Surface properties and catalytic activity of ferrospinels of nickel, cobalt and copper, prepared by soft chemical methods

Ferrospinels of nickel, cobalt and copper and their sulphated analogues were prepared by the room temperature coprecipitation route to yield samples with high surface areas. The intrinsic acidity among the ferrites was found to decrease in the order: cobalt> nickel> copper. Sulphation caused an increase in the number of weak and medium strong acid sites, whereas the strong acid sites were left unaffected. Electron donor studies revealed that copper ferrite has both the highest proportion of strong sites and the lowest proportion of weak basic sites. All the ferrite samples proved to be good catalysts for the benzoy lation of toluene with benzoyl chloride. copper and cobalt ferrites being much more active than nickel ferrite. The catalytic activity for benzoylation was not much influenced by sulphation, but it increased remarkably with calcination temperature of the catalyst. Surface Lewis acid sites, provided by the octahedral cations on the spinel surface, are suggested to be responsible for the catalytic activity for the benzoylation reaction.

Influence of sulphate content on the physico-chemical properties and catalytic activity of some sulphated zirconia systems

The present work attempts a systematic examination of the effect of sulphate content on the physico-chemical properties and catalytic activity of sulphated zirconia and iron promoted sulphated zirconia systems. Sulphate content is estimated by EDX analysis. The amount of sulphate incorporated has been found to influence the surface area, crystal structure and the acid strength distribution. Ammonia TPD and adsorption studies using perylene have enabled the determination of surface acidic properties. The results are supported by the thermodesorption studies using pyridine and 2,6-dimethylpyridine. The catalytic activity towards benzoylation reaction has been correlated with the surface acidity of the systems.

Chemical sensing with microbent optical fiber

We propose and demonstrate the possibility of using a permanently microbent bare optical fiber for detecting chemical species. Two detection schemes, viz., a bright-field detection scheme (for the core modes), and a dark-field detection scheme (for the cladding modes) have been employed to produce a fiber-optic sensor. The sensor described here is sensitive enough to detect concentrations as low as nanomoles per liter of a chemical species, with a dynamic range of more than 6 orders of magnitude.

Long period gratings in multimode optical fibers: application in chemical sensing

We propose and demonstrate a new technique for evanescent wave chemical sensing by writing long period gratings in a bare multimode plastic clad silica fiber. The sensing length of the present sensor is only 10 mm, but is as sensitive as a conventional unclad evanescent wave sensor having about 100 mm sensing length. The minimum measurable concentration of the sensor reported here is 10 nmol/l and the operating range is more than 4 orders of magnitude. Moreover, the detection is carried out in two independent detection configurations viz., bright field detection scheme that detects the core-mode power and dark field detection scheme that detects the cladding mode power. The use of such a double detection scheme definitely enhances the reliability and accuracy of the results. Furthermore, the cladding of the present fiber need not be removed as done in conventional evanescent wave fiber sensors.

Magnetic field-induced cluster formation and variation of magneto-optical signals in zinc-substituted ferrofluids

Fine magnetic particles (size≅100 Å) belonging to the series ZnxFe1−xFe2O4 were synthesized by cold co-precipitation methods and their structural properties were evaluated using X-ray diffraction. Magnetization studies have been carried out using vibrating sample magnetometry (VSM) showing near-zero loss loop characteristics. Ferrofluids were then prepared employing these fine magnetic powders using oleic acid as surfactant and kerosene as carrier liquid by modifying the usually reported synthesis technique in order to induce anisotropy and enhance the magneto-optical signals. Liquid thin films of these fluids were prepared and field-induced laser transmission through these films was studied. The transmitted light intensity decreases at the centre with applied magnetic field in a linear fashion when subjected to low magnetic fields and saturate at higher fields. This is in accordance with the saturation in cluster formation. The pattern exhibited by these films in the presence of different magnetic fields was observed with the help of a CCD camera and was recorded photographically.

Significance of Time Scales in Nonlinear Dynamical Analysis of Electroencephalogram Signals

We propose to show in this paper, that the time series obtained from biological systems such as human brain are invariably nonstationary because of different time scales involved in the dynamical process. This makes the invariant parameters time dependent. We made a global analysis of the EEG data obtained from the eight locations on the skull space and studied simultaneously the dynamical characteristics from various parts of the brain. We have proved that the dynamical parameters are sensitive to the time scales and hence in the study of brain one must identify all relevant time scales involved in the process to get an insight in the working of brain.

Recurrence Quantification Analysis of System Signals for Detecting Tool and Chatter in Turning

In this thesis, the applications of the recurrence quantification analysis in metal cutting operation in a lathe, with specific objective to detect tool wear and chatter, are presented.This study is based on the discovery that process dynamics in a lathe is low dimensional chaotic. It implies that the machine dynamics is controllable using principles of chaos theory. This understanding is to revolutionize the feature extraction methodologies used in condition monitoring systems as conventional linear methods or models are incapable of capturing the critical and strange behaviors associated with the metal cutting process.As sensor based approaches provide an automated and cost effective way to monitor and control, an efficient feature extraction methodology based on nonlinear time series analysis is much more demanding. The task here is more complex when the information has to be deduced solely from sensor signals since traditional methods do not address the issue of how to treat noise present in real-world processes and its non-stationarity. In an effort to get over these two issues to the maximum possible, this thesis adopts the recurrence quantification analysis methodology in the study since this feature extraction technique is found to be robust against noise and stationarity in the signals.The work consists of two different sets of experiments in a lathe; set-I and set-2. The experiment, set-I, study the influence of tool wear on the RQA variables whereas the set-2 is carried out to identify the sensitive RQA variables to machine tool chatter followed by its validation in actual cutting. To obtain the bounds of the spectrum of the significant RQA variable values, in set-i, a fresh tool and a worn tool are used for cutting. The first part of the set-2 experiments uses a stepped shaft in order to create chatter at a known location. And the second part uses a conical section having a uniform taper along the axis for creating chatter to onset at some distance from the smaller end by gradually increasing the depth of cut while keeping the spindle speed and feed rate constant.The study concludes by revealing the dependence of certain RQA variables; percent determinism, percent recurrence and entropy, to tool wear and chatter unambiguously. The performances of the results establish this methodology to be viable for detection of tool wear and chatter in metal cutting operation in a lathe. The key reason is that the dynamics of the system under study have been nonlinear and the recurrence quantification analysis can characterize them adequately.This work establishes that principles and practice of machining can be considerably benefited and advanced from using nonlinear dynamics and chaos theory.

