Characterization of Selected Photonic Materials and Systems Using Photoacoustic Technique

The photoacoustic investigations carried out on different photonic materials are presented in this thesis. Photonic materials selected for the investigation are tape cast ceramics, muItilayer dielectric coatings, organic dye doped PVA films and PMMA matrix doped with dye mixtures. The studies are performed by the measurement of photoacoustic signal generated as a result of modulated cw laser irradiation of samples. The gas-microphone scheme is employed for the detection of photoacoustic signal. The different measurements reported here reveal the adaptability and utility of the PA technique for the characterization of photonic materials.Ceramics find applications in the field of microelectronics industry. Tape cast ceramics are the building blocks of many electronic components and certain ceramic tapes are used as thermal barriers. The thermal parameters of these tapes will not be the same as that of thin films of the same materials. Parameters are influenced by the presence of foreign bodies in the matrix and the sample preparation technique. Measurements are done on ceramic tapes of Zirconia, Zirconia-Alumina combination, barium titanate, barium tin titanate, silicon carbide, lead zirconate titanateil'Z'T) and lead magnesium niobate titanate(PMNPT). Various configurations viz. heat reflection geometry and heat transmission geometry of the photoacoustic technique have been used for the evaluation of different thermal parameters of the sample. Heat reflection geometry of the PA cell has been used for the evaluation of thermal effusivity and heat transmission geometry has been made use of in the evaluation of thermal diffusivity. From the thermal diffusivity and thermal effusivity values, thermal conductivity is also calculated. The calculated values are nearly the same as the values reported for pure materials. This shows the feasibility of photoacoustic technique for the thermal characterization of ceramic tapes.Organic dyes find applications as holographic recording medium and as active media for laser operations. Knowledge of the photochemical stability of the material is essential if it has to be used tor any of these applications. Mixing one dye with another can change the properties of the resulting system. Through careful mixing of the dyes in appropriate proportions and incorporating them in polymer matrices, media of required stability can be prepared. Investigations are carried out on Rhodamine 6GRhodamine B mixture doped PMMA samples. Addition of RhB in small amounts is found to stabilize Rh6G against photodegradation and addition of Rh6G into RhB increases the photosensitivity of the latter. The PA technique has been successfully employed for the monitoring of dye mixture doped PMMA sample. The same technique has been used for the monitoring of photodegradation ofa laser dye, cresyl violet doped polyvinyl alcohol also.Another important application of photoacoustic technique is in nondestructive evaluation of layered samples. Depth profiling capability of PA technique has been used for the non-destructive testing of multilayer dielectric films, which are highly reflecting in the wavelength range selected for investigations. Eventhough calculation of thickness of the film is not possible, number of layers present in the system can be found out using PA technique. The phase plot has clear step like discontinuities, the number of which coincides with the number of layers present in the multilayer stack. This shows the sensitivity of PA signal phase to boundaries in a layered structure. This aspect of PA signal can be utilized in non-destructive depth profiling of reflecting samples and for the identification of defects in layered structures.

Photothermal and photoacoustic investigations on certain polymers and semi conducting materials

