Studies on Heat Diffusion in Selected Conducting Polymers using Probe Beam Deflection and Photoacoustic Techniques

In the present study, radio frequency plasma polymerization technique is used to prepare thin films of polyaniline, polypyrrole, poly N-methyl pyrrole and polythiophene. The thermal characterization of these films is carried out using transverse probe beam deflection method. Electrical conductivity and band gaps are also determined. The effect of iodine doping on electrical conductivity and the rate of heat diffusion is explored.Bulk samples of poyaniline and polypyrrole in powder form are synthesized by chemical route. Open photoacoustic cell configuration is employed for the thermal characterization of these samples. The effect of acid doping on heat diffusion in these bulk samples of polyaniline is also investigated. The variation of electrical conductivity of doped polyaniline and polypyrrole with temperature is also studied for drawing conclusion on the nature of conduction in these samples. In order to improve the processability of polyaniline and polypyrrole, these polymers are incorporated into a host matrix of poly vinyl chloride. Measurements of thermal diffusivity and electrical conductivity of these samples are carried out to investigate the variation of these quantities as a function of the content of polyvinyl chloride.

Application of Fermentation Techniques in the Utilization of Prawn Shell Waste

The present study aimed at the utlisation of microbial organisms for the production of good quality chitin and chitosan. The three strains used for the study were Lactobacillus plantarum, Lactobacililus brevis and Bacillus subtilis. These strains were selected on the basis of their acid producing ability to reduce the pH of the fermenting substrates to prevent spoilage and thus caused demineralisation of the shell. Besides, the proteolytic enzymes in these strains acted on proteinaceous covering of shrimp and thus caused deprotenisation of shrimp shell waste. Thus the two processes involved in chitin production can be affected to certain extent using bacterial fermentation of shrimp shell.Optimization parameters like fermentation period, quantity of inoculum, type of sugar, concentration of sugar etc. for fermentation with three different strains were studied. For these, parameters like pH, Total titrable acidity (TTA), changes in sugar concentration, changes in microbial count, sensory changes etc. were studied.Fermentation study with Lactobacillus plantarum was continued with 20% w/v jaggery broth for 15 days. The inoculum prepared yislded a cell concentration of approximately 108 CFU/ml. In the present study, lactic acid and dilute hydrochloric acid were used for initial pH adjustment because; without adjusting the initial pH, it took more than 5 hours for the lactic acid bacteria to convert glucose to lactic acid and during this delay spoilage occurred due to putrefying enzymes active at neutral or higher pH. During the fermentation study, pH first decreased in correspondence with increase in TTA values. This showed a clear indication of acid production by the strain. This trend continued till their proteolytic activity showed an increasing trend. When the available sugar source started depleting, proteolytic activity also decreased and pH increased. This was clearly reflected in the sensory evaluation results. Lactic acid treated samples showed greater extent of demineralization and deprotenisation at the end of fermentation study than hydrochloric acid treated samples. It can be due to the effect of strong hydrochloric acid on the initial microbial count, which directly affects the fermentation process. At the end of fermentation, about 76.5% of ash was removed in lactic acid treated samples and 71.8% in hydrochloric acid treated samples; 72.8% of proteins in lactic acid treated samples and 70.6% in hydrochloric acid treated samples.The residual protein and ash in the fermented residue were reduced to permissible limit by treatment with 0.8N HCI and 1M NaOH. Characteristics of chitin like chitin content, ash content, protein content, % of N- acetylation etc. were studied. Quality characteristics like viscosity, degree of deacetylation and molecular weight of chitosan prepared were also compared. The chitosan samples prepared from lactic acid treated showed high viscosity than HCI treated samples. But degree of deacetylation is more in HCI treated samples than lactic acid treated ones. Characteristics of protein liquor obtained like its biogenic composition, amino acid composition, total volatile base nitrogen, alpha amino nitrogen etc. also were studied to find out its suitability as animal feed supplement.Optimization of fermentation parameters for Lactobacillus brevis fermentation study was also conducted and parameters were standardized. Then detailed fermentation study was done in 20%wlv jaggery broth for 17 days. Also the effect of two different acid treatments (mild HCI and lactic acid) used for initial pH adjustment on chitin production were also studied. In this study also trend of changes in pH. changes in sugar concentration ,microbial count changes were similar to Lactobacillus plantarum studies. At the end of fermentation, residual protein in the samples were only 32.48% in HCI treated samples and 31.85% in lactic acid treated samples. The residual ash content was about 33.68% in HCI treated ones and 32.52% in lactic acid treated ones. The fermented residue was converted to chitin with good characteristics by treatment with 1.2MNaOH and 1NHCI.Characteristics of chitin samples prepared were studied and extent of Nacetylation was about 84% in HCI treated chitin and 85%in lactic acid treated ones assessed from FTIR spectrum. Chitosan was prepared from these samples by usual chemical method and its extent of solubility, degree of deacetylation, viscosity and molecular weight etc were studied. The values of viscosity and molecular weight of the samples prepared were comparatively less than the chitosan prepared by Lactobacillus plantarum fermentation. Characteristics of protein liquor obtained were analyzed to determine its quality and is suitability as animal feed supplement.Another strain used for the study was Bacillus subtilis and fermentation was carried out in 20%w/v jaggery broth for 15 days. It was found that Bacillus subtilis was more efficient than other Lactobacillus species for deprotenisation and demineralization. This was mainly due to the difference in the proteolytic nature of the strains. About 84% of protein and 72% of ash were removed at the end of fermentation. Considering the statistical significance (P