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.

Highly conductive and transparent ZnO thin film using Chemical Spray Pyrolysis technique: Effect of doping and deposition parameters

In the present work we report the preparation details studies on ZnO thin films. ZnO thin films are prepared using cost effective deposition technique viz., Chemical Spray Pyrolysis (CSP). The method is very effective for large area preparation of the ZnO thin film. A new post-deposition process could also be developed to avoid the adsorption of oxygen that usually occurs after the spraying process i.e., while cooling. Studies were done by changing the various deposition parameters for optimizing the properties of ZnO thin film. Moreover, different methods of doping using various elements are also tried to enhance the conductivity and transparency of the film to make these suitable for various optoelectronic applications.

Optimization of Process Parameters for the Extraction of Gelatin from the Skin of Freshwater Fish and the Evaluation of Physical anal Chemical Characteristics

Faculty of Marine Sciences,Cochin University of Science and Technology

Analysis of System Signals Based on Cross Recurrence Method for System Dynamics Characterization

Natural systems are inherently non linear. Recurrent behaviours are typical of natural systems. Recurrence is a fundamental property of non linear dynamical systems which can be exploited to characterize the system behaviour effectively. Cross recurrence based analysis of sensor signals from non linear dynamical system is presented in this thesis. The mutual dependency among relatively independent components of a system is referred as coupling. The analysis is done for a mechanically coupled system specifically designed for conducting experiment. Further, cross recurrence method is extended to the actual machining process in a lathe to characterize the chatter during turning. The result is verified by permutation entropy method. Conventional linear methods or models are incapable of capturing the critical and strange behaviours associated with the dynamical process. Hence any effective feature extraction methodologies should invariably gather information thorough nonlinear time series analysis. The sensor signals from the dynamical system normally contain noise and non stationarity. In an effort to get over these two issues to the maximum possible extent, this work adopts the cross recurrence quantification analysis (CRQA) methodology since it is found to be robust against noise and stationarity in the signals. The study reveals that the CRQA is capable of characterizing even weak coupling among system signals. It also divulges the dependence of certain CRQA variables like percent determinism, percent recurrence and entropy to chatter unambiguously. The surrogate data test shows that the results obtained by CRQA are the true properties of the temporal evolution of the dynamics and contain a degree of deterministic structure. The results are verified using permutation entropy (PE) to detect the onset of chatter from the time series. The present study ascertains that this CRP based methodology is capable of recognizing the transition from regular cutting to the chatter cutting irrespective of the machining parameters or work piece material. The results establish this methodology to be feasible for detection of chatter in metal cutting operation in a lathe.

Bio-chemical changes associated with processing of shell fishes and flavour constituents of body meat and claw meat'of crab

In this thesis all these aspects are taken into consideration. Extensive studies were conducted on all aspects of processing of crabs, mussels and clams. The species taken for studies are commercially used ones namely Scylla sereta, perna viridis, and villorita cyprinoids. In Chapter 4.1 with regard to crab) the following aspects on their handling and processing are reported seasonal variation of chemical constituents, changes taking place during ice storage, freezing, canning etc. In Chapter 4._2 with regard to mussel, the relation between age (size) and chemical constituents, changes taking place during ice storage, freezing, canning etc. are reported and in Chapter 4.3 the changes taking place in clam muscle during icing and freezing are reported and the ame rebility of ice stored clams for canning purpose is reported.The interference of high concentration of glycogen in mussel and clam muscles during the colour development of ribose (Me-jbaum's method) is observed and remedial step are taken to minimise the interference.

Investment analysis of chemical projects and development of standerdised mathematical co-relation for cost estimation of pressure vessels in chemical industry

The present study is intended to provide a new scientific approach to the solution of the worlds cost engineering problems encountered in the chemical industries in our nation. The problem is that of cost estimation of equipments especially of pressure vessels when setting up chemical industries .The present study attempts to develop a model for such cost estimation. This in turn is hoped would go a long way to solve this and related problems in forecasting the cost of setting up chemical plants.

The economics of chemical industry in kerala

The main purpose of the present study is to examine the growth and development problems of a new industry ,the chemical industry in the state of kerala. Problems of productivity and efficiency are studied with respect to the different branches of the industry such as fertilizers and insecticides basic inorganic and organic chemicals drugs and pharmaceuticals and miscellaneous chemicals. A study of partial input output linkages between the different chemical units is also attempted. The chemical industry is generally characterized by high linkage effects .These linkages could be used to generate subsidiary industries and thereby help in the growth and diversification of the industry. The efficiency of the working of individual units is also studied to understand the problems involved and to suggest remedial measures.