27 resultados para Physics Based Modeling


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This thesis mainly deals with the preparation and studies on magnetic composites based on spinel ferrites prepared both chemically and mechanically. Rubber ferrite composites (RFC) are chosen because of their mouldability and flexibility and the ease with which the dielectric and magnetic properties can be manipulated to make them as useful devices. Natural rubber is chosen as the Matrix because of its local availability and possible value addition. Moreover, NR represents a typical unsaturated nonpolar matrix. The work can be thought of as two parts. Part l concentrates on the preparation and characterization of nanocomposites based on y-Fe203. Part 2 deals with the preparation and characterization of RFCs containing Nickel zinc ferrit In the present study magnetic nanocomposites have been prepared by ionexchange method and the preparation conditions have been optimized. The insitu incorporation of the magnetic component is carried out chemically. This method is selected as it is the easiest and simplest method for preparation of nanocomposite. Nanocomposite samples thus prepared were studied using VSM, Mossbauer spectroscopy, Iron content estimation, and ESR spectroscopy. For the preparation of RFCs, the filler material namely nickel zinc ferrite having the general formula Ni)_xZnxFez04, where x varies from 0 to 1 in steps of 0.2 have been prepared by the conventional ceramic techniques. The system of Nil_xZn"Fe204 is chosen because of their excellent high frequency characteristics. After characterization they are incorporated into the polymer matrix of natural rubber by mechanical method. The incorporation is done according to a specific recipe and for various Loadings of magnetic fillers and also for all compositions. The cure characteristics, magnetic properties and dielectric properties of these composites are evaluated. The ac electrical conductivity of both ceramic nickel zinc ferrites and rubber ferrite composites are also calculated using a simple relation. The results are correlated.

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Light emitting polymers (LEP) have drawn considerable attention because of their numerous potential applications in the field of optoelectronic devices. Till date, a large number of organic molecules and polymers have been designed and devices fabricated based on these materials. Optoelectronic devices like polymer light emitting diodes (PLED) have attracted wide-spread research attention owing to their superior properties like flexibility, lower operational power, colour tunability and possibility of obtaining large area coatings. PLEDs can be utilized for the fabrication of flat panel displays and as replacements for incandescent lamps. The internal efficiency of the LEDs mainly depends on the electroluminescent efficiency of the emissive polymer such as quantum efficiency, luminance-voltage profile of LED and the balanced injection of electrons and holes. Poly (p-phenylenevinylene) (PPV) and regio-regular polythiophenes are interesting electro-active polymers which exhibit good electrical conductivity, electroluminescent activity and high film-forming properties. A combination of Red, Green and Blue emitting polymers is necessary for the generation of white light which can replace the high energy consuming incandescent lamps. Most of these polymers show very low solubility, stability and poor mechanical properties. Many of these light emitting polymers are based on conjugated extended chains of alternating phenyl and vinyl units. The intra-chain or inter-chain interactions within these polymer chains can change the emitted colour. Therefore an effective way of synthesizing polymers with reduced π-stacking, high solubility, high thermal stability and high light-emitting efficiency is still a challenge for chemists. New copolymers have to be effectively designed so as to solve these issues. Hence, in the present work, the suitability of a few novel copolymers with very high thermal stability, excellent solubility, intense light emission (blue, cyan and green) and high glass transition temperatures have been investigated to be used as emissive layers for polymer light emitting diodes.

