A Reliable Method for Recycling (RE)‐Ba‐Cu‐O (RE: Sm,Gd, Y) Bulk Superconductors

Single grain (RE)‐Ba‐Cu‐O (RE: Sm, Gd, Y) high‐temperature superconductors are able to generate high magnetic fields. However, the relatively high cost of the raw materials and the low yield of the manufacturing process have impeded the development of practical applications of these materials to date. This article describes a simple, reliable, and economical method of recycling failed bulk (RE)‐Ba‐Cu‐O (RE: Sm, Gd, Y) samples. Sixty‐four failed bulk samples, with diameters up to 31 mm, were recycled with a yield of 90%. The key innovation in this recycling process involves reintroducing the liquid phase into the melt process, which is normally lost during the primary peritectic processing of these materials. This enables the direct re‐growth of failed samples from solid form without the need for re‐grinding into powder. We also demonstrate that the superconducting performance and microstructure of the recycled samples is similar to that of the primary grown samples.     

Analysis of Fatty Acid and Lignan Composition of Indian Germplasm of Sesame to Evaluate Their Nutritional Merits

An attempt was made to individually analyze a germplasm collection of 54 indigenous Indian sesame cultivars for fatty acid and lignan composition of their seed oil by gas chromatography and high performance liquid chromatography, respectively. The entries varied in their fatty acid and lignan composition. The mean percentage contents of palmitic, stearic, oleic, linoleic and α‐linolenic acids ranged between 10–22, 5–10, 38–50, 18–43 and less than 1 whereas sesamol, sesamin and sesamolin scored between 3–37, 27–67, 20–59 of the total percentage of lignan, respectively. The highest percentage of α‐linolenic acid (ALA) was obtained in Var‐9 (1.3 % of the total fatty acids). Among the lignans, high sesamin content is considered to be significant, particularly in terms of long shelf life and nutraceutical value of sesame seed oil. The study has broadened our understanding related to differential biochemical composition of the rich sesame germplasms, thereby providing us with a useful groundwork for identifying potential targets and suitable cultivars for genetic engineering approaches to be undertaken in order to improve the nutritional quality of sesame oil, which in turn would be beneficial towards human health.     

Carbon Doping in Boron Suboxide: Structure,Energetics, and Elastic Properties

The structural, electronic, and elastic properties of pristine and carbon‐doped boron suboxide (B₆O) are calculated using density functional theory. The results indicate that it is energetically preferable for a single carbon atom to substitute into an oxygen site rather than a boron site. The lattice parameters and cell volume increase to relieve the residual stress created by the carbon substitution. The interstitial position is not favorable for a single atom substitution. However, if two carbon atoms substitute for two neighboring oxygen atoms, then it becomes energetically favorable to dope an interstitial oxygen, boron, or carbon atom along the C–C chain. If the interstitial dopant is either boron or carbon, a local B₄C‐like structure with either a C–B–C or C–C–C chain is created within the boron suboxide unit cell. The resulting structure shows improvements in the bulk modulus at the expense of the shear and Young's moduli. The moduli further improve if an additional carbon is substituted within a polar or equatorial site of the neighboring B₁₂ icosahedron. Based on these calculations, we conclude that carbon doping can either harden or soften B₆O depending on the manner in which the substitutions are populated. Furthermore, as B₆O samples are often oxygen deficient, C doping can occupy such sites and improve the elastic properties.     

Phase Evolution,Magnetic, Optical,and Dielectric Properties of Zr‐Substituted Bi0.9Gd0.1FeO3 Multiferroics

Polycrystalline BiFeO₃ (BFO) and Bi_0.90Gd_0.10Fe_1?xZr_xO₃ (x = 0.0–0.10; BGFZ_x) ceramics were synthesized by solid‐state reaction method. Rietveld analysis of X‐ray diffraction patterns showed that BFO and BGFZ_x = 0.0 samples are stabilized in rhombohedral structure (space group R3c), whereas a small fraction of orthorhombic phase (space group Pn2₁a) is observed for BGFZ_{x = 0.03–0.10} samples. Suppression and disappearance of some Raman modes indicated a structural phase transition with addition of Zr dopant at Fe site. Magnetic measurements exhibited weak ferromagnetic behavior of BGFZ_x samples with increasing Zr⁺⁴ concentrations. The insertion of Gd⁺³ ions at Bi⁺³ sites and nonmagnetic Zr⁺⁴ ions at Fe⁺³ sites in Fe–O–Fe network suppressed the spin cycloid structure of BFO which in turn enhanced the magnetization of these ceramics. Electron spin resonance spectra revealed the breaking of spin cycloid of BFO due to the development of free spins with addition of Zr⁺⁴ dopants at Fe sites. UV–Visible diffuse reflectance spectra showed one d–d crystal field transition and two charge‐transfer (C–T) transitions along with a sharp absorption of light in visible region for all samples. Almost frequency‐independent dielectric constant and dielectric loss along with very low values of dielectric loss indicated greatly improved dielectric properties for BGFZ_{x = 0.03–0.10} samples.     

