11 resultados para Non-coherent spectral efficiency
em Cochin University of Science
Resumo:
The increasing interest in the interaction of light with electricity and electronically active materials made the materials and techniques for producing semitransparent electrically conducting films particularly attractive. Transparent conductors have found major applications in a number of electronic and optoelectronic devices including resistors, transparent heating elements, antistatic and electromagnetic shield coatings, transparent electrode for solar cells, antireflection coatings, heat reflecting mirrors in glass windows and many other. Tin doped indium oxide (indium tin oxide or ITO) is one of the most commonly used transparent conducting oxides. At present and likely well into the future this material offers best available performance in terms of conductivity and transmittivity combined with excellent environmental stability, reproducibility and good surface morphology. Although partial transparency, with a reduction in conductivity, can be obtained for very thin metallic films, high transparency and simultaneously high conductivity cannot be attained in intrinsic stoichiometric materials. The only way this can be achieved is by creating electron degeneracy in a wide bandgap (Eg > 3eV or more for visible radiation) material by controllably introducing non-stoichiometry and/or appropriate dopants. These conditions can be conveniently met for ITO as well as a number of other materials like Zinc oxide, Cadmium oxide etc. ITO shows interesting and technologically important combination of properties viz high luminous transmittance, high IR reflectance, good electrical conductivity, excellent substrate adherence and chemical inertness. ITO is a key part of solar cells, window coatings, energy efficient buildings, and flat panel displays. In solar cells, ITO can be the transparent, conducting top layer that lets light into the cell to shine the junction and lets electricity flow out. Improving the ITO layer can help improve the solar cell efficiency. A transparent ii conducting oxide is a material with high transparency in a derived part of the spectrum and high electrical conductivity. Beyond these key properties of transparent conducting oxides (TCOs), ITO has a number of other key characteristics. The structure of ITO can be amorphous, crystalline, or mixed, depending on the deposition temperature and atmosphere. The electro-optical properties are a function of the crystallinity of the material. In general, ITO deposited at room temperature is amorphous, and ITO deposited at higher temperatures is crystalline. Depositing at high temperatures is more expensive than at room temperature, and this method may not be compatible with the underlying devices. The main objective of this thesis work is to optimise the growth conditions of Indium tin oxide thin films at low processing temperatures. The films are prepared by radio frequency magnetron sputtering under various deposition conditions. The films are also deposited on to flexible substrates by employing bias sputtering technique. The films thus grown were characterised using different tools. A powder x-ray diffractometer was used to analyse the crystalline nature of the films. The energy dispersive x-ray analysis (EDX) and scanning electron microscopy (SEM) were used for evaluating the composition and morphology of the films. Optical properties were investigated using the UVVIS- NIR spectrophotometer by recording the transmission/absorption spectra. The electrical properties were studied using vander Pauw four probe technique. The plasma generated during the sputtering of the ITO target was analysed using Langmuir probe and optical emission spectral studies.
Resumo:
The Schiff base, 3-hydroxyquinoxaline-2-carboxalidine-4-aminoantipyrine, was synthesized by the condensation of 3-hydroxyquinoxaline-2-carboxaldehyde with 4-aminoantipyrine. HPLC, FT-IR and NMR spectral data revealed that the compound exists predominantly in the amide tautomeric form and exhibits both absorption and fluorescence solvatochromism, large stokes shift, two electron quasireversible redox behaviour and good thermal stability, with a glass transition temperature of 104oC. The third-order non-linear optical character was studied using open aperture Z-scan methodology employing 7 ns pulses at 532 nm. The third-order non-linear absorption coefficient, b, was 1.48 x 10-6 cm W-1 and the imaginary part of the third-order non-linear optical susceptibility, Im c(3), was 3.36 x10-10 esu. The optical limiting threshold for the compound was found to be 340 MW cm-2.