Material synthesizing and characterization has been one of the major areas of scientific research for the past few decades. Various techniques have been suggested for the preparation and characterization of thin films and bulk samples according to the industrial and scientific applications. Material characterization implies the determination of the electrical, magnetic, optical or thermal properties of the material under study. Though it is possible to study all these properties of a material, we concentrate on the thermal and optical properties of certain polymers. The thermal properties are detennined using photothermal beam deflection technique and the optical properties are obtained from various spectroscopic analyses. In addition, thermal properties of a class of semiconducting compounds, copper delafossites, arc determined by photoacoustic technique.Photothermal technique is one of the most powerful tools for non-destructive characterization of materials. This forms a broad class of technique, which includes laser calorimetry, pyroelectric technique, photoacollstics, photothermal radiometric technique, photothermal beam deflection technique etc. However, the choice of a suitable technique depends upon the nature of sample and its environment, purpose of measurement, nature of light source used etc. The polynler samples under the present investigation are thermally thin and optically transparent at the excitation (pump beam) wavelength. Photothermal beam deflection technique is advantageous in that it can be used for the detennination of thermal diffusivity of samples irrespective of them being thermally thick or thennally thin and optically opaque or optically transparent. Hence of all the abovementioned techniques, photothemlal beam deflection technique is employed for the successful determination of thermal diffusivity of these polymer samples. However, the semi conducting samples studied are themlally thick and optically opaque and therefore, a much simpler photoacoustic technique is used for the thermal characterization.The production of polymer thin film samples has gained considerable attention for the past few years. Different techniques like plasma polymerization, electron bombardment, ultra violet irradiation and thermal evaporation can be used for the preparation of polymer thin films from their respective monomers. Among these, plasma polymerization or glow discharge polymerization has been widely lIsed for polymer thin fi Im preparation. At the earlier stages of the discovery, the plasma polymerization technique was not treated as a standard method for preparation of polymers. This method gained importance only when they were used to make special coatings on metals and began to be recognized as a technique for synthesizing polymers. Thc well-recognized concept of conventional polymerization is based on molecular processcs by which thc size of the molecule increases and rearrangemcnt of atoms within a molecule seldom occurs. However, polymer formation in plasma is recognized as an atomic process in contrast to the above molecular process. These films are pinhole free, highly branched and cross linked, heat resistant, exceptionally dielectric etc. The optical properties like the direct and indirect bandgaps, refractive indices etc of certain plasma polymerized thin films prepared are determined from the UV -VIS-NIR absorption and transmission spectra. The possible linkage in the formation of the polymers is suggested by comparing the FTIR spectra of the monomer and the polymer. The thermal diffusivity has been measured using the photothermal beam deflection technique as stated earlier. This technique measures the refractive index gradient established in the sample surface and in the adjacent coupling medium, by passing another optical beam (probe beam) through this region and hence the name probe beam deflection. The deflection is detected using a position sensitive detector and its output is fed to a lock-in-amplifIer from which the amplitude and phase of the deflection can be directly obtained. The amplitude and phase of the deflection signal is suitably analyzed for determining the thermal diffusivity.Another class of compounds under the present investigation is copper delafossites. These samples in the form of pellets are thermally thick and optically opaque. Thermal diffusivity of such semiconductors is investigated using the photoacoustic technique, which measures the pressure change using an elcctret microphone. The output of the microphone is fed to a lock-in-amplificr to obtain the amplitude and phase from which the thermal properties are obtained. The variation in thermal diffusivity with composition is studied.

Photoacoustic studies on multilayer dielectric coatings

Non-destructive testing d multilayer dielectric coatings (SiO2/TiO2 structure) has been carried out using the photoacoustic technique. This technique makes use d a 10 mW He-Ne laser, a photoacoustic cell and a lock-in amplifier. The chopped He-Ne laser beam is allowed to fall on the sample placed in a photoacoustic cell. The acoustic signals thus generated are detected using a microphone and the resulting output is processed by a lock-in amplifier. The amplitude and phase of the signals were measured as a function of the chopping frequency. Striking step-like variations are observed in me phase against frequency plot which dearly reveals the different layers present in the multilayer structure.

Thermal characterisation of doped InP using photoacoustic technique

An open cell photoacoustic configuration has been employed to evaluate the thermal diffusivity of pure InP as well as InP doped with sulphur and iron. Chopped optical radiation at 488 nm from an Ar-ion laser has been used to excite photoacoustic signals which been detected by a sensitive electret microphone. Thermal diffusivity value have been calculated from phase versus chopping frequency plots. Doped sample are found to show a reduced value for thermal diffusivity in comparison with intrinsically pure sample. The results have been interpreted in terms of the mechanisms of heat generation and transmission in semiconductors.

