CuInS2/In2S3 Cells using a Cost-effective Technique: Significance of Precursor Ratios on Cell Parameters

Thin film solar cells having structure CuInS2/In2S3 were fabricated using chemical spray pyrolysis (CSP) technique over ITO coated glass. Top electrode was silver film (area 0.05 cm2). Cu/In ratio and S/Cu in the precursor solution for CuInS2 were fixed as 1.2 and 5 respectively. In/S ratio in the precursor solution for In2S3 was fixed as 1.2/8. An efficiency of 0.6% (fill factor -37.6%) was obtained. Cu diffusion to the In2S3 layer, which deteriorates junction properties, is inevitable in CuInS2/In2S3 cell. So to decrease this effect and to ensure a Cu-free In2S3 layer at the top of the cell, Cu/In ratio was reduced to 1. Then a remarkable increase in short circuit current density was occurred from 3 mA/cm2 to 14.8 mA/cm2 and an efficiency of 2.13% was achieved. Also when In/S ratio was altered to 1.2/12, the short circuit current density increased to 17.8 mA/cm2 with an improved fill factor of 32% and efficiency remaining as 2%. Thus Cu/In and In/S ratios in the precursor solutions play a crucial role in determining the cell parameters

Reliable and Damage-Free Estimation of Resistivity of ZnO Thin Films for Photovoltaic Applications Using Photoluminescence Technique

This work projects photoluminescence (PL) as an alternative technique to estimate the order of resistivity of zinc oxide (ZnO) thin films. ZnO thin films, deposited using chemical spray pyrolysis (CSP) by varying the deposition parameters like solvent, spray rate, pH of precursor, and so forth, have been used for this study. Variation in the deposition conditions has tremendous impact on the luminescence properties as well as resistivity. Two emissions could be recorded for all samples—the near band edge emission (NBE) at 380 nm and the deep level emission (DLE) at ∼500 nm which are competing in nature. It is observed that the ratio of intensities of DLE to NBE ( DLE/ NBE) can be reduced by controlling oxygen incorporation in the sample. - measurements indicate that restricting oxygen incorporation reduces resistivity considerably. Variation of DLE/ NBE and resistivity for samples prepared under different deposition conditions is similar in nature. DLE/ NBE was always less than resistivity by an order for all samples.Thus from PL measurements alone, the order of resistivity of the samples can be estimated.

A STUDY OF THE TECHNIQUE OF THE HINDI DRAMA POST PRASAD PERIOD (1935 - 1965)

Hindi

THE PDETICAL WORKS DF GIRI-IA KUMAR MATHUR: SENSIBILITY AND TECHNIQUE

HINDI

Synthesis, Characterization and Applications of Hybrid Nanocomposites of TiO2 With Conducting Polymers

A nanocomposite is a multiphase solid material where one of the phases has one, two or three dimensions of less than 100 nanometers (nm), or structures having nano-scale repeat distances between the different phases that make up the material. In the broadest sense this definition can include porous media, colloids, gels and copolymers, but is more usually taken to mean the solid combination of a bulk matrix and nano-dimensional phase(s) differing in properties due to dissimilarities in structure and chemistry. The mechanical, electrical, thermal, optical, electrochemical, catalytic properties of the nanocomposite will differ markedly from that of the component materials. Size limits for these effects have been proposed, <5 nm for catalytic activity, <20 nm for making a hard magnetic material soft, <50 nm for refractive index changes, and <100 nm for achieving superparamagnetism, mechanical strengthening or restricting matrix dislocation movement. Conducting polymers have attracted much attention due to high electrical conductivity, ease of preparation, good environmental stability and wide variety of applications in light-emitting, biosensor chemical sensor, separation membrane and electronic devices. The most widely studied conducting polymers are polypyrrole, polyaniline, polythiophene etc. Conducting polymers provide tremendous scope for tuning of their electrical conductivity from semiconducting to metallic region by way of doping and are organic electro chromic materials with chemically active surface. But they are chemically very sensitive and have poor mechanical properties and thus possessing a processibility problem. Nanomaterial shows the presence of more sites for surface reactivity, they possess good mechanical properties and good dispersant too. Thus nanocomposites formed by combining conducting polymers and inorganic oxide nanoparticles possess the good properties of both the constituents and thus enhanced their utility. The properties of such type of nanocomposite are strongly depending on concentration of nanomaterials to be added. Conducting polymer composites is some suitable composition of a conducting polymer with one or more inorganic nanoparticles so that their desirable properties are combined successfully. The composites of core shell metal oxide particles-conducting polymer combine the electrical properties of the polymer shell and the magnetic, optical, electrical or catalytic characteristics of the metal oxide core, which could greatly widen their applicability in the fields of catalysis, electronics and optics. Moreover nanocomposite material composed of conducting polymers & oxides have open more field of application such as drug delivery, conductive paints, rechargeable batteries, toners in photocopying, smart windows, etc.The present work is mainly focussed on the synthesis, characterization and various application studies of conducting polymer modified TiO2 nanocomposites. The conclusions of the present work are outlined below, Mesoporous TiO2 was prepared by the cationic surfactant P123 assisted hydrothermal synthesis route and conducting polymer modified TiO2 nanocomposites were also prepared via the same technique. All the prepared systems show XRD pattern corresponding to anatase phase of TiO2, which means that there is no phase change occurring even after conducting polymer modification. Raman spectroscopy gives supporting evidence for the XRD results. It also confirms the incorporation of the polymer. The mesoporous nature and surface area of the prepared samples were analysed by N2 adsorption desorption studies and the mesoporous ordering can be confirmed by low angle XRD measurementThe morphology of the prepared samples was obtained from both SEM & TEM. The elemental analysis of the samples was performed by EDX analysisThe hybrid composite formation is confirmed by FT-IR spectroscopy and X-ray photoelectron spectroscopyAll the prepared samples have been used for the photocatalytic degradation of dyes, antibiotic, endocrine disruptors and some other organic pollutants. Photocatalytic antibacterial activity studies were also performed using the prepared systemsAll the prepared samples have been used for the photocatalytic degradation of dyes, antibiotic, endocrine disruptors and some other organic pollutants. Photocatalytic antibacterial activity studies were also performed using the prepared systems Polyaniline modified TiO2 nanocomposite systems were found to have good antibacterial activity. Thermal diffusivity studies of the polyaniline modified systems were carried out using thermal lens technique. It is observed that as the amount of polyaniline in the composite increases the thermal diffusivity also increases. The prepared systems can be used as an excellent coolant in various industrial purposes. Nonlinear optical properties (3rd order nonlinearity) of the polyaniline modified systems were studied using Z scan technique. The prepared materials can be used for optical limiting Applications. Lasing studies of polyaniline modified TiO2 systems were carried out and the studies reveal that TiO2 - Polyaniline composite is a potential dye laser gain medium.