Resumo:
The Schiff base, 3-hydroxyquinoxaline-2-carboxalidine-4-aminoantipyrine, was synthesized by the condensation of 3-hydroxyquinoxaline-2-carboxaldehyde with 4-aminoantipyrine. HPLC, FT-IR and NMR spectral data revealed that the compound exists predominantly in the amide tautomeric form and exhibits both absorption and fluorescence solvatochromism, large stokes shift, two electron quasireversible redox behaviour and good thermal stability, with a glass transition temperature of 104 oC. The third-order non-linear optical character was studied using open aperture Z-scan methodology employing 7 ns pulses at 532 nm. The third-order non-linear absorption coefficient, b, was 1.48 x 10-6 cm W-1 and the imaginary part of the third-order non-linear optical susceptibility, Im c(3), was 3.36x10-10 esu. The optical limiting threshold for the compound was found to be 340 MW cm-2.
Resumo:
Non-destructive testing (NDT) is the use of non-invasive techniques to determine the integrity of a material, component, or structure. Engineers and scientists use NDT in a variety of applications, including medical imaging, materials analysis, and process control.Photothermal beam deflection technique is one of the most promising NDT technologies. Tremendous R&D effort has been made for improving the efficiency and simplicity of this technique. It is a popular technique because it can probe surfaces irrespective of the size of the sample and its surroundings. This technique has been used to characterize several semiconductor materials, because of its non-destructive and non-contact evaluation strategy. Its application further extends to analysis of wide variety of materials. Instrumentation of a NDT technique is very crucial for any material analysis. Chapter two explores the various excitation sources, source modulation techniques, detection and signal processing schemes currently practised. The features of the experimental arrangement including the steps for alignment, automation, data acquisition and data analysis are explained giving due importance to details.Theoretical studies form the backbone of photothermal techniques. The outcome of a theoretical work is the foundation of an application.The reliability of the theoretical model developed and used is proven from the studies done on crystalline.The technique is applied for analysis of transport properties such as thermal diffusivity, mobility, surface recombination velocity and minority carrier life time of the material and thermal imaging of solar cell absorber layer materials like CuInS2, CuInSe2 and SnS thin films.analysis of In2S3 thin films, which are used as buffer layer material in solar cells. The various influences of film composition, chlorine and silver incorporation in this material is brought out from the measurement of transport properties and analysis of sub band gap levels.The application of photothermal deflection technique for characterization of solar cells is a relatively new area that requires considerable attention.The application of photothermal deflection technique for characterization of solar cells is a relatively new area that requires considerable attention. Chapter six thus elucidates the theoretical aspects of application of photothermal techniques for solar cell analysis. The experimental design and method for determination of solar cell efficiency, optimum load resistance and series resistance with results from the analysis of CuInS2/In2S3 based solar cell forms the skeleton of this chapter.
Resumo:
In this Letter we present the spectral and nonlinear optical properties of ZnO–Ag nanocomposites prepared by colloidal chemical synthesis. Obvious enhancement of ultraviolet (UV) emission of the samples is observed and the strongest UV emission is over three times than that of pure ZnO. These nanocomposites show self-defocusing nonlinearity and good nonlinear absorption behaviour which increases with increasing Ag volume fraction. The observed nonlinear absorption is explained through two photon absorption followed by free carrier absorption. ZnO–Ag is a potential nanocomposite material for the UV light emission and for the development of nonlinear optical devices with a relatively small limiting threshold.
Resumo:
The present work deals with the complexation of Schiff bases of aroylhydrazines with various transition metal ions. The hydrazone systems selected for study have long 7I:-delocalized chain in the ligand molecule itself, which get intensified due to metal-to-ligand or ligand-to-metal charge transfer excitations upon coordination. Complexation with metal ions like copper, nickel, cobalt, manganese, iron, zinc and cadmium are tried. Various spectral techniques are employed for characterization. The structures of some complexes have been well established by single crystal X-ray diffraction studies. The nonIinaer optical studies of the ligands and complexes synthesized have been studied by hyper-Rayleigh scattering technique.The work is presented in seven chapters and the last one deals with summary and conclusion. One of the hydrazone system selected for study proved that it could give rise to polymeric metal complexes. Some of the copper, nickel, zinc and cadmium complexes showed non-linear optical activity. The NLO studies of manganese and iron showed negative result, may be due to the inversion centre of symmetry within the molecular lattice.