Speech Analysis using Modern Techniques of Nonlinear Dynamics

Medical fields requires fast, simple and noninvasive methods of diagnostic techniques. Several methods are available and possible because of the growth of technology that provides the necessary means of collecting and processing signals. The present thesis details the work done in the field of voice signals. New methods of analysis have been developed to understand the complexity of voice signals, such as nonlinear dynamics aiming at the exploration of voice signals dynamic nature. The purpose of this thesis is to characterize complexities of pathological voice from healthy signals and to differentiate stuttering signals from healthy signals. Efficiency of various acoustic as well as non linear time series methods are analysed. Three groups of samples are used, one from healthy individuals, subjects with vocal pathologies and stuttering subjects. Individual vowels/ and a continuous speech data for the utterance of the sentence "iruvarum changatimaranu" the meaning in English is "Both are good friends" from Malayalam language are recorded using a microphone . The recorded audio are converted to digital signals and are subjected to analysis.Acoustic perturbation methods like fundamental frequency (FO), jitter, shimmer, Zero Crossing Rate(ZCR) were carried out and non linear measures like maximum lyapunov exponent(Lamda max), correlation dimension (D2), Kolmogorov exponent(K2), and a new measure of entropy viz., Permutation entropy (PE) are evaluated for all three groups of the subjects. Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. The results shows that nonlinear dynamical methods seem to be a suitable technique for voice signal analysis, due to the chaotic component of the human voice. Permutation entropy is well suited due to its sensitivity to uncertainties, since the pathologies are characterized by an increase in the signal complexity and unpredictability. Pathological groups have higher entropy values compared to the normal group. The stuttering signals have lower entropy values compared to the normal signals.PE is effective in charaterising the level of improvement after two weeks of speech therapy in the case of stuttering subjects. PE is also effective in characterizing the dynamical difference between healthy and pathological subjects. This suggests that PE can improve and complement the recent voice analysis methods available for clinicians. The work establishes the application of the simple, inexpensive and fast algorithm of PE for diagnosis in vocal disorders and stuttering subjects.

