Study of cyclohexanol decomposition reaction over the ferrospinels, A1−xCuxFe2O4 (A=Ni or Co and x=0, 0.3, 0.5, 0.7 and 1), prepared by ‘soft’ chemical methods

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.

Influence of surface and acid properties of vanadia supported on ceria promoted with rice husk silica on cyclohexanol decomposition

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.

Studies on the Surface Properties and Catalytic Activity of Metal Chromites on Thermal Decomposition of Ammonium Perchlorate

Department of Applied Chemistry, Cochin University of Science and Technology

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