7 resultados para Atomic decomposition

em Cochin University of Science


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Preparation of simple and mixed ferrospinels of nickel, cobalt and copper and their sulphated analogues by the room temperature coprecipitation method yielded fine particles with high surface areas. Study of the vapour phase decomposition of cyclohexanol at 300 °C over all the ferrospinel systems showed very good conversions yielding cyclohexene by dehydration and/or cyclohexanone by dehydrogenation, as the major products. Sulphation very much enhanced the dehydration activity over all the samples. A good correlation was obtained between the dehydration activities of the simple ferrites and their weak plus medium strength acidities (usually of the Brφnsted type) determined independently by the n-butylamine adsorption and ammonia-TPD methods. Mixed ferrites containing copper showed a general decrease in acidities and a drastic decrease in dehydration activities. There was no general correlation between the basicity parameters obtained by electron donor studies and the ratio of dehydrogenation to dehydration activities. There was a leap in the dehydrogenation activities in the case of all the ferrospinel samples containing copper. Along with the basic properties, the redox properties of copper ion have been invoked to account for this added activity.

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Cyclohexanol decomposition activity of supported vanadia catalysts is ascribed to the high surface area, total acidity and interaction between supported vanadia and the amorphous support. Among the supported catalysts, the effect of vanadia over various wt% V2O5 (2–10) loading indicates that the catalyst comprising of 6 wt% V2O5 exhibits higher acidity and decomposition activity. Structural characterization of the catalysts has been done by techniques like energy dispersive X-ray analysis, X-ray diffraction and BET surface area. Acidity of the catalysts has been measured by temperature programmed desorption using ammonia as a probe molecule and the results have been correlated with the activity of catalysts.

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Department of Applied Chemistry, Cochin University of Science and Technology

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In the present thesis we have formulated the Dalgarno-Lewis procedure for two-and three-photon processes and an elegant alternate expressions are derived. Starting from a brief review on various multiphoton processes we have discussed the difficulties coming in the perturbative treatment of multiphoton processes. A small discussion on various available methods for studying multiphoton processes are presented in chapter 2. These theoretical treatments mainly concentrate on the evaluation of the higher order matrix elements coming in the perturbation theory. In chapter 3 we have described the use of Dalgarno-Lewis procedure and its implimentation on second order matrix elements. The analytical expressions for twophoton transition amplitude, two-photon ionization cross section, dipole dynamic polarizability and Kramers-Heiseberg are obtained in a unified manner. Fourth chapter is an extension of the implicit summation technique presented in chapter 3. We have clearly mentioned the advantage of our method, especially the analytical continuation of the relevant expressions suited for various values of radiation frequency which is also used for efficient numerical analysis. A possible extension of the work is to study various multiphoton processcs from the stark shifted first excited states of hydrogen atom. We can also extend this procedure for studying multiphoton processes in alkali atoms as well as Rydberg atoms. Also, instead of going for analytical expressions, one can try a complete numerical evaluation of the higher order matrix elements using this procedure.

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Present work deals with the Preparation and characterization of high-k aluminum oxide thin films by atomic layer deposition for gate dielectric applications.The ever-increasing demand for functionality and speed for semiconductor applications requires enhanced performance, which is achieved by the continuous miniaturization of CMOS dimensions. Because of this miniaturization, several parameters, such as the dielectric thickness, come within reach of their physical limit. As the required oxide thickness approaches the sub- l nm range, SiO 2 become unsuitable as a gate dielectric because its limited physical thickness results in excessive leakage current through the gate stack, affecting the long-term reliability of the device. This leakage issue is solved in the 45 mn technology node by the integration of high-k based gate dielectrics, as their higher k-value allows a physically thicker layer while targeting the same capacitance and Equivalent Oxide Thickness (EOT). Moreover, Intel announced that Atomic Layer Deposition (ALD) would be applied to grow these materials on the Si substrate. ALD is based on the sequential use of self-limiting surface reactions of a metallic and oxidizing precursor. This self-limiting feature allows control of material growth and properties at the atomic level, which makes ALD well-suited for the deposition of highly uniform and conformal layers in CMOS devices, even if these have challenging 3D topologies with high aspect-ratios. ALD has currently acquired the status of state-of-the-art and most preferred deposition technique, for producing nano layers of various materials of technological importance. This technique can be adapted to different situations where precision in thickness and perfection in structures are required, especially in the microelectronic scenario.

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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

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Optimum conditions and experimental details for the formation of v-Fe203 from goethite have been worked out. In another method, a cheap complexing medium of starch was employed for precipitating acicular ferrous oxalate, which on decomposition in nitrogen and subsequent oxidation yielded acicular y-Fe203. On the basis of thermal decomposition in dry and moist nitrogen, DTA, XRD, GC and thermodynamic arguments, the mechanism of decomposition was elucidated. New materials obtained by doping ~'-Fe203 with 1-16 atomic percent magnesium, cobalt, nickel and copper, were synthesised and characterized