Ni(II) and Ru(II) Schiff base complexes as catalysts for the reduction of benzene

Two new complexes, [MII(L)(Cl)(H2O)2]·H2O (where M=Ni or Ru and L = heterocyclic Schiff base, 3- hydroxyquinoxaline-2-carboxalidene-4-aminoantipyrine), have been synthesized and characterized by elemental analysis, FT-IR, UV–vis diffuse reflectance spectroscopy, FAB-MASS, TG–DTA, AAS, cyclic voltammetry, conductance and magnetic susceptibility measurements. The complexes have a distorted octahedral structure andwere found to be effective catalysts for the hydrogenation of benzene. The influence of several reaction parameters such as reaction time, temperature, hydrogen pressure, concentration of the catalyst and concentration of benzenewas tested. A turnover frequency of 5372 h−1 has been found in the case of ruthenium complex for the reduction of benzene at 80 ◦C with 3.64×10−6 mol catalyst, 0.34 mol benzene and at a hydrogen pressure of 50 bar. In the case of the nickel complex, a turnover frequency of 1718 h−1 has been found for the same reaction with 3.95×10−6 mol catalyst under similar experimental conditions. The nickel complex shows more selectivity for the formation of cyclohexene while the ruthenium complex is more selective for the formation of cyclohexane

Alkylation of Benzene with I-Octene over Titania Pillared Monmorillonite

Linear alkylbenzene sulfonic acid, the largest-volume synthetic surfactant, in addition to its excellent performance , is important due to its biodegradable environmental friendliness, as it has a straight chain and is prepared by the sulphonation of linear alkylbenzenes (LAB). To ensure environmental protection, the commercial benzene alkylation catalysts HF or AICI3 are replaced and we have developed a clean LAB production process using a pillared clay catalyst capable of not only replacing the conventional homogeneous catalyst, but also having high selectivity for the best biodegradable 2-phenyl LAB isomer .Pillared clay catalysts having high Bronsted acidity show efficient conversion in gas phase alkylation of benzene with 1-octene with a good 2-phenyl octane selectivity.

Thermochemistry of Charge-Transfer Complexes of 7,7,8,8-Tetracyanoquinodimethane with Benzene and Its Chloro Derivatives

The enthalpies of formation of charge-transfer complexes of benzene, chlorobenzene, and 1,3-dichlorobenzene as donors with 7,7,8,8-tetracyanoquinodimethane as acceptor were determined. The thermochemical data show an increased stability of charge-transfer complexes of donors with permanent dipole moment. The results confirm the importance of electrostatic forces in bonding and stabilizing weak complexes. The approximate formation constants of the complexes are also reported.

Influence of residual cations (Na+, K+ and Mg2+) in the alkylation activity of benzene with 1-octene over rare earth metal ion exchanged FAU–Y zeolite

The effect of residual cations in rare earth metal modified faujasite–Y zeolite has been monitored using magic angle spinning NMR spectral analysis and catalytic activity studies. The second metal ions being used are Na+, K+ and Mg+. From a comparison of the spectra of different samples, it is concluded that potassium and magnesium exchange causes a greater downfield shift in the 29Si NMR peaks. Also, lanthanum exchanged samples show migration behavior from large cages to small cages, which causes the redistribution of second counter cations. It is also observed that Mg2+ causes the most effective migration of lanthanum ions due to its greater charge. The prepared systems were effectively employed for the alkylation of benzene with 1-octene in the vapor phase. From the deactivation studies it is observed that the as-exchanged zeolites possess better stability towards reaction condition over the pure HFAU zeolite.

Modeling and Analysis of Some Heavy Tailed Time Series

The thesis has covered various aspects of modeling and analysis of finite mean time series with symmetric stable distributed innovations. Time series analysis based on Box and Jenkins methods are the most popular approaches where the models are linear and errors are Gaussian. We highlighted the limitations of classical time series analysis tools and explored some generalized tools and organized the approach parallel to the classical set up. In the present thesis we mainly studied the estimation and prediction of signal plus noise model. Here we assumed the signal and noise follow some models with symmetric stable innovations.We start the thesis with some motivating examples and application areas of alpha stable time series models. Classical time series analysis and corresponding theories based on finite variance models are extensively discussed in second chapter. We also surveyed the existing theories and methods correspond to infinite variance models in the same chapter. We present a linear filtering method for computing the filter weights assigned to the observation for estimating unobserved signal under general noisy environment in third chapter. Here we consider both the signal and the noise as stationary processes with infinite variance innovations. We derived semi infinite, double infinite and asymmetric signal extraction filters based on minimum dispersion criteria. Finite length filters based on Kalman-Levy filters are developed and identified the pattern of the filter weights. Simulation studies show that the proposed methods are competent enough in signal extraction for processes with infinite variance.Parameter estimation of autoregressive signals observed in a symmetric stable noise environment is discussed in fourth chapter. Here we used higher order Yule-Walker type estimation using auto-covariation function and exemplify the methods by simulation and application to Sea surface temperature data. We increased the number of Yule-Walker equations and proposed a ordinary least square estimate to the autoregressive parameters. Singularity problem of the auto-covariation matrix is addressed and derived a modified version of the Generalized Yule-Walker method using singular value decomposition.In fifth chapter of the thesis we introduced partial covariation function as a tool for stable time series analysis where covariance or partial covariance is ill defined. Asymptotic results of the partial auto-covariation is studied and its application in model identification of stable auto-regressive models are discussed. We generalize the Durbin-Levinson algorithm to include infinite variance models in terms of partial auto-covariation function and introduce a new information criteria for consistent order estimation of stable autoregressive model.In chapter six we explore the application of the techniques discussed in the previous chapter in signal processing. Frequency estimation of sinusoidal signal observed in symmetric stable noisy environment is discussed in this context. Here we introduced a parametric spectrum analysis and frequency estimate using power transfer function. Estimate of the power transfer function is obtained using the modified generalized Yule-Walker approach. Another important problem in statistical signal processing is to identify the number of sinusoidal components in an observed signal. We used a modified version of the proposed information criteria for this purpose.

