Statistical Modeling Studies of Iron Recovery from Red Mud Using Thermal Plasma

Optimization studies of plasma smelting of red mud were carried out. Reduction of the dried red mud fines was done in an extended arc plasma reactor to recover the pig iron. Lime grit and low ash metallurgical (LAM) coke were used as the flux and reductant, respectively. 2level factorial design was used to study the influence of all parameters on the responses. Response surface modeling was done with the data obtained from statistically designed experiments. Metal recovery at optimum parameters was found to be 79.52%.     

Ultrasound assisted synthesis of PMMA/clay nanocomposites: Study of oxygen permeation and flame retardant properties

PMMA/clay nanocomposites were synthesized by ultrasound assisted emulsifier-free emulsion polymerization technique. Ultrasound waves of different power and frequencies were applied to enhance the dispersion of the clay layers with polymer matrix. The structural information of the synthesized materials was studied by X-ray diffraction (XRD) and it was revealed that the interlayer spacing increased with clay loading. The magnitude of dispersion of the clay in the polymer matrix was detected by transmission electron microscopy (TEM). The Young’s modulus, breaking stress, elongation at break, toughness, yield stress and yield strain of the nanocomposites as a function of different clay concentrations and ultrasonic power were measured. Particle diameter of the nanocomposites was measured by laser diffraction technique. Oxygen permeability of the samples was studied and it was found that the oxygen flow rate was reduced by the combined effect of clay loading and ultrasound. The flame retardant property of the nanocomposites due to clay dispersion was investigated by measurement of limiting oxygen index (LOI).     

Post irradiated microstructural characterization of Zr–1Nb alloy by X-ray diffraction technique and positron annihilation spectroscopy

Zr–1Nb samples were irradiated with 116 MeV O^5 + ions at different doses ranging from 5 × 10¹⁷ to 8 × 10¹⁸ O^5 +/m². X-ray diffraction line profile analysis was performed to characterize the microstructural parameters of these samples. Average domain size, microstrain and dislocation density were estimated as a function of dose. An anomaly was observed in the values of these parameters at a dose of 2 × 10¹⁸ O^5 +/m². Positron annihilation spectroscopy was used to determine the existence and nature of vacancy clusters in the samples. Isochronal annealing was carried out for a sample to study the evolution of defect clusters.     

A component‐by‐component characterisation of high‐risk atherosclerotic plaques by multiphoton microscopic imaging

Aims: Atherosclerotic plaques vulnerable to rupture are almost always inflamed, and carry a large lipid core covered by a thin fibrous cap. The other components may include neovascularisation, intraplaque haemorrhage and spotty calcification. In contrast, stable plaques are characterised by a predominance of smooth muscle cells and collagen, and lipid core is usually deep seated or absent. This study is a proof of principle experiment to evaluate the feasibility of multiphoton microscopy (MPM) to identify aforementioned plaque components. Methods and Results: MPM is a nonlinear optical technique that allows imaging based on intrinsic tissue signals including autofluorescence and higher‐order scattering. In our study, MPM imaging was performed on morphologically diverse aortic and coronary artery plaques obtained during autopsy. Various histologically verified plaque components including macrophages, cholesterol crystals, haemorrhage, collagen and calcification were recognised by MPM. Conclusions: Recognition of the distinct signatures of various plaque components suggests that MPM has the potential to offer next‐generation characterisation of atherosclerotic plaques. The higher lateral resolution (comparable to histology) images generated by MPM for identifying plaque components might complement larger field of view and greater imaging depth currently available with optical coherence tomography imaging. As the next step MPM would need to be evaluated for intact vessel imaging ex vivo and in vivo.     

Optimization analysis on the economy of the electro-discharge machining process using electronic pulse generator

Research is yet to be clone on the direct economy of the electro-discharge machining process which is a vital criterion for the users of the machine. In this paper an expression for contribution rate, as a function of process variables, which is a direct indicator to measure the economic objectives of the process for a production system is derived and a methodology forestimating the process and hence the objective function with respect to the process variables is cited.

Further, in this paper a Complementary Geometric Programming algorithm is used to optimize the contribution rate under technical and technological constraints.

This paper also compares the contribution rates obtained from the results of the optimization problem with the following objective functions under compatible sets of restrictions: (i) Contribution rate. (ii) Material removal rate.

(iii) Electrode wear rate.

(iv) Ratio of material removal rate to electrode wear rate.

The data, for this paper is generated from JUSPA III, the electro-discharge machine based on the electronic pulse generator installed in the Machine Tool Research Laboratory at Jadavpur University, India.     

A note on the correct evaluation of junction capacitance of a solar cell

In the fabrication of low-cost solar cells one has often to contend with finite series and shunt resistances. These tend to give misleading values of the junction capacitance as measured with an ordinary bridge. The problem is discussed analytically and graphical plots are given for determination of the true values from the measured ones. Practical use of these plots is discussed and illustrated with the help of experiments on thin-film Cu₂S-CdS solar cells.     

THE BOUNDARY NODE METHOD FOR POTENTIAL PROBLEMS

The Element-Free Galerkin (EFG) method allows one to use a nodal data structure (usually with an underlying cell structure) within the domain of a body of arbitrary shape. The usual EFG combines Moving Least-Squares (MLS) interpolants with a variational principle (weak form) and has been used to solve two-dimensional (2-D) boundary value problems in mechanics such as in potential theory, elasticity and fracture. This paper proposes a combination of MLS interpolants with Boundary Integral Equations (BIE) in order to retain both the meshless attribute of the former and the dimensionality advantage of the latter! This new method, called the Boundary Node Method (BNM), only requires a nodal data structure on the bounding surface of a body whose dimension is one less than that of the domain itself. An underlying cell structure is again used for numerical integration. In principle, the BNM, for 3-D problems, should be extremely powerful since one would only need to put nodes (points) on the surface of a solid model for an object. Numerical results are presented in this paper for the solution of Laplace's equation in 2-D. Dirichlet, Neumann and mixed problems have been solved, some on bodies with piecewise straight and others with curved boundaries. Results from these numerical examples are extremely encouraging. © 1997 by John Wiley & Sons, Ltd.     

Cobalt nanoparticles as reusable catalysts for reduction of 4-nitrophenol under mild conditions

Facile reduction of p-nitrophenol to p-aminophenol by sodium borohydride catalysed by cobalt nanoparticles (CoNPs) has been discussed. A simple approach has been made to synthesize highly active and ordered structures of CoNPs. The air-stable nanoparticles were prepared from cobalt sulphate using tetrabutyl ammonium bromide as surfactant and sodium borohydride as reductant. The cobalt nanocolloids in aqueous medium were found to be efficient reusable catalysts for the p-nitrophenol reduction. Palladium nanoparticles prepared from palladium chloride and the same surfactant were found to reduce p-nitrophenol but lose their catalytic efficiency after recovery. Based on chemical and kinetic studies, an attempt has been made to elucidate the mechanism of p-nitrophenol reduction using these nanoclusters.     

On grain growth kinetics in two-phase polycrystalline materials through Monte Carlo simulation

Monte Carlo Potts model simulation was carried out on a 2D square lattice for various surface fractions of second phase particles for over 50,000 iterations. The observations are in good agreement with known theoretical and experimental results with respect to both growth kinetics as well as grain size distribution. Further, the average grain size and the largest grain size were computed for various surface fractions which have indicated normal grain growth and microstructure homogeneity. The surface fraction of the second phase particles interacting with the grain boundaries (Φ), hitherto not computed through the simulation route, is shown to vary inversely as the average grain size due to Zener pinning.