Development of selected electro-active polymer-ceramic nanocomposites as pyroelectric thermal/infrared detector materials

The present work emphasises on the synthesis and characterization of electro-active polymer-ceramic nanocomposites which can be used for pyroelectric thermal/infrared detection applications. Two sets of samples belong to polymer-microcrystalline composites have also been investigated in the work. The polymers used in the work have been commercially available ones, but the nanoceramics have been synthesized following simple chemical routes and aqueous organic gel routes. After characterizing the nanoceramics for their structure by powder XRD, they have been dispersed in liquid polymer and sonicated for uniform dispersion. The viscous mixture so formed was cast in the form of films for experimentation. Samples with volume fraction of the ceramic phase varied from 0 to 0.25 have been prepared. Solution growth was followed to prepare microcrystalline samples for the polymer-microcrystalline composites. The physical properties that determine the pyroelectric sensitivity of a material are dielectric constant, dielectric loss, pyroelectric coefficient, thermal conductivity and specific heat capacity. These parameters have been determined for all the samples and compositions reported in this work.The pyroelectric figures of merit for all the samples were determined. The pyroelectric figures of merit that determine the pyroelectric sensitivity of a material are current sensitivity, voltage responsivity and detectivity. All these have been determined for each set of samples and reported in the thesis. In order to assess the flexibility and mouldability of the composites we have measured the Shore hardness of each of the composites by indentation technique and compared with the pyroelectric figures of merit. Some important factors considered during the material fabrication stages were maximum flexibility and maximum figures of merit for pyroelectric thermal/IR detection applications. In order to achieve these goals, all the samples are synthesized as composites of polymers and nano/microcrystalline particles and are prepared in the form of freestanding films. The selected polymer matrices and particle inclusions possess good pyroelectric coefficients, low thermal and dielectric properties, so that good pyroelectric figures of merit could be achieved. The salient features of the work include the particle size of the selected ceramic materials. Since they are in nanometer size it was possible to achieve high flexibility and moldability with high figures of merit for even low volume fractions of inclusions of the prepared nanocrystalline composites. In the case of microcrystalline TGS and DTGS, their composites in PU matrix protect them from fragility and humidity susceptibility and made them for environmental friendly applications.

A multiple-building diffraction attenuation function expressed in terms of UTD coefficients for microcellular communications

This work presents an explicit formulation for multiple- edge diffraction for mobile radiowave propagation in terms of uniform theory of diffraction (UTD) coefficients when a spherical incident wave is considered. This solution can be used in an UTD context and sharply reduces the computing time over existing formulation. Results can be applied in the planning of microcellular systems

Thermal transport across incommensurate phases in potassium selenate: photo-pyroelectric and calorimetric measurements

The thermal transport properties—thermal diffusivity, thermal conductivity and specific heat capacity—of potassium selenate crystal have been measured through the successive phase transitions, following the photo-pyroelectric thermal wave technique. The variation of thermal conductivity with temperature through the incommensurate (IC) phase of this crystal is measured. The enhancement in thermal conductivity in the IC phase is explained in terms of heat conduction by phase modes, and the maxima in thermal conductivity during transitions is due to enhancement in the phonon mean free path and the corresponding reduction in phonon scattering. The anisotropy in thermal conductivity and its variation with temperature are reported. The variation of the specific heat with temperature through the high temperature structural transition at 745 K is measured, following the differential scanning calorimetric method. By combining the results of photo-pyroelectric thermal wave methods and differential scanning calorimetry, the variation of the specific heat capacity with temperature through all the four phases of K2SeO4 is reported. The results are discussed in terms of phonon mode softening during transitions and phonon scattering by phase modes in the IC phase.

Salting Coefficients of Fluorobenzoic Acids

The Setschenow parameter and thermodynamic parameters of transfer of 2-, 3- and 4-fluorobenzoic acid from water to salt solution are reported. The data have been rationalized by considering the structure breaking effects of the ions of the salts, the localized hydrolysis model and the internal pressure theory.

Salting Coefficients of 2-, 3-, and 4-Methylbenzoic Acids

The Setschenow parameter and thermodynamic parameters of transfer of 2-, 3-, and 4-methylbenzoic acids from water to salt solutions have been reported. The data have been rationalized by considering the structure breaking effects of the ions of the salts, the localized hydrolysis model, and the internal pressure theory.

An Improved Technique for Evolving Wavelet Coefficients for Fingerprint Image Compression

In this paper, an improved technique for evolving wavelet coefficients refined for compression and reconstruction of fingerprint images is presented. The FBI fingerprint compression standard [1, 2] uses the cdf 9/7 wavelet filter coefficients. Lifting scheme is an efficient way to represent classical wavelets with fewer filter coefficients [3, 4]. Here Genetic algorithm (GA) is used to evolve better lifting filter coefficients for cdf 9/7 wavelet to compress and reconstruct fingerprint images with better quality. Since the lifting filter coefficients are few in numbers compared to the corresponding classical wavelet filter coefficients, they are evolved at a faster rate using GA. A better reconstructed image quality in terms of Peak-Signal-to-Noise-Ratio (PSNR) is achieved with the best lifting filter coefficients evolved for a compression ratio 16:1. These evolved coefficients perform well for other compression ratios also.

Faster techniques to evolve wavelet coefficients for better fingerprint image compression

In this article, techniques have been presented for faster evolution of wavelet lifting coefficients for fingerprint image compression (FIC). In addition to increasing the computational speed by 81.35%, the coefficients performed much better than the reported coefficients in literature. Generally, full-size images are used for evolving wavelet coefficients, which is time consuming. To overcome this, in this work, wavelets were evolved with resized, cropped, resized-average and cropped-average images. On comparing the peak- signal-to-noise-ratios (PSNR) offered by the evolved wavelets, it was found that the cropped images excelled the resized images and is in par with the results reported till date. Wavelet lifting coefficients evolved from an average of four 256 256 centre-cropped images took less than 1/5th the evolution time reported in literature. It produced an improvement of 1.009 dB in average PSNR. Improvement in average PSNR was observed for other compression ratios (CR) and degraded images as well. The proposed technique gave better PSNR for various bit rates, with set partitioning in hierarchical trees (SPIHT) coder. These coefficients performed well with other fingerprint databases as well.

Evolution of Better Wavelet Coefficients for Fingerprint Image Compression using cropped images

This paper explains the Genetic Algorithm (GA) evolution of optimized wavelet that surpass the cdf9/7 wavelet for fingerprint compression and reconstruction. Optimized wavelets have already been evolved in previous works in the literature, but they are highly computationally complex and time consuming. Therefore, in this work, a simple approach is made to reduce the computational complexity of the evolution algorithm. A training image set comprised of three 32x32 size cropped images performed much better than the reported coefficients in literature. An average improvement of 1.0059 dB in PSNR above the classical cdf9/7 wavelet over the 80 fingerprint images was achieved. In addition, the computational speed was increased by 90.18 %. The evolved coefficients for compression ratio (CR) 16:1 yielded better average PSNR for other CRs also. Improvement in average PSNR was experienced for degraded and noisy images as well