Spray Pyrolysed Tin Chalcogenide Thin Films: Optimization of optoelectronic properties of SnS for possible photovoltaic application as an absorber layer

In the early 19th century, industrial revolution was fuelled mainly by the development of machine based manufacturing and the increased use of coal. Later on, the focal point shifted to oil, thanks to the mass-production technology, ease of transport/storage and also the (less) environmental issues in comparison with the coal!! By the dawn of 21st century, due to the depletion of oil reserves and pollution resulting from heavy usage of oil the demand for clean energy was on the rising edge. This ever growing demand has propelled research on photovoltaics which has emerged successful and is currently being looked up to as the only solace for meeting our present day energy requirements. The proven PV technology on commercial scale is based on silicon but the recent boom in the demand for photovoltaic modules has in turn created a shortage in supply of silicon. Also the technology is still not accessible to common man. This has onset the research and development work on moderately efficient, eco-friendly and low cost photovoltaic devices (solar cells). Thin film photovoltaic modules have made a breakthrough entry in the PV market on these grounds. Thin films have the potential to revolutionize the present cost structure of solar cells by eliminating the use of the expensive silicon wafers that alone accounts for above 50% of total module manufacturing cost.Well developed thin film photovoltaic technologies are based on amorphous silicon, CdTe and CuInSe2. However the cell fabrication process using amorphous silicon requires handling of very toxic gases (like phosphene, silane and borane) and costly technologies for cell fabrication. In the case of other materials too, there are difficulties like maintaining stoichiometry (especially in large area films), alleged environmental hazards and high cost of indium. Hence there is an urgent need for the development of materials that are easy to prepare, eco-friendly and available in abundance. The work presented in this thesis is an attempt towards the development of a cost-effective, eco-friendly material for thin film solar cells using simple economically viable technique. Sn-based window and absorber layers deposited using Chemical Spray Pyrolysis (CSP) technique have been chosen for the purpose

Discrete commutative difference operator theory

The object of this thesis is to formulate a basic commutative difference operator theory for functions defined on a basic sequence, and a bibasic commutative difference operator theory for functions defined on a bibasic sequence of points, which can be applied to the solution of basic and bibasic difference equations. in this thesis a brief survey of the work done in this field in the classical case, as well as a review of the development of q~difference equations, q—analytic function theory, bibasic analytic function theory, bianalytic function theory, discrete pseudoanalytic function theory and finally a summary of results of this thesis

Some problems of discrete function theory

An attempt is made by the researcher to establish a theory of discrete functions in the complex plane. Classical analysis q-basic theory, monodiffric theory, preholomorphic theory and q-analytic theory have been utilised to develop concepts like differentiation, integration and special functions.

Studies in the geometry of the discrete plane

This thesis is an attempt to initiate the development of a discrete geometry of the discrete plane H = {(qmxo,qnyo); m,n e Z - the set of integers}, where q s (0,1) is fixed and (xO,yO) is a fixed point in the first quadrant of the complex plane, xo,y0 ¢ 0. The discrete plane was first considered by Harman in 1972, to evolve a discrete analytic function theory for geometric difference functions. We shall mention briefly, through various sections, the principle of discretization, an outline of discrete a alytic function theory, the concept of geometry of space and also summary of work done in this thesis

Analysis discrete function theory

There is a recent trend to describe physical phenomena without the use of infinitesimals or infinites. This has been accomplished replacing differential calculus by the finite difference theory. Discrete function theory was first introduced in l94l. This theory is concerned with a study of functions defined on a discrete set of points in the complex plane. The theory was extensively developed for functions defined on a Gaussian lattice. In 1972 a very suitable lattice H: {Ci qmxO,I qnyo), X0) 0, X3) 0, O < q < l, m, n 5 Z} was found and discrete analytic function theory was developed. Very recently some work has been done in discrete monodiffric function theory for functions defined on H. The theory of pseudoanalytic functions is a generalisation of the theory of analytic functions. When the generator becomes the identity, ie., (l, i) the theory of pseudoanalytic functions reduces to the theory of analytic functions. Theugh the theory of pseudoanalytic functions plays an important role in analysis, no discrete theory is available in literature. This thesis is an attempt in that direction. A discrete pseudoanalytic theory is derived for functions defined on H.