Resumo:
This study is concerned with Autoregressive Moving Average (ARMA) models of time series. ARMA models form a subclass of the class of general linear models which represents stationary time series, a phenomenon encountered most often in practice by engineers, scientists and economists. It is always desirable to employ models which use parameters parsimoniously. Parsimony will be achieved by ARMA models because it has only finite number of parameters. Even though the discussion is primarily concerned with stationary time series, later we will take up the case of homogeneous non stationary time series which can be transformed to stationary time series. Time series models, obtained with the help of the present and past data is used for forecasting future values. Physical science as well as social science take benefits of forecasting models. The role of forecasting cuts across all fields of management-—finance, marketing, production, business economics, as also in signal process, communication engineering, chemical processes, electronics etc. This high applicability of time series is the motivation to this study.
Resumo:
Supra molecular architectures of coordination complexes of liydrazones through non covalent interactions have been explored. Molecular self—assernbly driven by weak interactions such as hydrogen— bonding, K '”T[, C-1-I‘ "TE, van der Waals interactions, and so forth are currently of tremendous research interest in the fields of molecule based materials. The directional properties of the hydrogembonding interaction associate discrete molecules into aggregate structures that are sufficiently stable to be considered as independent chemical species. Chemistry can borrow nature’s strategy to utilize hydrogen-bonding as Well as other noncovalent interactions as found in secondary and tertiary structures of proteins such as the double helix folding of DNA, hydrophobic selflorganization of phospholipids in cell membrane etc. In supramolecular chemistry hydrogen bonding plays an important role in forming a variety of architectures. Thus, the wise modulation and tuning of the complementary sites responsible for hydrogen—bond formation have led to its application in supramolecular electronics, host-guest chemistry, self-assembly of molecular capsules, nanotubes etc. The work presented in this thesis describes the synthesis and characterization of metal complexes derived from some substituted aroylhydrazones. The thesis is divided into seven chapters.
Resumo:
Five Mn(II) complexes of bis(thiosemicarbazones) which are represented as [Mn(H2Ac4Ph)Cl2] (1), [Mn(Ac4Ph)H2O] (2), [Mn(H2Ac4Cy)Cl2]·H2O (3), [Mn(H2Ac4Et)Cl2]·3H2O (4) and [Mn(H2Ac4Et)(OAc)2]·3H2O (5) have been synthesized and characterized by elemental analyses, electronic, infrared and EPR spectral techniques. In all the complexes except [Mn(Ac4Ph)H2O], the ligands act as pentadentate neutral molecules and coordinate to Mn(II) ion through two thione sulfur atoms, two azomethine nitrogens and the pyridine nitrogen, suggesting a heptacoordination. While in compound [Mn(Ac4Ph)H2O], the dianionic ligand is coordinated to the metal suggesting six coordination in this case. Magnetic studies indicate the high spin state of Mn(II). Conductivity measurements reveal their non-electrolyte nature. EPR studies indicate five g values for [Mn(Ac4Ph)H2O] showing zero field splitting.
Resumo:
A spectral angle based feature extraction method, Spectral Clustering Independent Component Analysis (SC-ICA), is proposed in this work to improve the brain tissue classification from Magnetic Resonance Images (MRI). SC-ICA provides equal priority to global and local features; thereby it tries to resolve the inefficiency of conventional approaches in abnormal tissue extraction. First, input multispectral MRI is divided into different clusters by a spectral distance based clustering. Then, Independent Component Analysis (ICA) is applied on the clustered data, in conjunction with Support Vector Machines (SVM) for brain tissue analysis. Normal and abnormal datasets, consisting of real and synthetic T1-weighted, T2-weighted and proton density/fluid-attenuated inversion recovery images, were used to evaluate the performance of the new method. Comparative analysis with ICA based SVM and other conventional classifiers established the stability and efficiency of SC-ICA based classification, especially in reproduction of small abnormalities. Clinical abnormal case analysis demonstrated it through the highest Tanimoto Index/accuracy values, 0.75/98.8%, observed against ICA based SVM results, 0.17/96.1%, for reproduced lesions. Experimental results recommend the proposed method as a promising approach in clinical and pathological studies of brain diseases
Resumo:
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.