Development of Elastomeric Hybrid Composite Based on Synthesised Manosilica and Short Nylon Fiber

Nanoscale silica was synthesized by precipitation method using sodium silicate and dilute hydrochloric acid under controlled conditions. The synthesized silica was characterized by Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), BET adsorption and X-Ray Diffraction (XRD). The particle size of silica was calculated to be 13 nm from the XRD results and the surface area was found to be 295 m2/g by BET method. The performance of this synthesized nanosilica as a reinforcing filler in natural rubber (NR) compound was investigated. The commercial silica was used as the reference material. Nanosilica was found to be effective reinforcing filler in natural rubber compound. Filler-matrix interaction was better for nanosilica than the commercial silica. The synthesized nanosilica was used in place of conventional silica in HRH (hexamethylene tetramine, resorcinol and silica) bonding system for natural rubber and styrene butadiene rubber / Nylon 6 short fiber composites. The efficiency of HRH bonding system based on nanosilica was better. Nanosilica was also used as reinforcing filler in rubber / Nylon 6 short fiber hybrid composite. The cure, mechanical, ageing, thermal and dynamic mechanical properties of nanosilica / Nylon 6 short fiber / elastomeric hybrid composites were studied in detail. The matrices used were natural rubber (NR), nitrile rubber (NBR), styrene butadiene rubber (SBR) and chloroprene rubber (CR). Fiber loading was varied from 0 to 30 parts per hundred rubber (phr) and silica loading was varied from 0 to 9 phr. Hexa:Resorcinol:Silica (HRH) ratio was maintained as 2:2:1. HRH loading was adjusted to 16% of the fiber loading. Minimum torque, maximum torque and cure time increased with silica loading. Cure rate increased with fiber loading and decreased with silica content. The hybrid composites showed improved mechanical properties in the presence of nanosilica. Tensile strength showed a dip at 10 phr fiber loading in the case of NR and CR while it continuously increased with fiber loading in the case of NBR and SBR. The nanosilica improved the tensile strength, modulus and tear strength better than the conventional silica. Abrasion resistance and hardness were also better for the nanosilica composites. Resilience and compression set were adversely affected. Hybrid composites showed anisotropy in mechanical properties. Retention in ageing improved with fiber loading and was better for nanosilica-filled hybrid composites. The nanosilica also improved the thermal stability of the hybrid composite better than the commercial silica. All the composites underwent two-step thermal degradation. Kinetic studies showed that the degradation of all the elastomeric composites followed a first-order reaction. Dynamic mechanical analysis revealed that storage modulus (E’) and loss modulus (E”) increased with nanosiica content, fiber loading and frequency for all the composites, independent of the matrix. The highest rate of increase was registered for NBR rubber.

Polyaniline/Pillared Montmorillonite Clay Composite Nanofibers

In situ polymerization of aniline is done inside the pillared clay matrix. The nonswellable pillared clay confined matrix allows efficient polymerization that leads to nanofibrous morphology. As a result high polymer order and crystallinity is attained and is evident from XRD patterns. The strong interaction between the clay layers and polyaniline (PANI) is understood from FTIR and DRS spectra. Additionally these analytical results suggest that the prepared PANI is in the doped state. The PANI/pillared clay nanocomposite formation gives additional thermal stability to the polymer backbone and is clear from the DTG curves.

Investigations on the preparation of composite polysaccharide films and micro / nanoparticles for novel applications

chemical Sciences and Technology Division, National Institute for Interdisciplinary Science and Technology, CSIR

Biocompatibility Study Of Hydroxyapatite-Chitosan Composite For Medical Applications At Microwave Frequencies

Hydroxyapatite (HAp, Ca10(PO4)6(OH)2) bioceramic and chitosan (poly [( -1-4) D-glucosamine]) biopolymer show good biocompatibility in vivo. They have biological origin and show excellent interactions with microwave. Microwave study of HAp made using different drying techniques and their composites with chitosan in the ISM band is presented. Pastes are made using HAp and chitosan with different ratios of mixing. The dielectric properties of this composites match with that of human fat, collagen tissues. Some of the compositions exhibit dielectric property close to that of natural bone. This makes them more biocompatible and better substitutes for natural bone. Thus composite bioceramics can be considered as phantom model constituents for imaging purposes. Their dielectric properties prove that they are biocompatible.