Permutation entropy based real-time chatter detection using audio signal in turning process

Machine tool chatter is an unfavorable phenomenon during metal cutting, which results in heavy vibration of cutting tool. With increase in depth of cut, the cutting regime changes from chatter-free cutting to one with chatter. In this paper, we propose the use of permutation entropy (PE), a conceptually simple and computationally fast measurement to detect the onset of chatter from the time series using sound signal recorded with a unidirectional microphone. PE can efficiently distinguish the regular and complex nature of any signal and extract information about the dynamics of the process by indicating sudden change in its value. Under situations where the data sets are huge and there is no time for preprocessing and fine-tuning, PE can effectively detect dynamical changes of the system. This makes PE an ideal choice for online detection of chatter, which is not possible with other conventional nonlinear methods. In the present study, the variation of PE under two cutting conditions is analyzed. Abrupt variation in the value of PE with increase in depth of cut indicates the onset of chatter vibrations. The results are verified using frequency spectra of the signals and the nonlinear measure, normalized coarse-grained information rate (NCIR).

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.

Permutation Entropy Based Analysis of Complex Signals for Characterising Change in System Dynamics

Timely detection of sudden change in dynamics that adversely affect the performance of systems and quality of products has great scientific relevance. This work focuses on effective detection of dynamical changes of real time signals from mechanical as well as biological systems using a fast and robust technique of permutation entropy (PE). The results are used in detecting chatter onset in machine turning and identifying vocal disorders from speech signal.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. Here we propose the use of permutation entropy (PE), to detect the dynamical changes in two non linear processes, turning under mechanical system and speech under biological system.Effectiveness of PE in detecting the change in dynamics in turning process from the time series generated with samples of audio and current signals is studied. Experiments are carried out on a lathe machine for sudden increase in depth of cut and continuous increase in depth of cut on mild steel work pieces keeping the speed and feed rate constant. The results are applied to detect chatter onset in machining. These results are verified using frequency spectra of the signals and the non linear measure, normalized coarse-grained information rate (NCIR).PE analysis is carried out to investigate the variation in surface texture caused by chatter on the machined work piece. Statistical parameter from the optical grey level intensity histogram of laser speckle pattern recorded using a charge coupled device (CCD) camera is used to generate the time series required for PE analysis. Standard optical roughness parameter is used to confirm the results.Application of PE in identifying the vocal disorders is studied from speech signal recorded using microphone. Here analysis is carried out using speech signals of subjects with different pathological conditions and normal subjects, and the results are used for identifying vocal disorders. Standard linear technique of FFT is used to substantiate thc results.The results of PE analysis in all three cases clearly indicate that this complexity measure is sensitive to change in regularity of a signal and hence can suitably be used for detection of dynamical changes in real world systems. This work establishes the application of the simple, inexpensive and fast algorithm of PE for the benefit of advanced manufacturing process as well as clinical diagnosis in vocal disorders.

Realization of a Scanning Photoacoustic Technique: Thermal properties of Bulk and Film Samples

