On the magnetic properties of ultra-Þne zinc ferrites

Zinc ferrite belongs to the class of normal spinels where it is assumed to have a cation distribution of Zn2`(Fe3`)2(O2~)4, and it is purported to be showing zero net magnetisation. However, there have been recent reports suggesting that zinc ferrite exhibits anomaly in its magnetisation. Zinc ferrite samples have been prepared by two di¤erent routes and have been analysed using low energy ion scattering, Mo¬ ssbauer spectroscopy and magnetic measurements. The results indicate that zinc occupies octahedral sites, contrary to the earlier belief that zinc occupies only the tetrahedral sites in a normal spinel. The amount of zinc on the B site increases with decrease in particle size. The LEIS results together with the Mo¬ ssbauer results and the magnetic measurements lead to the conclusion that zinc occupies the B site and the magnetisation exhibited by ultraÞne particles of zinc is due to short range ordering

Preferential exposure of certain crystallographic planes on the surface of spinel ferrites: a study by LEIS on polycrystalline spinel ferrite surfaces

Spinel ferrites are commercially important because of their excellent magnetic and catalytic properties. The study by Low Energy Ion Scattering (LEIS) can reveal atomic scale information on the surface. The surface of selected spinel ferrites was investigated by LEIS. It has been found that it is the octahedral sites which are preferentially exposed on the surface of the spinel ferrites. So the probable planes which are exposed on spinel ferrite surfaces are D(110) or B(111). This prediction using LEIS gives scope for tailor-making compounds with catalytically active ions on the surface for various catalytic reactions.

Cure Characteristics and Mechanical Properties of Rubber Ferrite Composites Based on Nano-Nickel Ferrites

Ultra fine nickel ferrite have been synthesized by the sol-gel method. By heat treating different portions of the prepared powder separately at different temperatures, nano-sized particles of nickel ferrite with varying particle sizes were obtained. These powders were characterised by the X-ray diffraction and then incorporated in the nitrile rubber matrix according to a specific recipe for various loadings. The cure characteristics and the mechanical properties of these rubber ferrite composites (RFCs) were evaluated. The effect of loading and the grain size of the filler on the cure characteristics and tensile properties were also evaluated. It is found that the grain size and porosity of the filler plays a vital role in determining the mechanical properties of the RFCs

Development of Hierarchical Clustering Techniques for Gridded Data from Mixed Data Sequences

Knowledge discovery in databases is the non-trivial process of identifying valid, novel potentially useful and ultimately understandable patterns from data. The term Data mining refers to the process which does the exploratory analysis on the data and builds some model on the data. To infer patterns from data, data mining involves different approaches like association rule mining, classification techniques or clustering techniques. Among the many data mining techniques, clustering plays a major role, since it helps to group the related data for assessing properties and drawing conclusions. Most of the clustering algorithms act on a dataset with uniform format, since the similarity or dissimilarity between the data points is a significant factor in finding out the clusters. If a dataset consists of mixed attributes, i.e. a combination of numerical and categorical variables, a preferred approach is to convert different formats into a uniform format. The research study explores the various techniques to convert the mixed data sets to a numerical equivalent, so as to make it equipped for applying the statistical and similar algorithms. The results of clustering mixed category data after conversion to numeric data type have been demonstrated using a crime data set. The thesis also proposes an extension to the well known algorithm for handling mixed data types, to deal with data sets having only categorical data. The proposed conversion has been validated on a data set corresponding to breast cancer. Moreover, another issue with the clustering process is the visualization of output. Different geometric techniques like scatter plot, or projection plots are available, but none of the techniques display the result projecting the whole database but rather demonstrate attribute-pair wise analysis