Neural Network based studies on Spectroscopic Analysis and Image Processing

International School of Photonics, Cochin University of Science and Technology

Fabrication and Characterization of Chalcogenide nano composite based materials for Photonic device applications

In this context,in search of new materials based on chalcogenide glasses,we have developed a novel technique for fabrication of chalcogenide nano composites which are presented in this theis.The techniques includes the dissolution of bulk chalcogenide glasses in amine solvent.This solution casting method allows to retain the attractive optical properties of chalcogenide glasses enabling new fabrication routes for realization of large area thick-thin films with less cost. Chalcogenide glass fiber geometry opens new possibilities for a large number of applications in optics,like remote temperature measurements ,CO2 laser power delivery, and optical sensing and single mode propagation of IR light.We have fabricated new optical polymer fibers doped with chalcogenide glasses which can be used for many optical applications.The present thesis also describes the structural,thermal and optical characterization of certain chalocogenide based materials prepared for different methods and its applications.

Speech sample estimation from composite zerocrossings and encoding via adaptive switching of transforms

This thesis investigates the potential use of zerocrossing information for speech sample estimation. It provides 21 new method tn) estimate speech samples using composite zerocrossings. A simple linear interpolation technique is developed for this purpose. By using this method the A/D converter can be avoided in a speech coder. The newly proposed zerocrossing sampling theory is supported with results of computer simulations using real speech data. The thesis also presents two methods for voiced/ unvoiced classification. One of these methods is based on a distance measure which is a function of short time zerocrossing rate and short time energy of the signal. The other one is based on the attractor dimension and entropy of the signal. Among these two methods the first one is simple and reguires only very few computations compared to the other. This method is used imtea later chapter to design an enhanced Adaptive Transform Coder. The later part of the thesis addresses a few problems in Adaptive Transform Coding and presents an improved ATC. Transform coefficient with maximum amplitude is considered as ‘side information’. This. enables more accurate tfiiz assignment enui step—size computation. A new bit reassignment scheme is also introduced in this work. Finally, sum ATC which applies switching between luiscrete Cosine Transform and Discrete Walsh-Hadamard Transform for voiced and unvoiced speech segments respectively is presented. Simulation results are provided to show the improved performance of the coder

Development of a portable composite equipment for coastal fishery and hydrographic investigations

This thesis reports on the details of the works done to develop a complete system for acquisition of the important marine environmental parameters namely, current, current direction, salinity, temperature and depth. It encompaéps transducers,signalconditioners display arrangements and remote controlled multiplexer which constitue the system. The various associate instruentation and environmental requisites and problems have been discussed and solved to considerable extend. The design and development features of this composite system includes an integrated approach in order to make the final equipment to be simple, inexpensive and easy for operation from small and large boats. This could be achieved with the successful development of all required components with features matching between them, such as sensors, signals conditioners remote operated multiplexers, comon display methods, quick performance check and calibration methods. The major success rests on the development of sensors with excellent performance characteristics suitable for marine environment. out of the 5 sensors. that of current salinity and depth are quite noval types with specific advantages. The environmental effects have been eliminated to the required extend. The common signal conditioner for salinity, temperature and depth has noval design features for achieving simplicity, reliability and accomodating the three sensors of different functional requirements.

Investigations On The Development Of An Ann Model & Visual Manipulation Approach For 2-D Dft Computation In Image Processing

This thesis is an outcome of the investigations carried out on the development of an Artificial Neural Network (ANN) model to implement 2-D DFT at high speed. A new definition of 2-D DFT relation is presented. This new definition enables DFT computation organized in stages involving only real addition except at the final stage of computation. The number of stages is always fixed at 4. Two different strategies are proposed. 1) A visual representation of 2-D DFT coefficients. 2) A neural network approach. The visual representation scheme can be used to compute, analyze and manipulate 2D signals such as images in the frequency domain in terms of symbols derived from 2x2 DFT. This, in turn, can be represented in terms of real data. This approach can help analyze signals in the frequency domain even without computing the DFT coefficients. A hierarchical neural network model is developed to implement 2-D DFT. Presently, this model is capable of implementing 2-D DFT for a particular order N such that ((N))4 = 2. The model can be developed into one that can implement the 2-D DFT for any order N upto a set maximum limited by the hardware constraints. The reported method shows a potential in implementing the 2-D DF T in hardware as a VLSI / ASIC

Document Image Segmentation and Compression using Artificial Neural Networks and Evolutionary Methods