Some bivariate life time models in discrete time"

The term reliability of an equipment or device is often meant to indicate the probability that it carries out the functions expected of it adequately or without failure and within specified performance limits at a given age for a desired mission time when put to use under the designated application and operating environmental stress. A broad classification of the approaches employed in relation to reliability studies can be made as probabilistic and deterministic, where the main interest in the former is to device tools and methods to identify the random mechanism governing the failure process through a proper statistical frame work, while the latter addresses the question of finding the causes of failure and steps to reduce individual failures thereby enhancing reliability. In the probabilistic attitude to which the present study subscribes to, the concept of life distribution, a mathematical idealisation that describes the failure times, is fundamental and a basic question a reliability analyst has to settle is the form of the life distribution. It is for no other reason that a major share of the literature on the mathematical theory of reliability is focussed on methods of arriving at reasonable models of failure times and in showing the failure patterns that induce such models. The application of the methodology of life time distributions is not confined to the assesment of endurance of equipments and systems only, but ranges over a wide variety of scientific investigations where the word life time may not refer to the length of life in the literal sense, but can be concieved in its most general form as a non-negative random variable. Thus the tools developed in connection with modelling life time data have found applications in other areas of research such as actuarial science, engineering, biomedical sciences, economics, extreme value theory etc.

Optimization of carbon and nitrogen sources and growth factors for the production of an aquaculture probiotic (Pseudomonas MCCB 103) using response surface methodology

Aim: To develop a new medium for enhanced production of biomass of an aquaculture probiotic Pseudomonas MCCB 103 and its antagonistic phenazine compound, pyocyanin. Methods and Results: Carbon and nitrogen sources and growth factors, such as amino acids and vitamins, were screened initially in a mineral medium for the biomass and antagonistic compound of Pseudomonas MCCB 103. The selected ingredients were further optimized using a full-factorial central composite design of the response surface methodology. The medium optimized as per the model for biomass contained mannitol (20 g l)1), glycerol (20 g l)1), sodium chloride (5 g l)1), urea (3Æ3 g l)1) and mineral salts solution (20 ml l)1), and the one optimized for the antagonistic compound contained mannitol (2 g l)1), glycerol (20 g l)1), sodium chloride (5Æ1 g l)1), urea (3Æ6 g l)1) and mineral salts solution (20 ml l)1). Subsequently, the model was validated experimentally with a biomass increase by 19% and fivefold increase of the antagonistic compound. Conclusion: Significant increase in the biomass and antagonistic compound production could be obtained in the new media. Significance and Impact of the Study: Media formulation and optimization are the primary steps involved in bioprocess technology, an attempt not made so far in the production of aquaculture probiotics

Optimization of medium for the production of a novel aquaculture probiotic, Micrococcus MCCB 104 using central composite design

A marine isolate of jáÅêçÅçÅÅìë MCCB 104 has been identified as an aquaculture probiotic antagonistic to sáÄêáç. In the present study different carbon and nitrogen sources and growth factors in a mineral base medium were optimized for enhanced biomass production and antagonistic activity against the target pathogen, sáÄêáç=Ü~êîÉóá, following response surface methodology (RSM). Accordingly the minimum and maximum limits of the selected variables were determined and a set of fifty experiments programmed employing central composite design (CCD) of RSM for the final optimization. The response surface plots of biomass showed similar pattern with that of antagonistic activity, which indicated a strong correlation between the biomass and antagonism. The optimum concentration of the carbon sources, nitrogen sources, and growth factors for both biomass and antagonistic activity were glucose (17.4 g/L), lactose (17 g/L), sodium chloride (16.9 g/L), ammonium chloride (3.3 g/L), and mineral salts solution (18.3 mL/L). © KSBB

A Numerically efficient power optimization scheme for coded OFDM systems in achieving minimum frame error rate

Coded OFDM is a transmission technique that is used in many practical communication systems. In a coded OFDM system, source data are coded, interleaved and multiplexed for transmission over many frequency sub-channels. In a conventional coded OFDM system, the transmission power of each subcarrier is the same regardless of the channel condition. However, some subcarrier can suffer deep fading with multi-paths and the power allocated to the faded subcarrier is likely to be wasted. In this paper, we compute the FER and BER bounds of a coded OFDM system given as convex functions for a given channel coder, inter-leaver and channel response. The power optimization is shown to be a convex optimization problem that can be solved numerically with great efficiency. With the proposed power optimization scheme, near-optimum power allocation for a given coded OFDM system and channel response to minimize FER or BER under a constant transmission power constraint is obtained