Synthesis of ultra-small silicon nanoparticles by femtosecond laser ablation of porous silicon

We report a detailed study on the synthesis of ultra-small (1–10 nm) colloidal silicon nanoparticles (Si NPs) by ablating porous silicon (pSi) in acetone using femtosecond laser pulses. Porous silicon is considered as a target material for ablation because it contains a large number of light emitting silicon nanoparticles. The pSi samples were prepared by anodic etching of silicon in aqueous HF solution for different etching current densities. Transmission electron microscope measurements confirmed the successful formation of well-isolated spherical silicon nanoparticles. The average size of spherical NPs were estimated to be ~7.6, ~7, and ~6 nm when anodic etching current densities of 5, 10, and 20 mA/cm² were used respectively for preparing pSi targets. The crystallinity of these Si NPs was confirmed by selective area electron diffraction and Raman spectroscopy measurements. The observed blue shift in the absorption and emission spectra are attributed to reduction in the average particle size with increase in etching current density. These Si NPs may be useful for fabricating low-dimensional microelectronic compatible photonic devices.     

A non‐intrusive model reduction approach for polynomial chaos expansion using proper orthogonal decomposition

In this paper, a non‐intrusive stochastic model reduction scheme is developed for polynomial chaos representation using proper orthogonal decomposition. The main idea is to extract the optimal orthogonal basis via inexpensive calculations on a coarse mesh and then use them for the fine‐scale analysis. To validate the developed reduced‐order model, the method is implemented to: (1) the stochastic steady‐state heat diffusion in a square slab; (2) the incompressible, two‐dimensional laminar boundary‐layer over a flat plate with uncertainties in free‐stream velocity and physical properties; and (3) the highly nonlinear Ackley function with uncertain coefficients. For the heat diffusion problem, the thermal conductivity of the slab is assumed to be a stochastic field with known exponential covariance function and approximated via the Karhunen–Loève expansion. In all three test cases, the input random parameters are assumed to be uniformly distributed, and a polynomial chaos expansion is found using the regression method. The Sobol's quasi‐random sequence is used to generate the sample points. The numerical results of the three test cases show that the non‐intrusive model reduction scheme is able to produce satisfactory results for the statistical quantities of interest. It is found that the developed non‐intrusive model reduction scheme is computationally more efficient than the classical polynomial chaos expansion for uncertainty quantification of stochastic problems. The performance of the developed scheme becomes more apparent for the problems with larger stochastic dimensions and those requiring higher polynomial order for the stochastic discretization. Copyright © 2015 John Wiley & Sons, Ltd.     

A hybrid optimization model for proficient bidding strategies with no Karush–Kuhn–Tucker optimality conditions

The computational complexity behind the bi‐level optimization problem has led the researchers to adopt Karush–Kuhn–Tucker (KKT) optimality conditions. However, the problem function has more number of complex constraints to be satisfied. Classical optimization algorithms are impotent to handle the function. This paper presents a simplified minimization function, in which both the profit maximization problem and the ISO market clearance problem are considered, but with no KKT optimality conditions. Subsequently, this paper solves the minimization function using a hybrid optimization algorithm. The hybrid optimization algorithm is developed by combining the operations of group search optimizer (GSO) and genetic algorithm (GA). The hybridization enables the dispersion process of GSO to be a new mutated dispersion process for improving the convergence rate. We evaluate the methodology by experimenting on IEEE 14 and IEEE 30 bus systems. The obtained results are compared with the outcomes of bidding strategies that are based on GSO, PSO, and GA. The results demonstrate that the hybrid optimization algorithm solves the minimization function better than PSO, GA, and GSO. Hence, the profit maximization in the proposed methodology is relatively better than that of the conventional algorithms. Copyright © 2015 John Wiley & Sons, Ltd.     

Magnetic resonance image denoising using nonlocal maximum likelihood paradigm in DCT‐framework

The data acquired by magnetic resonance (MR) imaging system are inherently degraded by noise that has its origin in the thermal Brownian motion of electrons. Denoising can enhance the quality (by improving the SNR) of the acquired MR image, which is important for both visual analysis and other post processing operations. Recent works on maximum likelihood (ML) based denoising shows that ML methods are very effective in denoising MR images and has an edge over the other state‐of‐the‐art methods for MRI denoising. Among the ML based approaches, the Nonlocal maximum likelihood (NLML) method is commonly used. In the conventional NLML method, the samples for the ML estimation of the unknown true pixel are chosen in a nonlocal fashion based on the intensity similarity of the pixel neighborhoods. Euclidean distance is generally used to measure this similarity. It has been recently shown that computing similarity measure is more robust in discrete cosine transform (DCT) subspace, compared with Euclidean image subspace. Motivated by this observation, we integrated DCT into NLML to produce an improved MRI filtration process. Other than improving the SNR, the time complexity of the conventional NLML can also be significantly reduced through the proposed approach. On synthetic MR brain image, an average improvement of 5% in PSNR and 86%reduction in execution time is achieved with a search window size of 91 × 91 after incorporating the improvements in the existing NLML method. On an experimental kiwi fruit image an improvement of 10% in PSNR is achieved. We did experiments on both simulated and real data sets to validate and to demonstrate the effectiveness of the proposed method. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 256–264, 2015