivity analysis, First Order Reliability Analysis (FORA) and Monte-Carlo simulations are performed to evaluate the fuzzy risk of low water quality. Fuzzy multiobjective programming is used to formulate the multiobjective model. Probabilistic Global Search Laussane (PGSL), a global search algorithm developed recently, is used for solving the resulting non-linear optimization problem. The algorithm is based on the assumption that better sets of points are more likely to be found in the neighborhood of good sets of points, therefore intensifying the search in the regions that contain good solutions. Another model is developed for risk minimization, which deals with only the moments of the generated probability density functions of the water quality indicators. Suitable skewness values of water quality indicators, which lead to low fuzzy risk are identified. Results of the models are compared with the results of a deterministic fuzzy waste load allocation model (FWLAM), when methodologies are applied to the case study of Tunga-Bhadra river system in southern India, with a steady state BOD-DO model. The fractional removal levels resulting from the risk minimization model are slightly higher, but result in a significant reduction in risk of low water quality. (c) 2005 Elsevier Ltd. All rights reserved.