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Shiv Nadar University

Center for Informatics

The objective of this study was to develop a unified data-driven correlation for the overall gas hold-up for various gas-liquid systems using support vector regression (SVR)-based modeling technique. Over the years, researchers have amply quantified the hydrodynamics of bubble column reactors in terms of the overall gas hold-up. In this work, about 1810 experimental points were collected from 40 open sources spanning the years 1965-2007. The model for overall gas hold-up was established as a function of several parameters which include superficial gas velocity, superficial liquid velocity, gas density, molecular weight of gas, sparger type, sparger hole diameter, number of sparger holes, liquid viscosity, liquid density, liquid surface tension, operating temperature, operating pressure and column diameter of the gas-liquid system. For understanding the hold-up behavior, the data used for training the model was grouped into various gas-liquid systems viz., air-water, gas-aqueous viscous liquids, gas-organic liquids, gas-aqueous electrolyte solutions and gas-liquid systems operated over a wide range of pressure. A generalized model established using SVR was evaluated for its performance for various gas-liquid systems. Statistical analysis showed that the proposed generalized SVR-based correlation for overall gas hold-up has prediction accuracy of 97% with average absolute relative error (% AARE) of 12.11%. A comparison of this correlation with the selected system specific correlations in the literature showed that the developed SVR-based correlation significantly gives enhanced prediction of overall gas hold-up. © 2007.

World University root node

Chemical Engineering Science

Development of support vector regression (SVR)-based correlation for prediction of overall gas hold-up in bubble column reactors for various gas-liquid systems

Perovskite-type RRh3B and RRh3C (R = Y, Sc) form a continuous solid solution, RRh3BxC1-x, in the range of 0 ≦ x ≦ 1 with cubic structure (space group: Pm3m, Z = 1). The values of the microhardness of YRh3BxC1-x for x = 0, 0.25, 0.50, 0.75 and 1.00 are investigated as 4.4 ± 0.1, 4.9 ± 0.1, 5.5 ± 0.2, 6.4 ± 0.2 and 7.5 ± 0.15 GPa, respectively. On the other hand, the values of the microhardness of ScRh 3BxC1-x for x = 0, 0.25, 0.50, 0.75 and 1.00 are 4.5 ± 0.2, 6.1 ± 0.2, 7.4 ± 0.2, 8.9 ± 0.2 and 9.6 ± 0.1 GPa, respectively. Thus, the microhardness of RRh 3BxC1-x continuously becomes larger with increasing boron content. The oxidation onset temperatures of YRh 3BxC1-x for x = 0, 0.25, 0.50, 0.75 and 1.00 are 604, 631, 655, 687 and 978 K, respectively. On the other hand, the oxidation onset temperatures of ScRh3BxC1-x for x = 0, 0.25, 0.50, 0.75 and 1.00 are 674, 675, 695, 725 and 753 K, respectively. Thermogravimetric analysis of the phase indicates that the oxidation onset temperature also increases with boron content. Thus, it appears that both mechanical strength and chemical stability of the RRh 3BxC1-x phase essentially depend on its boron content. Ab initio calculations have been performed to obtain the equilibrium lattice constants and the bulk moduli. The calculated lattice constants are in excellent agreement with experimental results. {\textcopyright} 2005 Elsevier B.V. All rights reserved.

Journal of Alloys and Compounds

Hardness and oxidation resistance of the perovskite-type RRh 3BxC1-x (R = Y, Sc)

Atomic structures of MonO2n, n = 1-6 clusters are studied using first principles calculations and are compared with those obtained for MonS2n clusters. The lowest energy isomers of MonO2n differ significantly from those of MonS2n for n > 3. Oxygen atoms favor to bind with two Mo atoms, while S atoms are bonded with three Mo atoms. However, the clustering of Mo atoms is generally favored xin both cases due to the partially occupied d-orbitals. The lowest energy isomers of MonO2n have larger HOMO-LUMO gaps than the values for MonS2n clusters and for n = 1 and 4 the clusters are magnetic. {\textcopyright} 2006 Elsevier B.V. All rights reserved.