Among the large number of photothcrmal techniques available, photoacoustics assumes a very significant place because of its essential simplicity and the variety of applications it finds in science and technology. The photoacoustic (PA) effect is the generation of an acoustic signal when a sample, kept inside an enclosed volume, is irradiated by an intensity modulated beam of radiation. The radiation absorbed by the sample is converted into thermal waves by nonradiative de-excitation processes. The propagating thermal waves cause a corresponding expansion and contraction of the gas medium surrounding the sample, which in tum can be detected as sound waves by a sensitive microphone. These sound waves have the same frequency as the initial modulation frequency of light. Lock-in detection method enables one to have a sufficiently high signal to noise ratio for the detected signal. The PA signal amplitude depends on the optical absorption coefficient of the sample and its thermal properties. The PA signal phase is a function of the thermal diffusivity of the sample.Measurement of the PA amplitude and phase enables one to get valuable information about the thermal and optical properties of the sample. Since the PA signal depends on the optical and thennal properties of the sample, their variation will get reflected in the PA signal. Therefore, if the PA signal is collected from various points on a sample surface it will give a profile of the variations in the optical/thennal properties across the sample surface. Since the optical and thermal properties are affected by the presence of defects, interfaces, change of material etc. these will get reflected in the PA signal. By varying the modulation frequency, we can get information about the subsurface features also. This is the basic principle of PA imaging or PA depth profiling. It is a quickly expanding field with potential applications in thin film technology, chemical engineering, biology, medical diagnosis etc. Since it is a non-destructive method, PA imaging has added advantages over some of the other imaging techniques. A major part of the work presented in this thesis is concemed with the development of a PA imaging setup that can be used to detect the presence of surface and subsmface defects in solid samples.Determination of thermal transport properties such as thermal diffusivity, effusivity, conductivity and heat capacity of materials is another application of photothennal effect. There are various methods, depending on the nature of the sample, to determine these properties. However, there are only a few methods developed to determine all these properties simultaneously. Even though a few techniques to determine the above thermal properties individually for a coating can be found in literature, no technique is available for the simultaneous measurement of these parameters for a coating. We have developed a scanning photoacoustic technique that can be used to determine all the above thermal transport properties simultaneously in the case of opaque coatings such as paints. Another work that we have presented in this thesis is the determination of thermal effusivity of many bulk solids by a scanning photoacoustic technique. This is one of the very few methods developed to determine thermal effiisivity directly.

Photoacoustic investigation of the optical and thermal properties of selected amorphous chalcogenide semiconductors

This thesis work has mainly concentrated on the investigation of the ,optical and thermal properties of binary semiconducting chalcogenide glasses belonging to the AivB¥5x and AZBXEX families. The technique used for these studies is a relatively new one namely, the photoacoustic (PA) technique. This technique is based on the detection of acoustic signal produced in an enclosed volume when the sample is irradiated by an intensity modulated radiation. The signal produced depends upon the optical properties of the sample, and the thermal properties of the sample, backing material and the surrounding gas. For the present studies an efficient signal beam gas-microphone PA spectrometer, consisting of a high power Xenon lamp, monochromator, light beam chopper, PA cell with microphone and lock-in amplifier, has been set up. Two PA cells have been fabricated: one for room temperature measurements and another for measurements at high temperatures. With the high temperature PA cell measurements can be taken upto 250°C. Provisions are incorporated. in both the cells to change the volume and to use different backing materials for the sample. The cells have been calibrated by measuring the frequency response of the cells using carbon black as the sample

Feature Extraction Methods Based on Linear Predictive Coding and Wavelet Packet Decomposition for Recognizing Spoken Words in Malayalam

Speech signals are one of the most important means of communication among the human beings. In this paper, a comparative study of two feature extraction techniques are carried out for recognizing speaker independent spoken isolated words. First one is a hybrid approach with Linear Predictive Coding (LPC) and Artificial Neural Networks (ANN) and the second method uses a combination of Wavelet Packet Decomposition (WPD) and Artificial Neural Networks. Voice signals are sampled directly from the microphone and then they are processed using these two techniques for extracting the features. Words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. Training, testing and pattern recognition are performed using Artificial Neural Networks. Back propagation method is used to train the ANN. The proposed method is implemented for 50 speakers uttering 20 isolated words each. Both the methods produce good recognition accuracy. But Wavelet Packet Decomposition is found to be more suitable for recognizing speech because of its multi-resolution characteristics and efficient time frequency localizations