Development of Time - Frequency Techniques for Sonar Applications

Sonar signal processing comprises of a large number of signal processing algorithms for implementing functions such as Target Detection, Localisation, Classification, Tracking and Parameter estimation. Current implementations of these functions rely on conventional techniques largely based on Fourier Techniques, primarily meant for stationary signals. Interestingly enough, the signals received by the sonar sensors are often non-stationary and hence processing methods capable of handling the non-stationarity will definitely fare better than Fourier transform based methods.Time-frequency methods(TFMs) are known as one of the best DSP tools for nonstationary signal processing, with which one can analyze signals in time and frequency domains simultaneously. But, other than STFT, TFMs have been largely limited to academic research because of the complexity of the algorithms and the limitations of computing power. With the availability of fast processors, many applications of TFMs have been reported in the fields of speech and image processing and biomedical applications, but not many in sonar processing. A structured effort, to fill these lacunae by exploring the potential of TFMs in sonar applications, is the net outcome of this thesis. To this end, four TFMs have been explored in detail viz. Wavelet Transform, Fractional Fourier Transfonn, Wigner Ville Distribution and Ambiguity Function and their potential in implementing five major sonar functions has been demonstrated with very promising results. What has been conclusively brought out in this thesis, is that there is no "one best TFM" for all applications, but there is "one best TFM" for each application. Accordingly, the TFM has to be adapted and tailored in many ways in order to develop specific algorithms for each of the applications.

Oligo(p-Phenylenevinylene) Derived Organogels: A Novel Class of Functional Supramolecular Materials

The main objective of the present study is to have a detailed investigation on the gelation properties, morphology and optical properties of small π-conjugated oligomers. For this purpose we have chosen oligo(p-phenylenevinylene)s (OPVs), a class of molecules which have received considerable attention due to their unique optical and electronic properties. Though a large number of reports are available in the literature on the self-assembly properties of tailor made OPVs, none of them pertain to the design of nanostructures based on organogels. In view of this, we aimed at the creation of functional chromophoric assemblies of π-conjugated OPVs through the formation of organogels, with the objective of crafting nanoscopic assemblies of different size and shape thereby modulating their optical and electronic properties.In order to fulfill the above objectives, the design and synthesis of a variety of OPVs with appropriate structural variations were planned. The design principle involves the derivatization of OPVs with weak H-bonding hydroxymethyl end groups and with long aliphatic hydrocarbon side chains. The noncovalent interactions in these molecules were expected to lead the formation of supramolecular assembly and gels in hydrocarbon solvents. In such an event, detailed study of gelation and extensive analysis of the morphology of the gel structures were planned using advanced microscopic techniques. Since OPVs are strongly fluorescent molecules, gelation is expected to perturb the optical properties. Therefore, detailed study on the gelation induced optical properties as a way to probe the nature and stability of the selfassembly was planned. Apart from this, the potential use of the modulation of the optical properties for the purpose of light harvesting was aimed. The approach to this problem was to entrap an appropriate energy trap to the OPV gel matrix which may lead to the efficient energy transfer from the OPV gel based donor to the entrapped acceptor. The final question that we wanted to address in this investigation was the creation of helical nanostructures through proper modification of the OPV backbone With chiral handles.The present thesis is a detailed and systematic approach to the realization of the above objectives which are presented in different chapters of the thesis.

Investigations of Optical Interaction Processes in Certain Photonic Materials Using Z-scan and Thermal Lens Techniques

International School of Photonics, Cochin University of Science and Technology

Novel Melt Transurethane Process for Cycloaliphatic Polyurethanes and Their Self-Organization for Nano-Materials

