Pt-Au/C cathode with enhanced oxygen-reduction activity in PEFCs

Carbon-supported Pt-Au (Pt-Au/C) catalyst is prepared separately by impregnation, colloidal and micro-emulsion methods, and characterized by physical and electrochemical methods. Highest catalytic activity towards oxygen-reduction reaction (ORR) is exhibited by Pt-Au/C catalyst prepared by colloidal method. The optimum atomic ratio of Pt to Au in Pt-Au/C catalyst prepared by colloidal method is determined using linear-sweep and cyclic voltammetry in conjunction with cell-polarization studies. Among 3:1, 2:1 and 1:1 Pt-Au/C catalysts, (3:1) Pt-Au/C exhibits maximum electrochemical activity towards ORR. Powder X-ray diffraction pattern and transmission electron micrograph suggest Pt-Au alloy nanoparticles to be well dispersed onto the carbon-support. Energy dispersive X-ray analysis and inductively coupled plasma-optical emission spectroscopy data suggest that the atomic ratios of the alloying elements match well with the expected values. A polymer electrolyte fuel cell (PEFC) operating at 0 center dot 6 V with (3:1) Pt-Au/C cathode delivers a maximum power-density of 0 center dot 65 W/cm (2) in relation to 0 center dot 53 W/cm (2) delivered by the PEFC with pristine carbon-supported Pt cathode.

Correction for Bias in Downscaling GCM Simulations for Hydrologic Impact Assessment

In a statistical downscaling model, it is important to remove the bias of General Circulations Model (GCM) outputs resulting from various assumptions about the geophysical processes. One conventional method for correcting such bias is standardisation, which is used prior to statistical downscaling to reduce systematic bias in the mean and variances of GCM predictors relative to the observations or National Centre for Environmental Prediction/ National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data. A major drawback of standardisation is that it may reduce the bias in the mean and variance of the predictor variable but it is much harder to accommodate the bias in large-scale patterns of atmospheric circulation in GCMs (e.g. shifts in the dominant storm track relative to observed data) or unrealistic inter-variable relationships. While predicting hydrologic scenarios, such uncorrected bias should be taken care of; otherwise it will propagate in the computations for subsequent years. A statistical method based on equi-probability transformation is applied in this study after downscaling, to remove the bias from the predicted hydrologic variable relative to the observed hydrologic variable for a baseline period. The model is applied in prediction of monsoon stream flow of Mahanadi River in India, from GCM generated large scale climatological data.

Landslide susceptibility mapping in the downstream region of Sharavathi river basin, Central Western Ghats

Landslides are hazards encountered during monsoon in undulating terrains of Western Ghats causing geomorphic make over of earth surface resulting in significant damages to life and property. An attempt is made in this paper to identify landslides susceptibility regions in the Sharavathi river basin downstream using frequency ratio method based on the field investigations during July- November 2007. In this regard, base layers of spatial data such as topography, land cover, geology and soil were considered. This is supplemented with the field investigations of landslides. Factors that influence landslide were extracted from the spatial database. The probabilistic model -frequency ratio is computed based on these factors. Landslide susceptibility indices were computed and grouped into five classes. Validation of LHS, showed an accuracy of 89% as 25 of the 28 regions tallied with the field condition of highly vulnerable landslide regions. The landslide susceptible map generated for the downstream would be useful for the district officials to implement appropriate mitigation measures to reduce hazards.

Bioenergy Status of Sharavathi River Basin, Western Ghats, India

Most of the developing countries including India depend heavily on bioenergy and it accounts for about 15% of the global energy usage. Its role in meeting a region’s requirement has increased the interest of assessing the status of biomass availability in a region. The present work deals with the bioenergy status in the Linganamakki reservoir catchment of the Sharavathi river basin, Western Ghats,India, by assessing the energy supply and sector wise energy consumption. The study reveals that majority of the households (92.17%) depend on fuelwood for their domestic energy needs with the per capita fuelwood consumption of 1.2 tonnes/year, which is higher than the national average (0.7 tonnes/year). This higher dependence on fuelwood has contributed to the degradation of forests,resulting in scarcity of bioresources necessitating exploration of viable energy alternatives to meet the growing energy demand.