PERFORMANCE OF DIFFERENT CLASSIFIERS IN SPEECH RECOGNITION

Speech is the most natural means of communication among human beings and speech processing and recognition are intensive areas of research for the last five decades. Since speech recognition is a pattern recognition problem, classification is an important part of any speech recognition system. In this work, a speech recognition system is developed for recognizing speaker independent spoken digits in Malayalam. Voice signals are sampled directly from the microphone. The proposed method is implemented for 1000 speakers uttering 10 digits each. Since the speech signals are affected by background noise, the signals are tuned by removing the noise from it using wavelet denoising method based on Soft Thresholding. Here, the features from the signals are extracted using Discrete Wavelet Transforms (DWT) because they are well suitable for processing non-stationary signals like speech. This is due to their multi- resolutional, multi-scale analysis characteristics. Speech recognition is a multiclass classification problem. So, the feature vector set obtained are classified using three classifiers namely, Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Naive Bayes classifiers which are capable of handling multiclasses. During classification stage, the input feature vector data is trained using information relating to known patterns and then they are tested using the test data set. The performances of all these classifiers are evaluated based on recognition accuracy. All the three methods produced good recognition accuracy. DWT and ANN produced a recognition accuracy of 89%, SVM and DWT combination produced an accuracy of 86.6% and Naive Bayes and DWT combination produced an accuracy of 83.5%. ANN is found to be better among the three methods.

Tailoring Magnetic, Mechanical and Dielectric Properties of Magnetorheological Elastomers based on Natural Rubber and Iron by Magnetic Field Assisted Curing for Possible Applications

If magnetism is universal in nature, magnetic materials are ubiquitous. A life without magnetism is unthinkable and a day without the influence of a magnetic material is unimaginable. They find innumerable applications in the form of many passive and active devices namely, compass, electric motor, generator, microphone, loud speaker, maglev train, magnetic resonance imaging, data recording and reading, hadron collider etc. The list is endless. Such is the influence of magnetism and magnetic materials in ones day to day life. With the advent of nanoscience and nanotechnology, along with the emergence of new areas/fields such as spintronics, multiferroics and magnetic refrigeration, the importance of magnetism is ever increasing and attracting the attention of researchers worldwide. The search for a fluid which exhibits magnetism has been on for quite some time. However nature has not bestowed us with a magnetic fluid and hence it has been the dream of many researchers to synthesize a magnetic fluid which is thought to revolutionize many applications based on magnetism. The discovery of a magnetic fluid by Jacob Rabinow in the year 1952 paved the way for a new branch of Physics/Engineering which later became magnetic fluids. This gave birth to a new class of material called magnetorheological materials. Magnetorheological materials are considered superior to electrorheological materials in that magnetorheology is a contactless operation and often inexpensive.Most of the studies in the past on magnetorheological materials were based on magnetic fluids. Recently the focus has been on the solid state analogue of magnetic fluids which are called Magnetorheological Elastomers (MREs). The very word magnetorheological elastomer implies that the rheological properties of these materials can be altered by the influence of an external applied magnetic field and this process is reversible. If the application of an external magnetic field modifies the viscosity of a magnetic fluid, the effect of external magnetic stimuli on a magnetorheological elastomer is in the modification of its stiffness. They are reversible too. Magnetorheological materials exhibit variable stiffness and find applications in adaptive structures of aerospace, automotive civil and electrical engineering applications. The major advantage of MRE is that the particles are not able to settle with time and hence there is no need of a vessel to hold it. The possibility of hazardous waste leakage is no more with a solid MRE. Moreover, the particles in a solid MRE will not affect the performance and durability of the equipment. Usually MR solids work only in the pre yield region while MR fluids, typically work in the post yield state. The application of an external magnetic field modifies the stiffness constant, shear modulus and loss modulus which are complex quantities. In viscoelastic materials a part of the input energy is stored and released during each cycle and a part is dissipated as heat. The storage modulus G′ represents the capacity of the material to store energy of deformation, which contribute to material stiffness. The loss modulusG′′ represents the ability of the material to dissipate the energy of deformation. Such materials can find applications in the form of adaptive vibration absorbers (ATVAs), stiffness tunable mounts and variable impedance surfaces. MREs are an important material for automobile giants and became the focus of this research for eventual automatic vibration control, sound isolation, brakes, clutches and suspension systems