In this introduction part, importance has been given to the elastomeric properties of polyurethanes. Emphasis has been laid to this property based on microphase separation and how this could be modified by modifying the segment lengths, as well as the structure of the segments. Implication was also made on the mechanical and thermal properties of these copolymers based on various analytical methods usually used for characterization of polymers. A brief overview of the challenges faced by the polyurethane chemistry was also done, pointing to the fact that though polyurethane industry is more than 75 years old, still a lot of questions remain unanswered, that too mostly in the synthesis of polyurethanes. A major challenge in this industry is the utilization of more environmental friendly “Green Chemistry Routes” for the synthesis of polyurethanes which are devoid of any isocyanates or harsh solvents.The research work in this thesis was focused to develop non-isocyanate green chemical process for polyurethanes and also self-organize the resultant novel polymers into nano-materials. The thesis was focused on the following three major aspects:(i) Design and development of novel melt transurethane process for polyurethanes under non-isocyanate and solvent free melt condition. (ii) Solvent induced self-organization of the novel cycloaliphatic polyurethanes prepared by the melt transurethane process into microporous templates and nano-sized polymeric hexagons and spheres. (iii) Novel polyurethane-oligophenylenevinylene random block copolymer nano-materials and their photoluminescence properties. The second chapter of the thesis gives an elaborate discussion on the “Novel Melt Transurethane Process ” for the synthesis of polyurethanes under non-isocyanate and solvent free melt condition. The polycondensation reaction was carried out between equimolar amounts of a di-urethane monomer and a diol in the presence of a catalyst under melt condition to produce polyurethanes followed by the removal of low boiling alcohol from equilibrium. The polymers synthesized through this green chemical route were found to be soluble (devoid of any cross links), thermally stable and free from any isocyanate entities. The polymerization reaction was confirmed by various analytical techniques with specific references to the extent of reaction which is the main watchful point for any successful polymerization reaction. The mechanistic aspects of the reaction were another point of consideration for the novel polymerization route which was successfully dealt with by performing various model reactions. Since this route was successful enough in synthesizing polyurethanes with novel structures, they were employed for the solvent induced self-organization which is an important area of research in the polymer world in the present scenario. Chapter three mesmerizes the reader with multitudes of morphologies depending upon the chemical backbone structure of the polyurethane as well as on the nature and amount of various solvents employed for the self-organization tactics. The rationale towards these morphologies-“Hydrogen Bonding ” have been systematically probed by various techniques. These polyurethanes were then tagged with luminescent 0ligo(phenylene vinylene) units and the effects of these OPV blocks on the morphology of the polyurethanes were analyzed in chapter four. These blocks have resulted in the formation of novel “Blue Luminescent Balls” which could find various applications in optoelectronic devices as well as delivery vehicles.

Development and Evaluation of Blind Identification Techniques for Nonlinear Systems

Identification and Control of Non‐linear dynamical systems are challenging problems to the control engineers.The topic is equally relevant in communication,weather prediction ,bio medical systems and even in social systems,where nonlinearity is an integral part of the system behavior.Most of the real world systems are nonlinear in nature and wide applications are there for nonlinear system identification/modeling.The basic approach in analyzing the nonlinear systems is to build a model from known behavior manifest in the form of system output.The problem of modeling boils down to computing a suitably parameterized model,representing the process.The parameters of the model are adjusted to optimize a performanace function,based on error between the given process output and identified process/model output.While the linear system identification is well established with many classical approaches,most of those methods cannot be directly applied for nonlinear system identification.The problem becomes more complex if the system is completely unknown but only the output time series is available.Blind recognition problem is the direct consequence of such a situation.The thesis concentrates on such problems.Capability of Artificial Neural Networks to approximate many nonlinear input-output maps makes it predominantly suitable for building a function for the identification of nonlinear systems,where only the time series is available.The literature is rich with a variety of algorithms to train the Neural Network model.A comprehensive study of the computation of the model parameters,using the different algorithms and the comparison among them to choose the best technique is still a demanding requirement from practical system designers,which is not available in a concise form in the literature.The thesis is thus an attempt to develop and evaluate some of the well known algorithms and propose some new techniques,in the context of Blind recognition of nonlinear systems.It also attempts to establish the relative merits and demerits of the different approaches.comprehensiveness is achieved in utilizing the benefits of well known evaluation techniques from statistics. The study concludes by providing the results of implementation of the currently available and modified versions and newly introduced techniques for nonlinear blind system modeling followed by a comparison of their performance.It is expected that,such comprehensive study and the comparison process can be of great relevance in many fields including chemical,electrical,biological,financial and weather data analysis.Further the results reported would be of immense help for practical system designers and analysts in selecting the most appropriate method based on the goodness of the model for the particular context.