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Organic crystals possess extremely large optical nonlinearity compared to inorganic crystals. Also organic compounds have the amenability for synthesis and scope for introducing desirable characteristics by inclusions. A wide variety of organic materials having electron donor and acceptor groups, generate high order of nonlinearity. In the present work, a new nonlinear optical crystal, L-citrulline oxalate (LCO) based on the aminoacid L-citrulline was grown using slow evaporation technique. Structural characterization was carried out by single crystal XRD. It crystallizes in the noncentrosymmetric, orthorhombic structure with space group P21 P21 P21. Functional groups present in the sample were identified by Fourier transform infra red (FTIR) and FT-Raman spectral analysis. On studying the FTIR and Raman spectra of the precursors L-citrulline and oxalic acid, used for growing L-citrulline oxalate crystal, it is found that the significant peaks of the precursors are present in the spectra of the L-citrulline oxalate crystal . This observation along with the presence of NH3 + group in the spectra of L-citrulline oxalate, confirms the formation of the charge transfer complex

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The development of new materials has been the hall mark of human civilization. The quest for making new devices and new materials has prompted humanity to pursue new methods and techniques that eventually has given birth to modern science and technology. With the advent of nanoscience and nanotechnology, scientists are trying hard to tailor materials by varying their size and shape rather than playing with the composition of the material. This, along with the discovery of new and sophisticated imaging tools, has led to the discovery of several new classes of materials like (3D) Graphite, (2D) graphene, (1D) carbon nanotubes, (0D) fullerenes etc. Magnetic materials are in the forefront of applications and have beencontributing their share to remove obsolescence and bring in new devices based on magnetism and magnetic materials. They find applications in various devices such as electromagnets, read heads, sensors, antennas, lubricants etc. Ferromagnetic as well as ferrimagnetic materials have been in use in the form of various devices. Among the ferromagnetic materials iron, cobalt and nickel occupy an important position while various ferrites finds applications in devices ranging from magnetic cores to sensors.

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In the present study, nano particles of NiFe3O4, I_.l()5Feg5O4 and CoFegO4 are prepared by sol gel method. By appropriate heat treatments, particles of different grain sizes are obtained. The structural, magnetic and electrical measurements are evaluated as a function of grain size and temperature. NiFe3O4 prepared in the ultrafine regime are then incorporated in nitrile rubber matrix. The incorporation was carried out according to a specific recipe and for various loadings of magnetic fillers. The cure characteristics, magnetic properties, electrical properties and mechanical properties of these elastomer blends are carried out. The electrical permittivity of all the rubber samples in the X — band are also conducted

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Quantile functions are efficient and equivalent alternatives to distribution functions in modeling and analysis of statistical data (see Gilchrist, 2000; Nair and Sankaran, 2009). Motivated by this, in the present paper, we introduce a quantile based Shannon entropy function. We also introduce residual entropy function in the quantile setup and study its properties. Unlike the residual entropy function due to Ebrahimi (1996), the residual quantile entropy function determines the quantile density function uniquely through a simple relationship. The measure is used to define two nonparametric classes of distributions

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Partial moments are extensively used in literature for modeling and analysis of lifetime data. In this paper, we study properties of partial moments using quantile functions. The quantile based measure determines the underlying distribution uniquely. We then characterize certain lifetime quantile function models. The proposed measure provides alternate definitions for ageing criteria. Finally, we explore the utility of the measure to compare the characteristics of two lifetime distributions

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Thermally stable materials with low dielectric constant (k < 3.9) are being hotly pursued. They are essential as interlayer dielectrics/intermetal dielectrics in integrated circuit technology, which reduces parasitic capacitance and decreases the RC time constant. Most of the currently employed materials are based on silicon. Low k films based on organic polymers are supposed to be a viable alternative as they are easily processable and can be synthesized with simpler techniques. It is known that the employment of ac/rf plasma polymerization yields good quality organic thin films, which are homogenous, pinhole free and thermally stable. These polymer thin films are potential candidates for fabricating Schottky devices, storage batteries, LEDs, sensors, super capacitors and for EMI shielding. Recently, great efforts have been made in finding alternative methods to prepare low dielectric constant thin films in place of silicon-based materials. Polyaniline thin films were prepared by employing an rf plasma polymerization technique. Capacitance, dielectric loss, dielectric constant and ac conductivity were evaluated in the frequency range 100 Hz– 1 MHz. Capacitance and dielectric loss decrease with increase of frequency and increase with increase of temperature. This type of behaviour was found to be in good agreement with an existing model. The ac conductivity was calculated from the observed dielectric constant and is explained based on the Austin–Mott model for hopping conduction. These films exhibit low dielectric constant values, which are stable over a wide range of frequencies and are probable candidates for low k applications.

