Spray Drying of Metal Alkoxide Sol for Strontium Titanate Ceramics

Conditions for obtaining a stable sol in an isopropyl alcohol–water medium containing titanium isopropoxide and strontium nitrate, and acetic acid as a modifier, have been described. Spray drying of the sol results in submicrometer spherical agglomerates which on further thermal decomposition yield submicrometer particles of strontium titanate at temperatures as low as 500°C. The thermal decomposition characteristics of the spray-dried precursor and the development of strontium titanate phase have been discussed. Calcined precursor powder possesses a specific surface area of 12m²/g, a comp action density of 57%, and a sintered density of > 98%. The optimum sintering temperature of such a powder was 1450°C, which resulted in a sintered grain size around 1.5 μm. Further, such a sintered sample had a dielectric constant of 260 and a loss factor of 0.008 at 1 kHz. This method appears to be very convenient with respect to handling of stable sols and thus avoids the usual difficulties regarding extended gelation as well as inhomogeneous precipitation.     

The use of optimization techniques in the analysis of cracked members by the finite element displacement and stress methods

Mathematical programming is applied to the two-dimensional stationary crack problem of a body composed of nonlinear elastic incompressible material. Fully admissible displacement as well as stress formulations are used to discretize the problem. Crack tip singularity is introduced in the displacement formulation by enriched elements for plane stress and, in certain cases, by superposition for plane strain. Pointwise incompressibility is obtained through constrained displacement functions. For three crack geometries Rice's J integral is evaluated by the energy difference method for different values of the hardening index. The numerical results, which are also applicable to secondary creep problems, appear to suggest a bounding character.     

Achieving excellent energy storage density of Pb0.97La0.02(ZrxSn0.05Ti0.95-x)O3 ceramics by the B-site modification

The applications of antiferroelectric (AFE) materials in miniaturized and integrated electronic devices are limited by their low energy density. To address the above issue, the antiferroelectricity of the reinforced material was designed to improve its AFE-ferroelectric (FE) phase transition under electric fields. In this present study, the composition of Zr⁴⁺ (0.72 Å) and Ti⁴⁺ (0.605 Å) at B-site of Pb_0.97La_0.02(Zr_xSn_0.05Ti_0.95-x)O₃ ceramics with orthogonal reflections are synthesized via the tape-casting method. These ceramics are modified to enhance their antiferroelectricity by reducing their tolerance factor. A recoverable energy storage density W_rec 12.1 J/cm³ was obtained for x = 0.93 under 376 kV/cm, which is superior value than reported until now in lead-based energy storage systems. Moreover, the discharge energy density can reach 10.23 J/cm³, and 90 % of which can be released within 5.66 μs. This work provides a new window and potential materials for further industrialization of pulse power capacitors.     

A Reversible Data Hiding Scheme for Interpolated Images Based on Pixel Intensity Range

Multimedia Tools and Applications - In this paper, we propose a novel interpolation and a new reversible data hiding scheme for upscaling the original image and hiding secret data into the...     

Chaotic neurons for on-line quality control in manufacturing

Given today's trend towards globalisation of markets, on-line quality control of manufacturing processes is deemed essential. We describe the use of neural networks and chaos theory to implement the idea of intelligent integrated diagnostics (IID) for this purpose. Our efforts are specifically concentrated on implementing IID in the turning process — a ubiquitous manufacturing process. We propose and develop two types of chaotic neurons — neural network architectures trained to capture the underlying chaotic dynamics of the turning process — to address the common problems of tool wear and chatter. The first, called the fractal estimation continuously estimates tool wear; the second, called theCOPAVAS, initiates optimal chatter control.     

Modelling of anisotropic elastic properties in alloy 718 built by electron beam melting

ABSTRACT

Owing to the inherent nature of the process, typically material produced via electron beam melting (EBM) has a columnar microstructure. As a result of that, the material will have anisotropic mechanical properties. In this work, anisotropic elastic properties of EBM built Alloy 718 samples at room temperature were investigated by using experiments and modelling work. Electron backscatter diffraction data from the sample microstructure was used to predict the Young’s modulus. The results showed that the model developed in the finite element software OOF2 was able to capture the anisotropy in the Young’s modulus. The samples showed transversely isotropic elastic properties having lowest Young’s modulus along build direction. In addition to that, complete transversely isotropic stiffness tensor of the sample was also calculated.

This paper is part of a thematic issue on Nuclear Materials.     

Analysis and classification of malignancy in pancreatic magnetic resonance images using neural network techniques

Computer-aided diagnosis (CAD) is a computerized way of detecting tumors in MR images. Magnetic resonance imaging (MRI) has been generally used in the diagnosis and detection of pancreatic tumors. In a medical imaging system, soft tissue contrast and noninvasiveness are clear preferences of MRI. Inaccurate detection of tumor and long time consumption are the disadvantages of MRI. Computerized classifiers can greatly renew the diagnosis activity, in terms of both accuracy and time necessity by normal and abnormal images, automatically. This article presents an intelligent, automatic, accurate, and robust method to classify human pancreas MRI images as normal or abnormal in terms of pancreatic tumor. It represents the response of artificial neural network (ANN) and support vector machine (SVM) techniques for pancreatic tumor classification. For this, we extract features from MR images of pancreas using the GLCM method and select the best features using JAFER algorithm. These features are analyzed by five classification techniques: ANN BP, ANN RBF, SVM Linear, SVM Poly, and SVM RBF. We compare the results with benchmark data set of MR brain images. The analytical outcome presents that the two best features used to classify the MR images using ANN BP technique have 98% classification accuracy.     

Antenna Design: Micro Strip Patch for Spectrum Utilization in Cognitive Radio Networks

Wireless Personal Communications - A micro strip patch antenna with multiple parasitic patches for Cognitive Radio Network applications is presented to enhance the bandwidth. Multiple resonances...     

Assembly pathway analysis of DNA nanostructures and the construction of parallel motifs

We present a system for analyzing the assembly pathway of DNA nanostructures. This enables the identification, explanation, and avoidance of obstacles to proper structure formation. Potential problems include strand end-pinning and misfolding caused by the structural bias of nominally flexible junctions. We have used this system to guide the construction of parallel motifs that had previously, for unknown reasons, resisted assembly.     

Sorption of Tertiary Butyl Mercaptan to Indoor Materials in Contact with Air or Water

This study reports sorption of the malodorant 2-methyl-2-propanethiol, commonly known as tertiary butyl mercaptan (TBM), to selected indoor materials. The phase distribution of TBM in gas-solid and aqueous-solid systems was evaluated using batch reactors. Sorbents used in the study included two carpets, two wallpapers, a soil, and granular activated carbon (GAC). Sorption was studied for gaseous and aqueous TBM concentrations spanning three orders of magnitude and contact times ranging from 1 to 28 days. The phase distribution data were plotted and fitted using linear and Freundlich relationships. Results indicated that all solids sorbed environmentally significant quantities of TBM, with the likelihood of producing concentrations above the odor threshold during subsequent remediation using mechanical ventilation. TBM retention by sorbents was greater from air than from water. The malodorant partitioned readily into wallpapers and slowly into the carpet materials. Sorption was nonlinear in the case of GAC and the nonlinearity appeared to increase with sorption contact time. GAC sorbed TBM strongly from both air and water.