Parallel Genetic Algorithm for Document Image Compression Optimization

This work proposes a parallel genetic algorithm for compressing scanned document images. A fitness function is designed with Hausdorff distance which determines the terminating condition. The algorithm helps to locate the text lines. A greater compression ratio has achieved with lesser distortion

Short-Term Load Forecast Of A Low Loadfactor Power System For Optimization Of Merit Order Dispatch Using Adaptive Learning Algorithm

Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year

GA-based Optimization of a Fourth-order Sigma-delta Modulator for WLAN

Over-sampling sigma-delta analogue-to-digital converters (ADCs) are one of the key building blocks of state of the art wireless transceivers. In the sigma-delta modulator design the scaling coefficients determine the overall signal-to-noise ratio. Therefore, selecting the optimum value of the coefficient is very important. To this end, this paper addresses the design of a fourthorder multi-bit sigma-delta modulator for Wireless Local Area Networks (WLAN) receiver with feed-forward path and the optimum coefficients are selected using genetic algorithm (GA)- based search method. In particular, the proposed converter makes use of low-distortion swing suppression SDM architecture which is highly suitable for low oversampling ratios to attain high linearity over a wide bandwidth. The focus of this paper is the identification of the best coefficients suitable for the proposed topology as well as the optimization of a set of system parameters in order to achieve the desired signal-to-noise ratio. GA-based search engine is a stochastic search method which can find the optimum solution within the given constraints.

Discrete wavelet transform de-noising in eukaryotic gene splicing

This paper compares the most common digital signal processing methods of exon prediction in eukaryotes, and also proposes a technique for noise suppression in exon prediction. The specimen used here which has relevance in medical research, has been taken from the public genomic database - GenBank.Here exon prediction has been done using the digital signal processing methods viz. binary method, EIIP (electron-ion interaction psuedopotential) method and filter methods. Under filter method two filter designs, and two approaches using these two designs have been tried. The discrete wavelet transform has been used for de-noising of the exon plots.Results of exon prediction based on the methods mentioned above, which give values closest to the ones found in the NCBI database are given here. The exon plot de-noised using discrete wavelet transform is also given.Alterations to the proven methods as done by the authors, improves performance of exon prediction algorithms. Also it has been proven that the discrete wavelet transform is an effective tool for de-noising which can be used with exon prediction algorithms

Optimization of parameters of chemical spray pyrolysis technique to get n and p-type layers of SnS

SnS thin films were prepared using automated chemical spray pyrolysis (CSP) technique. Single-phase, p-type, stoichiometric, SnS films with direct band gap of 1.33 eV and having very high absorption coefficient (N105/cm) were deposited at substrate temperature of 375 °C. The role of substrate temperature in determining the optoelectronic and structural properties of SnS films was established and concentration ratios of anionic and cationic precursor solutions were optimized. n-type SnS samples were also prepared using CSP technique at the same substrate temperature of 375 °C, which facilitates sequential deposition of SnS homojunction. A comprehensive analysis of both types of films was done using x-ray diffraction, energy dispersive x-ray analysis, scanning electron microscopy, atomic force microscopy, optical absorption and electrical measurements. Deposition temperatures required for growth of other binary sulfide phases of tin such as SnS2, Sn2S3 were also determined

Optimization of Lignin Peroxidase, Manganese Peroxidase, and Lac Production from Ganoderma lucidum Under Solid State Fermentation of Pineapple Leaf

This study was undertaken to isolate ligninase-producing white-rot fungi for use in the extraction of fibre from pineapple leaf agriwaste. Fifteen fungal strains were isolated from dead tree trunks and leaf litter. Ligninolytic enzymes (lignin peroxidase (LiP), manganese peroxidase (MnP), and laccase (Lac)), were produced by solid-state fermentation (SSF) using pineapple leaves as the substrate. Of the isolated strains, the one showing maximum production of ligninolytic enzymes was identified to be Ganoderma lucidum by 18S ribotyping. Single parameter optimization and response surface methodology of different process variables were carried out for enzyme production. Incubation period, agitation, and Tween-80 were identified to be the most significant variables through Plackett-Burman design. These variables were further optimized by Box-Behnken design. The overall maximum yield of ligninolytic enzymes was achieved by experimental analysis under these optimal conditions. Quantitative lignin analysis of pineapple leaves by Klason lignin method showed significant degradation of lignin by Ganoderma lucidum under SSF