Chemical Physics Letters

Bonding nature and magnetism in small MoX2 (X = O and S) clusters - A comparative study by first principles calculations

First principles calculations have been performed on perovskite-type RRh3B and RRh3C (R = Sc, Y and La) compounds to obtain the equilibrium lattice constants and elastic properties such as the elastic constants, bulk moduli, shear moduli and Young's moduli. The calculated lattice constants are in excellent agreement with the experimental results. A new relationship between the bulk modulus and the nearest neighbor distance is proposed for the present systems. {\textcopyright} 2005 Elsevier B.V. All rights reserved.

Computational Materials Science

A first principles study of the elastic properties in perovskite-type RRh3B and RRh3C with R = Sc, y and La

The origin of spontaneous electric dipole moments and uncoupled magnetic moments, observed in niobium clusters below a size dependent critical temperature, are explained using first-principles electronic structure calculations. The calculated dipole moments for NbN (N=2-15) generally agree with the experiment and support the interpretation that the electric dipole has a structural origin. A strong correlation is found between structural asymmetry, as quantified by the inertial moments and charge deformation density and the electric dipole. For clusters with odd N, magnetocrystalline anisotropy is small in comparison to the rotational energy of the cluster, such that the spin magnetic moment (1 $\mu$B) is uncoupled to the cluster. Two potential mechanisms to explain the temperature dependence of the electric dipole are investigated. The excitation of harmonic vibrations is unable to explain the observed temperature dependence. However, classical simulations of the deflection of a cluster in a molecular beam show that thermal averaging reduces the asymmetry of the deflection profile at higher temperatures, which may affect the experimental observation of the electric dipole and polarizability. An experimental test is proposed to ascertain the importance of this effect. {\textcopyright} 2006 The American Physical Society.

Physical Review B - Condensed Matter and Materials Physics

Origin and temperature dependence of the electric dipole moment in niobium clusters

Physical Review-Section B-Condensed Matter

{Surface physics, nanoscale physics, low-dimensional systems-Thickness dependence of the atomic and electronic structures of TiO2 rutile (110) slabs and the effects on the {\ldots}}

Motivation: Inclusion body formation has been a major deterrent for overexpression studies since a large number of proteins form insoluble inclusion bodies when overexpressed in Escherichia coli. The formation of inclusion bodies is known to be an outcome of improper protein folding; thus the composition and arrangement of amino acids in the proteins would be a major influencing factor in deciding its aggregation propensity. There is a significant need for a prediction algorithm that would enable the rational identification of both mutants and also the ideal protein candidates for mutations that would confer higher solubility-on-overexpression instead of the presently used trial-and-error procedures. Results: Six physicochemical properties tog ether with residue and dipeptide-compositions have been used to develop a support vector machine-based classifier to predict the overexpression status in. The prediction accuracy is ∼72% suggesting that it performs reasonably well in predicting the propensity of a protein to be soluble or to form inclusion bodies. The algorithm could also correctly predict the change in solubility for most of the point mutations reported in literature. This algorithm can be a useful tool in screening protein libraries to identify soluble variants of proteins. © The Author 2005. Published by Oxford University Press. All rights reserved.

Fulltext

Bioinformatics

A support vector machine-based method for predicting the propensity of a protein to be soluble or to form inclusion body on overexpression in Escherichia coli

A new method for model selection in prediction of time series is proposed. Apart from the conventional criterion of minimizing RMS error, the method also minimizes the error on the distribution of singularities, evaluated through the local Hölder estimates and its probability density spectrum. Predictions of two simulated and one real time series have been done using kernel principal component regression (KPCR) and model parameters of KPCR have been selected employing the proposed as well as the conventional method. Results obtained demonstrate that the proposed method takes into account the sharp changes in a time series and improves the generalization capability of the KPCR model for better prediction of the unseen test data. © 2006 IOP Publishing Ltd.