Threshold Autoregressive Model for a Time Series Data

In this paper we try to fit a threshold autoregressive (TAR) model to time series data of monthly coconut oil prices at Cochin market. The procedure proposed by Tsay [7] for fitting the TAR model is briefly presented. The fitted model is compared with a simple autoregressive (AR) model. The results are in favour of TAR process. Thus the monthly coconut oil prices exhibit a type of non-linearity which can be accounted for by a threshold model.

ARMA modeling of time series based on rational approximation of spectral density function

This study is concerned with Autoregressive Moving Average (ARMA) models of time series. ARMA models form a subclass of the class of general linear models which represents stationary time series, a phenomenon encountered most often in practice by engineers, scientists and economists. It is always desirable to employ models which use parameters parsimoniously. Parsimony will be achieved by ARMA models because it has only finite number of parameters. Even though the discussion is primarily concerned with stationary time series, later we will take up the case of homogeneous non stationary time series which can be transformed to stationary time series. Time series models, obtained with the help of the present and past data is used for forecasting future values. Physical science as well as social science take benefits of forecasting models. The role of forecasting cuts across all fields of management-—finance, marketing, production, business economics, as also in signal process, communication engineering, chemical processes, electronics etc. This high applicability of time series is the motivation to this study.

Alkylation of Benzene with higher olefins over zeolites: A green route for lab synthesis.

The objective of the present work is to improve the textural and structural properties of zeolite-Y through ion exchange with rare earth metals. We meant to obtain a comparative evaluation of the physicochemical properties and catalytic activity of rare earth modified H-Y, Na-Y, K-Y, and Mg-Y zeolites. Friedel-Crafts alkylations of benzene with higher 1- olefins such as 1-octene, 1-decene, and 1dodecene for the synthesis of linear alkylbenzene (LAB) have been selected for the present study. An attempt has also been directed towards the correlation of the enhancement in 2-phenylalkane formation to the improvement in the textural and structural properties upon rare earth modification for the zeolite-Y. The present method for LAB synthesis stands as an effective Green alternative for the existing hydrofluoric acid technology

High Selectivity Filter Employing Stepped Impedance Resonators, Series Capacitors and Defected Ground Structures for Ultra Wide Band Applications

The paper presents a compact planar Ultra Wide Band ¯lter employing folded stepped impedance resonators with series capacitors and dumb bell shaped defected ground structures. An interdigital quarter wavelength coupled line is used for achieving the band pass characteristics. The transmission zeros are produced by stepped impedance resonators. The ¯lter has steep roll o® rate and good attenuation in its lower and upper stop bands, contributed by the series capacitor and defected ground structures respectively.

Enhancement of Calcifications in Mammograms using Volterra Series based Quadratic Filter

The paper summarizes the design and implementation of a quadratic edge detection filter, based on Volterra series, for enhancing calcifications in mammograms. The proposed filter can account for much of the polynomial nonlinearities inherent in the input mammogram image and can replace the conventional edge detectors like Laplacian, gaussian etc. The filter gives rise to improved visualization and early detection of microcalcifications, which if left undetected, can lead to breast cancer. The performance of the filter is analyzed and found superior to conventional spatial edge detectors

Estimation of the ground state correlation energy for isoelectronic series of 2 to 20 electrons

Correlation energies for all isoelectronic sequences of 2 to 20 electrons and Z = 2 to 25 are obtained by taking differences between theoretical total energies of Dirac-Fock calculations and experimental total energies. These are pure relativistic correlation energies because relativistic and QED effects are already taken care of. The theoretical as well as the experimental values are analysed critically in order to get values as accurate as possible. The correlation energies obtained show an essentially consistent behaviour from Z = 2 to 17. For Z > 17 inconsistencies occur indicating errors in the experimental values which become very large for Z > 25.

Algorithmic Computation of Formal Fourier Series

KAAD (Katholischer Akademischer Ausländer-Dienst)

On-the-Fly Maintenance of Series-Parallel Relationships in Fork-Join Multithreaded Programs

A key capability of data-race detectors is to determine whether one thread executes logically in parallel with another or whether the threads must operate in series. This paper provides two algorithms, one serial and one parallel, to maintain series-parallel (SP) relationships "on the fly" for fork-join multithreaded programs. The serial SP-order algorithm runs in O(1) amortized time per operation. In contrast, the previously best algorithm requires a time per operation that is proportional to Tarjan’s functional inverse of Ackermann’s function. SP-order employs an order-maintenance data structure that allows us to implement a more efficient "English-Hebrew" labeling scheme than was used in earlier race detectors, which immediately yields an improved determinacy-race detector. In particular, any fork-join program running in T₁ time on a single processor can be checked on the fly for determinacy races in O(T₁) time. Corresponding improved bounds can also be obtained for more sophisticated data-race detectors, for example, those that use locks. By combining SP-order with Feng and Leiserson’s serial SP-bags algorithm, we obtain a parallel SP-maintenance algorithm, called SP-hybrid. Suppose that a fork-join program has n threads, T₁ work, and a critical-path length of T[subscript ∞]. When executed on P processors, we prove that SP-hybrid runs in O((T₁/P + PT[subscript ∞]) lg n) expected time. To understand this bound, consider that the original program obtains linear speed-up over a 1-processor execution when P = O(T₁/T[subscript ∞]). In contrast, SP-hybrid obtains linear speed-up when P = O(√T₁/T[subscript ∞]), but the work is increased by a factor of O(lg n).