Techniques for Enhancing Wind Energy Generation - A CFD Based Multibody Dynamics Approach in Horizontal Axis Wind Turbines

Wind energy has emerged as a major sustainable source of energy.The efficiency of wind power generation by wind mills has improved a lot during the last three decades.There is still further scope for maximising the conversion of wind energy into mechanical energy.In this context,the wind turbine rotor dynamics has great significance.The present work aims at a comprehensive study of the Horizontal Axis Wind Turbine (HAWT) aerodynamics by numerically solving the fluid dynamic equations with the help of a finite-volume Navier-Stokes CFD solver.As a more general goal,the study aims at providing the capabilities of modern numerical techniques for the complex fluid dynamic problems of HAWT.The main purpose is hence to maximize the physics of power extraction by wind turbines.This research demonstrates the potential of an incompressible Navier-Stokes CFD method for the aerodynamic power performance analysis of horizontal axis wind turbine.The National Renewable Energy Laboratory USA-NREL (Technical Report NREL/Cp-500-28589) had carried out an experimental work aimed at the real time performance prediction of horizontal axis wind turbine.In addition to a comparison between the results reported by NREL made and CFD simulations,comparisons are made for the local flow angle at several stations ahead of the wind turbine blades.The comparison has shown that fairly good predictions can be made for pressure distribution and torque.Subsequently, the wind-field effects on the blade aerodynamics,as well as the blade/tower interaction,were investigated.The selected case corresponded to a 12.5 m/s up-wind HAWT at zero degree of yaw angle and a rotational speed of 25 rpm.The results obtained suggest that the present can cope well with the flows encountered around wind turbines.The areodynamic performance of the turbine and the flow details near and off the turbine blades and tower can be analysed using theses results.The aerodynamic performance of airfoils differs from one another.The performance mainly depends on co-efficient of performnace,co-efficient of lift,co-efficient of drag, velocity of fluid and angle of attack.This study shows that the velocity is not constant for all angles of attack of different airfoils.The performance parameters are calculated analytically and are compared with the standardized performance tests.For different angles of ,the velocity stall is determined for the better performance of a system with respect to velocity.The research addresses the effect of surface roughness factor on the blade surface at various sections.The numerical results were found to be in agreement with the experimental data.A relative advantage of the theoretical aerofoil design method is that it allows many different concepts to be explored economically.Such efforts are generally impractical in wind tunnels because of time and money constraints.Thus, the need for a theoretical aerofoil design method is threefold:first for the design of aerofoil that fall outside the range of applicability of existing calalogs:second,for the design of aerofoil that more exactly match the requirements of the intended application:and third,for the economic exploration of many aerofoil concepts.From the results obtained for the different aerofoils,the velocity is not constant for all angles of attack.The results obtained for the aerofoil mainly depend on angle of attack and velocity.The vortex generator technique was meticulously studies with the formulation of the specification for the right angle shaped vortex generators-VG.The results were validated in accordance with the primary analysis phase.The results were found to be in good agreement with the power curve.The introduction of correct size VGs at appropriate locations over the blades of the selected HAWT was found to increase the power generation by about 4%

Spectral and Structural Studies of Transition Metal Complexes of Thiosemicarbazones Containing Ring Incorporated at N(4)-position

