Crystal Structures and Spectral Aspects of Mixed Ligand Transition Metal Chelates Derived from Aldehyde based ONS Donor Thiosemicarbazones

Thiosemicarbazones have emerged as an important class of ligands over a period of time, for a variety of reasons, such as variable donor properties, structural diversity and biological applications. Interesting as the coordination chemistry may be, the driving force for the study of these ligands has undoubtedly been their biological properties and the majority of the 3000 or so publications on thiosemicarbazones since 2000 have alluded to this feature. Thiosemicarbazones with potential donor atoms in their structural skeleton fascinate coordination chemists with their versatile chelating behavior. The thiosemicarbazones of aromatic aldehydes and ketones form stable chelates with transition metal cations by utilizing both their sulfur and azomethine nitrogen as donor atoms. They have been shown to possess a diverse range of biological activities including anticancer, antitumor, antibacterial, antiviral, antimalarial and antifungal properties owing to their ability to diffuse through the semipermeable membrane of the cell lines. The enhanced effect may be attributed to the increased lipophilicity of the metal complexes compared to the ligand alone.

Acid-Base. Surface Electron Donatin6 &.Catai.Ytlc Properties Of Some Binary Mixed Oxides Containing Rare Earth Elements

Catalysis research underpins the science of modern chemical processing and fuel technologies. Catalysis is commercially one of the most important technologies in national economies. Solid state heterogeneous catalyst materials such as metal oxides and metal particles on ceramic oxide substrates are most common. They are typically used with commodity gases and liquid reactants. Selective oxidation catalysts of hydrocarbon feedstocks is the dominant process of converting them to key industrial chemicals, polymers and energy sources.[1] In the absence of a unique successfiil theory of heterogeneous catalysis, attempts are being made to correlate catalytic activity with some specific properties of the solid surface. Such correlations help to narrow down the search for a good catalyst for a given reaction. The heterogeneous catalytic performance of material depends on many factors such as [2] Crystal and surface structure of the catalyst. Thermodynamic stability of the catalyst and the reactant. Acid- base properties of the solid surface. Surface defect properties of the catalyst.Electronic and semiconducting properties and the band structure. Co-existence of dilferent types of ions or structures. Adsorption sites and adsorbed species such as oxygen.Preparation method of catalyst , surface area and nature of heat treatment. Molecular structure of the reactants. Many systematic investigations have been performed to correlate catalytic performances with the above mentioned properties. Many of these investigations remain isolated and further research is needed to bridge the gap in the present knowledge of the field.

eLearning and Semantic Web

Semantic Web: Software agents on the Semantic Web may use commonly agreed service language, which enables co-ordination between agents and proactive delivery of learning materials in the context of actual problems. The vision is that each user has his own personalized agent that communicates with other agents.

Studies On Strength Characteristics Of Soil Mixed With Bio-Waste

Researches are always in quest for finding innovative methods for ground improvement using sustainable and environmental friendly solutions. Theproduction of large quantity of biowastes all over the world faces serious problems of handling and disposal. Coir pith is a biowaste from coir industry and sugarcane baggase is another biowaste obtained after extractingjuice from sugar cane. So the present study is an investigation into the effect of coir pith and sugarcane baggase on some geotechnical properties of red earth. The investigation includes study on variation of properties such as O.M.C, maximum dry density, C.B.R. values,unconfined compressive strength and permeability when these materials are included in soil. Several conclusions are arrived at, on the basis of the experiments conducted and it may be helpful for predicting the behavior of such soil matrix

Magnetic and processability studies on rubber ferrite composites based on natural rubber and mixed ferrite

Polycrystalline single phasic mixed ferrites belonging to the series Ni1−xZnxFe2O4 for various values of x have been prepared by conventional ceramic techniques. Pre-characterized nickel zinc ferrites were then incorporated into a natural rubber matrix according to a specific recipe for various loadings. The processability and cure parameters were then determined. The magnetic properties of the ceramic filler as well as the ferrite loaded rubber ferrite composites (RFC) were evaluated and compared. A general equation for predicting the magnetic properties was also formulated. The validity of these equations were then checked and correlated with the experimental data. The coercivity of the RFCs almost resemble that of the ceramic component in the RFC. Percolation threshold is not reached for a maximum loading of 120 phr (parts per hundred rubber by weight) of the filler. These studies indicate that flexible magnets can be made with appropriate magnetic properties namely saturation magnetisation (Ms) and magnetic field strength (Hc) by a judicious choice of x and a corresponding loading. These studies also suggest that there is no possible interaction between the filler and the matrix at least at the macroscopic level. The formulated equation will aid in synthesizing RFCs with predetermined magnetic

Tailoring magnetic and dielectric properties of rubber ferrite composites containing mixed ferrites

Rubber ferrite composites containing various mixed ferrites were prepared for different compositions and various loadings. The magnetic and dielectric properties of the fillers as well as the ferrite filled matrixes were evaluated separately. The results are correlated. Simple equations are proposed to predetermine the magnetic and dielectric properties. The validity of these equations is verified and they are found to be in good agreement. These equations are useful in tailoring the magnetic and dielectric properties of these composites with predetermined properties

On the dielectric dispersion and absorption in nanosized manganese zinc mixed ferrites

The temperature and frequency dependence of dielectric permittivity and dielectric loss of nanosized Mn1−xZnxFe2O4 (for x = 0, 0.2, 0.4, 0.6, 0.8, 1) were investigated. The impact of zinc substitution on the dielectric properties of the mixed ferrite is elucidated. Strong dielectric dispersion and broad relaxation were exhibited by Mn1−xZnxFe2O4. The variation of dielectric relaxation time with temperature suggests the involvement of multiple relaxation processes. Cole–Cole plots were employed as an effective tool for studying the observed phenomenon. The activation energies were calculated from relaxation peaks and Cole–Cole plots and found to be consistent with each other and indicative of a polaron conduction

Mechanism of ac conduction in nanostructured manganese zinc mixed ferrites

Mn1−xZnxFe2O4 nanoparticles (x = 0 to 1) were synthesized by the wet chemical co-precipitation technique. X-ray diffraction and transmission electron microscopy and high resolution transmission electron microscopy were effectively utilized to investigate the different structural parameters. The ac conductivity of nanosized Mn1−xZnxFe2O4 were investigated as a function of frequency, temperature and composition. The frequency dependence of ac conductivity is analysed by the power law σ(ω)ac = Bωn which is typical for charge transport by hopping or tunnelling processes. The temperature dependence of frequency exponent n was investigated to understand the conduction mechanism in different compositions. The conduction mechanisms are mainly based on polaron hopping conduction

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