Indian Institute of Technology Kharagpur

About: Indian Institute of Technology Kharagpur is a education organization based out in Kharagpur, India. It is known for research contribution in the topics: Computer science & Dielectric. The organization has 16887 authors who have published 38658 publications receiving 714526 citations.

Controlled synthesis and catalytic activity of copper sulfide nanostructured assemblies with different morphologies.

Abstract: A simple, template-free and mild solution chemistry route was employed to synthesize diverse copper sulfide (CuS) nanostructured assemblies at 70 °C by varying the solvent (water or ethylene glycol, or their ratios (3:1, 1:1 and 1:3)). The CuS structures in the shape of spheres and nanotubes were found to be assemblies of either nanoplates or nanoparticles. The nanotube formation was elaborately studied by varying the synthesis parameters such as temperature, reaction duration, precursor’s ratio, and counterions. Counterions such as NO3– and SO42– were found to be suitable for nanotube formation whereas in the presence of Cl– and OAc– ions, CuS flake-like and nanoparticle assemblies are obtained, respectively. The optical bandgaps for the CuS with different morphologies were measured to be in the range of 1.88–2.16 eV. The bandgap of CuS in the visible region of electromagnetic radiation prompted it to be used as photocatalyst in the past under natural light. However, we demonstrate here the similar catal...

Artificial Neural Network Modeling for Groundwater Level Forecasting in a River Island of Eastern India

Abstract: Forecasting of groundwater levels is very useful for planning integrated management of groundwater and surface water resources in a basin. In the present study, artificial neural network models have been developed for groundwater level forecasting in a river island of tropical humid region, eastern India. ANN modeling was carried out to predict groundwater levels 1 week ahead at 18 sites over the study area. The inputs to the ANN models consisted of weekly rainfall, pan evaporation, river stage, water level in the drain, pumping rate and groundwater level in the previous week, which led to 40 input nodes and 18 output nodes. Three different ANN training algorithms, viz., gradient descent with momentum and adaptive learning rate backpropagation (GDX) algorithm, Levenberg–Marquardt (LM) algorithm and Bayesian regularization (BR) algorithm were employed and their performance was evaluated. As the neural network became very large with 40 input nodes and 18 output nodes, the LM and BR algorithms took too much time to complete a single iteration. Consequently, the study area was divided into three clusters and the performance evaluation of the three ANN training algorithms was done separately for all the clusters. The performance of all the three ANN training algorithms in predicting groundwater levels over the study area was found to be almost equally good. However, the performance of the BR algorithm was found slightly superior to that of the GDX and LM algorithms. The ANN model trained with BR algorithm was further used for predicting groundwater levels 2, 3 and 4 weeks ahead in the tubewells of one cluster using the same inputs. It was found that though the accuracy of predicted groundwater levels generally decreases with an increase in the lead time, the predicted groundwater levels are reasonable for the larger lead times as well.

A Single-Inductor Multiple-Output Switcher With Simultaneous Buck, Boost, and Inverted Outputs

Abstract: Portable applications require multiple supplies with different output levels and some applications also require negative outputs. Single-inductor multiple-output (SIMO) switchers are a good for existing parallel output configurations. This study presents an SIMO dc-dc converter capable of generating buck, boost, and inverted outputs simultaneously. The operation of this class of converter being driven by the ripple in the inductor current the conventional averaging method does not work well. An inductor current ripple-based modeling approach has been proposed to accurately model and analyze the converter. The control, cross-coupling, and cross-regulation transfer functions, generated through the model, accurately represent the performance of the converter. The proof of concept has been carried out with discrete components on an in-house built PCB and the experimental results validating the steady state and ac responses of the converter are presented.

Electrochemical synthesis of polyaniline and its comparison with chemically synthesized polyaniline

Abstract: The synthesis of polyaniline (PAni) powder was carried out from 0.15M of aniline and 1M of HCl in distilled water at room temperature in a single compartment electrochemical cell. The PAni was again synthesized chemically keeping the composition and temperature same as electrochemical process but adding equimolar amount of ammonium peroxydisulfate as an oxidizing agent. Then the PAni obtained from these two methods were characterized by the conductivity, solubility, X-ray, FTIR, TGA, UV, and SEM, and compared. Result shows that the electrochemically synthesized PAni (ECS-PAni) has somewhat lower conductivity, higher solubility, more benzenoid rings than quinoid rings, lower crystallinity, higher band energy, and higher particle size than that of chemically synthesized PAni (CS-PAni). © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 104: 1900–1904, 2007