The work is intended to study the following important aspects of document image processing and develop new methods. (1) Segmentation ofdocument images using adaptive interval valued neuro-fuzzy method. (2) Improving the segmentation procedure using Simulated Annealing technique. (3) Development of optimized compression algorithms using Genetic Algorithm and parallel Genetic Algorithm (4) Feature extraction of document images (5) Development of IV fuzzy rules. This work also helps for feature extraction and foreground and background identification. The proposed work incorporates Evolutionary and hybrid methods for segmentation and compression of document images. A study of different neural networks used in image processing, the study of developments in the area of fuzzy logic etc is carried out in this work

CBIR Using Local and Global Properties of Image Sub-blocks

This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation and finding the corner density in each partition. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. A combined colour and texture feature vector is computed for each region. The shape features are computed from the Edge Histogram Descriptor (EHD). Euclidean distance measure is used for computing the distance between the features of the query and target image. Experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods

Content Based Image Retrieval Using Low Level Features of Automatically Extracted Regions of Interest

This paper proposes a region based image retrieval system using the local colour and texture features of image sub regions. The regions of interest (ROI) are roughly identified by segmenting the image into fixed partitions, finding the edge map and applying morphological dilation. The colour and texture features of the ROIs are computed from the histograms of the quantized HSV colour space and Gray Level co- occurrence matrix (GLCM) respectively. Each ROI of the query image is compared with same number of ROIs of the target image that are arranged in the descending order of white pixel density in the regions, using Euclidean distance measure for similarity computation. Preliminary experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods.

A Sub-block Based Image Retrieval Using Modified Integrated Region Matching.

This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. A combined colour and texture feature vector is computed for each region. The shape features are computed from the Edge Histogram Descriptor (EHD). A modified Integrated Region Matching (IRM) algorithm is used for finding the minimum distance between the sub-blocks of the query and target image. Experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods

“Studies on short polyester fiber - polyurethane elastomer composite with different interfacial bonding agents”

The work presented in this thesis is regarding the development and evaluation of new bonding agents for short polyester fiber - polyurethane elastomer composites. The conventional bonding system based on hexamethylenetetramine, resorcinol and hydrated silica was not effective as a bonding agent for the composite, as the water eliminated during the formation of the RF resin hydrolysed the urethane linkages. Four bonding agents based on MDI/'I‘DI and polypropyleneglycol, propyleneglycol and glycerol were prepared and the composite recipe was optimised with respect to the cure characteristics and mechanical properties. The flow properties, stress relaxation pattern and the thermal degradation characteristics of the composites containing different bonding agents were then studied in detail to evaluate the new bonding systems. The optimum loading of resin was 5 phr and the ratio of the -01 to isocyanate was 1:1. The cure characteristics showed that the optimum combination of cure rate and processability was given by the composite with the resin based on polypropyleneglycol/ glycerol/ 4,4’diphenylmethanediisocynate (PPG/GL/MDI). From the rheological studies of the composites with and without bonding agents it was observed that all the composites showed pseudoplastic nature and the activation energy of flow of the composite was not altered by the presence of bonding agents. Mechanical properties such as tensile strength, modulus, tear resistance and abrasion resistance were improved in the presence of bonding agents and the effect was more pronounced in the case of abrasion resistance. The composites based on MDI/GL showed better initial properties while composites with resins based on MDI/PPG showed better aging resistance. Stress relaxation showed a multistage relaxation behaviour for the composite. Within the-strain levels studied, the initial rate of relaxation was higher and the cross over time was lesser for the composite containing bonding agents. The bonding agent based on MDI/PPG/GL was found to be a better choice for improving stress relaxation characteristics with better interfacial bonding. Thennogravimetirc analysis showed that the presence of fiber and bonding agents improved the thennal stability of the polyurethane elastomer marginally and it was maximum in the case of MDI / GL based bonding agents. The kinetics of degradation was not altered by the presence of bonding agents

Development of a Fully Automated Image Analysis Method for High Density cDNA and array CGH Microarray Based Genomic Studies

In this thesis, different techniques for image analysis of high density microarrays have been investigated. Most of the existing image analysis techniques require prior knowledge of image specific parameters and direct user intervention for microarray image quantification. The objective of this research work was to develop of a fully automated image analysis method capable of accurately quantifying the intensity information from high density microarrays images. The method should be robust against noise and contaminations that commonly occur in different stages of microarray development.