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Two-dimensional electronic systems play a crucial role in modern electronics and offer a multitude of opportunities to study the fundamental phenomena at low dimensional physics. A quantum well heterostructure based on polyaniline (P) and iodine doped polyaniline (I) thin films were fabricated using radio frequency plasma polymerization on indium tin oxide coated glass plate. Scanning probe microscopy and scanning electron microscopy studies were employed to study the morphology and roughness of the polymer thin films. Local electronic density of states (LDOS) of the P–I–P heterostructures is probed using scanning tunnelling spectroscopy (STS). A step like LDOS is observed in the P–I–P heterostructure and is attributed to the quantum well confinement of electrons in the polymer heterostructure.

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Modeling nonlinear systems using Volterra series is a century old method but practical realizations were hampered by inadequate hardware to handle the increased computational complexity stemming from its use. But interest is renewed recently, in designing and implementing filters which can model much of the polynomial nonlinearities inherent in practical systems. The key advantage in resorting to Volterra power series for this purpose is that nonlinear filters so designed can be made to work in parallel with the existing LTI systems, yielding improved performance. This paper describes the inclusion of a quadratic predictor (with nonlinearity order 2) with a linear predictor in an analog source coding system. Analog coding schemes generally ignore the source generation mechanisms but focuses on high fidelity reconstruction at the receiver. The widely used method of differential pnlse code modulation (DPCM) for speech transmission uses a linear predictor to estimate the next possible value of the input speech signal. But this linear system do not account for the inherent nonlinearities in speech signals arising out of multiple reflections in the vocal tract. So a quadratic predictor is designed and implemented in parallel with the linear predictor to yield improved mean square error performance. The augmented speech coder is tested on speech signals transmitted over an additive white gaussian noise (AWGN) channel.

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In this paper, a novel fast method for modeling mammograms by deterministic fractal coding approach to detect the presence of microcalcifications, which are early signs of breast cancer, is presented. The modeled mammogram obtained using fractal encoding method is visually similar to the original image containing microcalcifications, and therefore, when it is taken out from the original mammogram, the presence of microcalcifications can be enhanced. The limitation of fractal image modeling is the tremendous time required for encoding. In the present work, instead of searching for a matching domain in the entire domain pool of the image, three methods based on mean and variance, dynamic range of the image blocks, and mass center features are used. This reduced the encoding time by a factor of 3, 89, and 13, respectively, in the three methods with respect to the conventional fractal image coding method with quad tree partitioning. The mammograms obtained from The Mammographic Image Analysis Society database (ground truth available) gave a total detection score of 87.6%, 87.6%, 90.5%, and 87.6%, for the conventional and the proposed three methods, respectively.

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Software systems are progressively being deployed in many facets of human life. The implication of the failure of such systems, has an assorted impact on its customers. The fundamental aspect that supports a software system, is focus on quality. Reliability describes the ability of the system to function under specified environment for a specified period of time and is used to objectively measure the quality. Evaluation of reliability of a computing system involves computation of hardware and software reliability. Most of the earlier works were given focus on software reliability with no consideration for hardware parts or vice versa. However, a complete estimation of reliability of a computing system requires these two elements to be considered together, and thus demands a combined approach. The present work focuses on this and presents a model for evaluating the reliability of a computing system. The method involves identifying the failure data for hardware components, software components and building a model based on it, to predict the reliability. To develop such a model, focus is given to the systems based on Open Source Software, since there is an increasing trend towards its use and only a few studies were reported on the modeling and measurement of the reliability of such products. The present work includes a thorough study on the role of Free and Open Source Software, evaluation of reliability growth models, and is trying to present an integrated model for the prediction of reliability of a computational system. The developed model has been compared with existing models and its usefulness of is being discussed.