Plant Diversity in the Sharavathi River Basin in Relation to Human Disturbance

Changes in vegetation are taking place due to anthropogenic activities since the colonization of the evergreen forest zone of Western Ghats. The forests of the Western Ghats were contiguous and uniformly rich in endemism within each climatic and physiographic regime. The region continues to be one of the biodiversity hot spots of the world. However unplanned developmental activities are altering the balance of the ecosystem. This study focuses on the floristic structure, composition and diversity of forests with varying degree of human disturbances. Based on the investigations, various strategies for conservation and sustainable utilization of forest resources were proposed.

Sharavathi River Basin Flora Information System(SRFIS)

The INFORMATION SYSTEM with user friendly GUI’s (Graphical user Interface) is developed to maintain the flora data and generate reports for Sharavathi River Basin. The database consists of the information related to trees, herbs, shrubs and climbers. The data is based on the primary field survey and the information available in flora of Shimoga, Karnataka and Hassan flora. User friendly query options based on dichotomous keys are provided to help user to retrieve the data while data entry options aid in updating and editing the database at family, genus and species levels.

River water quality response under hypothetical climate change scenarios in Tunga-Bhadra river, India

Analysis of climate change impacts on streamflow by perturbing the climate inputs has been a concern for many authors in the past few years, but there are few analyses for the impacts on water quality. To examine the impact of change in climate variables on the water quality parameters, the water quality input variables have to be perturbed. The primary input variables that can be considered for such an analysis are streamflow and water temperature, which are affected by changes in precipitation and air temperature, respectively. Using hypothetical scenarios to represent both greenhouse warming and streamflow changes, the sensitivity of the water quality parameters has been evaluated under conditions of altered river flow and river temperature in this article. Historical data analysis of hydroclimatic variables is carried out, which includes flow duration exceedance percentage (e.g. Q90), single low- flow indices (e.g. 7Q10, 30Q10) and relationships between climatic variables and surface variables. For the study region of Tunga-Bhadra river in India, low flows are found to be decreasing and water temperatures are found to be increasing. As a result, there is a reduction in dissolved oxygen (DO) levels found in recent years. Water quality responses of six hypothetical climate change scenarios were simulated by the water quality model, QUAL2K. A simple linear regression relation between air and water temperature is used to generate the scenarios for river water temperature. The results suggest that all the hypothetical climate change scenarios would cause impairment in water quality. It was found that there is a significant decrease in DO levels due to the impact of climate change on temperature and flows, even when the discharges were at safe permissible levels set by pollution control agencies (PCAs). The necessity to improve the standards of PCA and develop adaptation policies for the dischargers to account for climate change is examined through a fuzzy waste load allocation model developed earlier. Copyright (C) 2011 John Wiley & Sons, Ltd.

Activities of indium in solid solutions of Cu+In, Au+In and Cu+Au+In alloys

Thin foils of Cu, Au and Cu + Au alloys embedded in indium sesquioxide were equilibrated with controlled streams of CO-CO2 mixtures. The equilibrium concentrations of indium in the foils were determined by neutron activation analysis. The corresponding chemical potentials of indium were calculated from the standard free energies of formation of carbon monoxide, carbon dioxide, and indium oxide. It was found that the size difference between the solute and the solvent does not make significant contributions to the solute—solute interaction energy in the α-phase. The chemical potential of indium at one at.% concentration is 8.6 Kcals more negative in gold than in copper at 900°K. The variation of this chemical potential with alloy composition in Cu + Au system was in good agreement with Alcock and Richardson's quasichemical equation. The agreement is strengthened by the accurate knowledge of the co-ordination number in these substitutional solid solutions from X-ray diffraction studies.