Soft Computing Approach for Optimization of siRNA Efficiency Prediction for Post-transcriptional Gene Silencing

Post-transcriptional gene silencing by RNA interference is mediated by small interfering RNA called siRNA. This gene silencing mechanism can be exploited therapeutically to a wide variety of disease-associated targets, especially in AIDS, neurodegenerative diseases, cholesterol and cancer on mice with the hope of extending these approaches to treat humans. Over the recent past, a significant amount of work has been undertaken to understand the gene silencing mediated by exogenous siRNA. The design of efficient exogenous siRNA sequences is challenging because of many issues related to siRNA. While designing efficient siRNA, target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. So before doing gene silencing by siRNAs, it is essential to analyze their off-target effects in addition to their inhibition efficiency against a particular target. Hence designing exogenous siRNA with good knock-down efficiency and target specificity is an area of concern to be addressed. Some methods have been developed already by considering both inhibition efficiency and off-target possibility of siRNA against agene. Out of these methods, only a few have achieved good inhibition efficiency, specificity and sensitivity. The main focus of this thesis is to develop computational methods to optimize the efficiency of siRNA in terms of “inhibition capacity and off-target possibility” against target mRNAs with improved efficacy, which may be useful in the area of gene silencing and drug design for tumor development. This study aims to investigate the currently available siRNA prediction approaches and to devise a better computational approach to tackle the problem of siRNA efficacy by inhibition capacity and off-target possibility. The strength and limitations of the available approaches are investigated and taken into consideration for making improved solution. Thus the approaches proposed in this study extend some of the good scoring previous state of the art techniques by incorporating machine learning and statistical approaches and thermodynamic features like whole stacking energy to improve the prediction accuracy, inhibition efficiency, sensitivity and specificity. Here, we propose one Support Vector Machine (SVM) model, and two Artificial Neural Network (ANN) models for siRNA efficiency prediction. In SVM model, the classification property is used to classify whether the siRNA is efficient or inefficient in silencing a target gene. The first ANNmodel, named siRNA Designer, is used for optimizing the inhibition efficiency of siRNA against target genes. The second ANN model, named Optimized siRNA Designer, OpsiD, produces efficient siRNAs with high inhibition efficiency to degrade target genes with improved sensitivity-specificity, and identifies the off-target knockdown possibility of siRNA against non-target genes. The models are trained and tested against a large data set of siRNA sequences. The validations are conducted using Pearson Correlation Coefficient, Mathews Correlation Coefficient, Receiver Operating Characteristic analysis, Accuracy of prediction, Sensitivity and Specificity. It is found that the approach, OpsiD, is capable of predicting the inhibition capacity of siRNA against a target mRNA with improved results over the state of the art techniques. Also we are able to understand the influence of whole stacking energy on efficiency of siRNA. The model is further improved by including the ability to identify the “off-target possibility” of predicted siRNA on non-target genes. Thus the proposed model, OpsiD, can predict optimized siRNA by considering both “inhibition efficiency on target genes and off-target possibility on non-target genes”, with improved inhibition efficiency, specificity and sensitivity. Since we have taken efforts to optimize the siRNA efficacy in terms of “inhibition efficiency and offtarget possibility”, we hope that the risk of “off-target effect” while doing gene silencing in various bioinformatics fields can be overcome to a great extent. These findings may provide new insights into cancer diagnosis, prognosis and therapy by gene silencing. The approach may be found useful for designing exogenous siRNA for therapeutic applications and gene silencing techniques in different areas of bioinformatics.