The thesis is an introduction to evaluate the coordination behaviour of a few compounds of our interest. The crucial aim of these investigations was to synthesize and characterize some transition metal complexes using the ligands benzaldehyde, 2-hydroxybenzaldehyde and 4-methoxybenzaldehyde N(4)-ring incorporated thiosemicarbazones.The study involves a brief foreword of the metal complexes of thiosemicarbazones including their bonding, stereochemistry and biological activities.The different analytical and spectroscopic techniques used for the analysis of the ligands and their complexes are discussed.It also deals with the synthesis and spectral characterization of the thiosemicarbazones and single crystal X-ray diffraction study of one of them.Chapter 3 describes the synthesis, spectral characterization, single crystal X-ray diffraction studies of copper(ll) complexes with ONS/NS donor thiosemicarbazones. Chapter 4 deals with the synthesis, spectral characterization and single crystal X-ray diffraction studies of nickel(II) complexes. Chapter 5 contains the synthesis, structural and spectral characterization of the cobalt(III) complexes. Chapters 6 and 7 include the synthesis, structural and spectral characterization of zinc(II) and cadmium(ll) complexes with ONS/NS donor thiosemicarbazones.

Fractal based techniques for classification of mammograms and identification of microcalcifications

After skin cancer, breast cancer accounts for the second greatest number of cancer diagnoses in women. Currently the etiologies of breast cancer are unknown, and there is no generally accepted therapy for preventing it. Therefore, the best way to improve the prognosis for breast cancer is early detection and treatment. Computer aided detection systems (CAD) for detecting masses or micro-calcifications in mammograms have already been used and proven to be a potentially powerful tool , so the radiologists are attracted by the effectiveness of clinical application of CAD systems. Fractal geometry is well suited for describing the complex physiological structures that defy the traditional Euclidean geometry, which is based on smooth shapes. The major contribution of this research include the development of • A new fractal feature to accurately classify mammograms into normal and normal (i)With masses (benign or malignant) (ii) with microcalcifications (benign or malignant) • A novel fast fractal modeling method to identify the presence of microcalcifications by fractal modeling of mammograms and then subtracting the modeled image from the original mammogram. The performances of these methods were evaluated using different standard statistical analysis methods. The results obtained indicate that the developed methods are highly beneficial for assisting radiologists in making diagnostic decisions. The mammograms for the study were obtained from the two online databases namely, MIAS (Mammographic Image Analysis Society) and DDSM (Digital Database for Screening Mammography.

Statistical Machine Learning Techniques for the Prediction of Learning Disabilities in School-Age Children

Learning Disability (LD) is a general term that describes specific kinds of learning problems. It is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. The learning disabled children are neither slow nor mentally retarded. This disorder can make it problematic for a child to learn as quickly or in the same way as some child who isn't affected by a learning disability. An affected child can have normal or above average intelligence. They may have difficulty paying attention, with reading or letter recognition, or with mathematics. It does not mean that children who have learning disabilities are less intelligent. In fact, many children who have learning disabilities are more intelligent than an average child. Learning disabilities vary from child to child. One child with LD may not have the same kind of learning problems as another child with LD. There is no cure for learning disabilities and they are life-long. However, children with LD can be high achievers and can be taught ways to get around the learning disability. In this research work, data mining using machine learning techniques are used to analyze the symptoms of LD, establish interrelationships between them and evaluate the relative importance of these symptoms. To increase the diagnostic accuracy of learning disability prediction, a knowledge based tool based on statistical machine learning or data mining techniques, with high accuracy,according to the knowledge obtained from the clinical information, is proposed. The basic idea of the developed knowledge based tool is to increase the accuracy of the learning disability assessment and reduce the time used for the same. Different statistical machine learning techniques in data mining are used in the study. Identifying the important parameters of LD prediction using the data mining techniques, identifying the hidden relationship between the symptoms of LD and estimating the relative significance of each symptoms of LD are also the parts of the objectives of this research work. The developed tool has many advantages compared to the traditional methods of using check lists in determination of learning disabilities. For improving the performance of various classifiers, we developed some preprocessing methods for the LD prediction system. A new system based on fuzzy and rough set models are also developed for LD prediction. Here also the importance of pre-processing is studied. A Graphical User Interface (GUI) is designed for developing an integrated knowledge based tool for prediction of LD as well as its degree. The designed tool stores the details of the children in the student database and retrieves their LD report as and when required. The present study undoubtedly proves the effectiveness of the tool developed based on various machine learning techniques. It also identifies the important parameters of LD and accurately predicts the learning disability in school age children. This thesis makes several major contributions in technical, general and social areas. The results are found very beneficial to the parents, teachers and the institutions. They are able to diagnose the child’s problem at an early stage and can go for the proper treatments/counseling at the correct time so as to avoid the academic and social losses.