Chemical potential of germanium in its solid solutions with Cu, Ag and Au

Thin foils of copper, silver and gold were equilibrated with tetragonal GeO2 under controlled View the MathML source gas streams at 1000 K. The equilibrium concentration of germanium in the foils was determined by the X-ray fluorescence technique. The standard free energy of formation of tetragonal GeO2 was measured by a solid oxide galvanic cell. The chemical potential of germanium calculated from the experimental data and the free energies of formation of carbon monoxide and carbon dioxide was found to decrease in the sequence Ag + Ge > Au + Ge > Cu + Ge. The more negative value for the chemical potential of germanium in solid copper, compared to that in solid gold, cannot be explained in terms of the strain energy factor, electro-negativity differences or the vaporization energies of the solvent, and suggests that the d band and its hybridization with s electrons are an important factor in determining the absolute values for the chemical potential in dilute solutions. However, the variation of the chemical potential with solute concentration can be correlated to the concentration of s and p electrons in the outer shell.

Solute solute and solvent solute interactions in solid solutions of Cu+Sn, Au+Sn and Cu+Au+Sn alloys

The chemical potentials of tin in its α-solid solutions with Cu, Au and Cu + Au alloys have been measured using a gas-solid equilibration technique. The variation of the excess chemical potential of tin with its composition in the alloy is related to the solute-solute repulsive interaction, while the excess chemical potential at infinite dilution of the solute is a measure of solvent-solute interaction energies. It is shown that solute-solute interaction is primarily determined by the concentration of (s + p) electrons in the conduction band, although the interaction energies are smaller than those predicted by either the rigid band model or calculation based on Friedel oscillations in the potential function. Finally, the variation of the solvent-solute interaction with solvent composition in the ternary system can be accounted for in terms of a quasi-chemical treatment which takes into account the clustering of the solvent atoms around the solute.

Effect of surface on the conductance characteristics of Au‐Bi2Sr2CaCu2O8+δ (single crystal) point contact junctions

We report the effect of surface treatments on the dynamic conductance curves (G=dI/dV‐V) of Au‐Bi2Sr2CaCu2O8+δ (single crystal) point contact junctions of variable junction conductances (100 mS≳G≳100 μS). We find that if the crystal surface is cleaved freshly just prior to making contacts, all irreproducible sharp multiple features often observed in tunneling data of Bi(2212) oxide superconductors disappear. If the cleaved crystal surfaces are left under ambient conditions for a few days and the tunneling experiments are repeated, these multiple features reappear. We also find that if the current in the junction is made to pass predominantly through the bulk (and not along the surface), gap features are sharper. The observed conductance curves are fitted to a modified model [G. E. Blonder et al., Phys. Rev. B 25, 4515 (1982)] and estimated gap values are Δ≂28 to 30 meV corresponding to the ratio 2Δ/kBTc ≂ 7.5 with lifetime broadening Γ/Δ≂0.2. We conclude that the sharp multiple features observed in Bi(2212) tunneling curves has no intrinsic origin in the bulk and they arise from the surface only.

Daily relative humidity projections in an Indian river basin for IPCC SRES scenarios

A two-stage methodology is developed to obtain future projections of daily relative humidity in a river basin for climate change scenarios. In the first stage, Support Vector Machine (SVM) models are developed to downscale nine sets of predictor variables (large-scale atmospheric variables) for Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES) (A1B, A2, B1, and COMMIT) to R (H) in a river basin at monthly scale. Uncertainty in the future projections of R (H) is studied for combinations of SRES scenarios, and predictors selected. Subsequently, in the second stage, the monthly sequences of R (H) are disaggregated to daily scale using k-nearest neighbor method. The effectiveness of the developed methodology is demonstrated through application to the catchment of Malaprabha reservoir in India. For downscaling, the probable predictor variables are extracted from the (1) National Centers for Environmental Prediction reanalysis data set for the period 1978-2000 and (2) simulations of the third-generation Canadian Coupled Global Climate Model for the period 1978-2100. The performance of the downscaling and disaggregation models is evaluated by split sample validation. Results show that among the SVM models, the model developed using predictors pertaining to only land location performed better. The R (H) is projected to increase in the future for A1B and A2 scenarios, while no trend is discerned for B1 and COMMIT.