Development of Novel Polymer based Adhesives

Novel latex based and solution based adhesives were prepared and evaluated for wood to wood bonding.These adhesive were found to be superior to commercical adhesives like fevicol and dentrite.Novel adhesives were prepared for leather to leather bonding and these were also found to be more efficientt than the polyurethane type and dentrite adhesives used commercially.A novel strip adhesive system employing very low amount of solvents was tried successfully for rubber-to-metal bonding.Further ,a novel adhesive system was investigated successfully for bonding copper coated bead wire and steel cord to rubber by modifying it with chloroprene rubber.

Computer vision techniques in seafood quality control

The application of computer vision based quality control has been slowly but steadily gaining importance mainly due to its speed in achieving results and also greatly due to its non- destnictive nature of testing. Besides, in food applications it also does not contribute to contamination. However, computer vision applications in quality control needs the application of an appropriate software for image analysis. Eventhough computer vision based quality control has several advantages, its application has limitations as to the type of work to be done, particularly so in the food industries. Selective applications, however, can be highly advantageous and very accurate.Computer vision based image analysis could be used in morphometric measurements of fish with the same accuracy as the existing conventional method. The method is non-destructive and non-contaminating thus providing anadvantage in seafood processing.The images could be stored in archives and retrieved at anytime to carry out morphometric studies for biologists.Computer vision and subsequent image analysis could be used in measurements of various food products to assess uniformity of size. One product namely cutlet and product ingredients namely coating materials such as bread crumbs and rava were selected for the study. Computer vision based image analysis was used in the measurements of length, width and area of cutlets. Also the width of coating materials like bread crumbs was measured.Computer imaging and subsequent image analysis can be very effectively used in quality evaluations of product ingredients in food processing. Measurement of width of coating materials could establish uniformity of particles or the lack of it. The application of image analysis in bacteriological work was also done

Transition metal complexes derived from ketone based N(4)-substituted thiosemicarbazones: Crystal structures and spectral studies

Thiosemicarbazones have recently attracted considerable attention due to their ability to form tridentate chelates with transition metal ions through either two nitrogen and sulfur atoms, N–N–S or oxygen, nitrogen and sulfur atoms, O–N–S. Considerable interest in thiosemicarbazones and their transition metal complexes has also grown in the areas of biology and chemistry due to biological activities such as antitumoral, fungicidal, bactericidal, antiviral and nonlinear optical properties. They have been used for metal analyses, for device applications related to telecommunications, optical computing, storage and information processing.The versatile applications of metal complexes of thiosemicarbazones in various fields prompted us to synthesize the tridentate NNS-donor thiosemicarbazones and their metal complexes. As a part of our studies on transition metal complexes with these ligands, the researcher undertook the current work with the following objectives. 1. To synthesize and physico-chemically characterize the following thiosemicarbazone ligands: a. Di-2-pyridyl ketone-N(4)-methyl thiosemicarbazone (HDpyMeTsc) b. Di-2-pyridyl ketone-N(4)-ethyl thiosemicarbazone (HDpyETsc) 2. To synthesize oxovanadium(IV), manganese(II), nickel(II), copper(II), zinc(II) and cadmium(II) complexes using the synthesized thiosemicarbazones as principal ligands and some anionic coligands. 3. To study the coordination modes of the ligands in metal complexes by using different physicochemical methods like partial elemental analysis, thermogravimetry and by different spectroscopic techniques. 4. To establish the structure of compounds by single crystal XRD studies