Study of embedded lead-tin nanoparticles in aluminum matrix

Nanoembedded lead-tin alloys in aluminum matrix were synthesized by rapid solidification processing. These melt-spun aluminum alloys were then investigated using XRD, EDX and TEM. The XRD study reveals that the melt-spun samples contain elemental aluminum, lead and tin. The TEM analysis shows that embedded particles in aluminium matrix have a distinct two-phase contrast of lead and tin. The lead and tin in these nanoalloys exhibit an orientation relationship with the matrix aluminum and with each other. DSC studies were conducted to reveal the melting and solidification characteristics of these embedded nanoalloys. DSC thermograms exhibit features of multiple solidification exotherms on thermal cycling, which can be attributed to sequential melting and solidification of lead and tin in the respective alloys.

The production of AlN-rich matrix composites by the reactive infiltration of Al alloys in nitrogen

Aluminium nitride (AlN)-Al matrices reinforced with Al2O3 particulate have been fabricated by reactive infiltration of Al-2% Mg alloy into Al2O3 preforms in N-2 in the temperature range of 900-1075 degreesC. The growth of composites of useful thickness was facilitated by the presence of a Mg-rich external getter, in the absence of which composite growth is self-limiting and terminates prematurely. Successful growth of composites has been attributed to the reduction in residual oxygen partial pressure brought about by the reaction with oxygen of highly volatile Mg in the getter alloy. The microstructure of the matrix consists of AlN-rich regions contiguous with the particulate with metal-rich channels in-between, thereby suggesting that nitridation initiates by preferential wicking of alloy along the particle surfaces. The increase in nitride content of the matrix with temperature is consistent with hardness values that vary between similar to3 and 10 GPa. (C) 2002 Acta Materialia Inc. Published by Elsevier Science Ltd. All rights reserved.

Studies on compressive failure features in syntactic foam material

Syntactic foam made by mechanical mixing of glass hollow spheres in epoxy resin matrix is characterized for compressive properties in the present study. Volume fraction of hollow spheres in the syntactic foam under investigation is kept at 67.8%. Effect of specimen aspect ratio on failure behavior and stress-strain curve of the material is highlighted. Considerable differences are noted in the macroscopic fracture features of the specimen and the stress-strain curve with the variation in specimen aspect ratio, although compressive yield strength values were within a narrow range. Post compression test scanning electron microscopic observations coupled with the macroscopic observations taken during the test helped in explaining the deviation in specimen behavior and in gathering support for the proposed arguments.

density matrix renormalization group study of polyacene

We study the nature of excited states of long polyacene oligomers within a Pariser-Parr-Pople (PPP) Hamiltonian using the Symmetrized Density Matrix Renormalization Group (SDMRG) technique. We find a crossover between the two-photon state and the lowest dipole allowed excited state as the system size is increased from tetracene to pentacene. The spin-gap is the smallest gap. We also study the equilibrium geome tries in the ground and excited states from bond orders and bond-bond correlation functions. We find that the Peierls instability in the ground state of polyacene is conditional both from energetics and structure factors computed froth correlation functions.

Influence of matrix characteristics on fracture toughness of high volume fraction Al2O3/Al–AlN composites

The role of matrix microstructure on the fracture of Al-alloy composites with 60 vol% alumina particulates was studied. The matrix composition and microstructure were systematically varied by changing the infiltration temperature and heat treatment. Characterization was carried out by a combination of metallography, hardness measurements, and fracture studies conducted on compact tension specimens to study the fracture toughness and crack growth in the composites. The composites showed a rise in crack resistance with crack extension (R curves) due to bridges of intact matrix ligaments formed in the crack wake. The steady-state or plateau toughness reached upon stable crack growth was observed to be more sensitive to the process temperature rather than to the heat treatment. Fracture in the composites was predominantly by particle fracture, extensive deformation, and void nucleation in the matrix. Void nucleation occurred in the matrix in the as-solutionized and peak-aged conditions and preferentially near the interface in the underaged and overaged conditions. Micromechanical models based on crack bridging by intact ductile ligaments were modified by a plastic constraint factor from estimates of the plastic zone formed under indentations, and are shown to be adequate in predicting the steady-state toughness of the composite.

An Approach for Distance Relay Co-ordination using Support Vector Machines

In this paper, an approach to enhance the Extra High Voltage (EHV) Transmission system distance protection is presented. The scheme depends on the apparent impedance seen by the distance relay during the disturbance. In a distance relay,the impedance seen at the relay location is calculated from the fundamental frequency component of the voltage and current signals. Support Vector Machines (SVMs) are a new learning-byexample are employed in discriminating zone settings (Zone-1,Zone-2 and Zone-3) using the signals to be used by the relay.Studies on 265-bus system, an equivalent of practical Indian Western grid are presented for illustrating the proposed scheme.

Self-organization of multiple components in a steroidal hydrogel matrix: design, construction and studies on novel tunable luminescent gels and xerogels

The present work combines two rapidly growing research areas-functional supramolecular gels and lanthanide based hybrid materials. Facile hydrogel formation from several lanthanide(III) cholates has been demonstrated. The morphological and mechanical properties of these cholate gels were investigated by TEM and rheology. The hydrogel matrix was subsequently utilized for the sensitization of Tb(III) by doping a non-coordinating chromophore, 2,3-dihydroxynaphthalene (DHN), at micromolar concentrations. In the mixed gels of Tb(III)-Eu(III), an energy transfer pathway was found to operate from Tb(III) to Eu(III) and by utilizing this energy transfer, tunable multiple-color luminescent hydrogels were obtained. The emissive properties of the hydrogels were also retained in the xerogels and their suspensions in n-hexane were used for making luminescent coating on glass surface.

Dynamic matrix rank with partial lookahead

We consider the problem of maintaining information about the rank of a matrix $M$ under changes to its entries. For an $n \times n$ matrix $M$, we show an amortized upper bound of $O(n^{\omega-1})$ arithmetic operations per change for this problem, where $\omega < 2.376$ is the exponent for matrix multiplication, under the assumption that there is a {\em lookahead} of up to $\Theta(n)$ locations. That is, we know up to the next $\Theta(n)$ locations $(i_1,j_1),(i_2,j_2),\ldots,$ whose entries are going to change, in advance; however we do not know the new entries in these locations in advance. We get the new entries in these locations in a dynamic manner.

A comparative study of ordinary kriging and support vector machine models for the spatial variability of rock depth in Bangalore

In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 sq.km. In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, ordinary kriging and Support Vector Machine (SVM) models have been developed. In ordinary kriging, the knowledge of the semivariogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of Bangalore, where field measurements are not available. A cross validation (Q1 and Q2) analysis is also done for the developed ordinary kriging model. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing e-insensitive loss function has been used to predict the reduced level of rock from a large set of data. A comparison between ordinary kriging and SVM model demonstrates that the SVM is superior to ordinary kriging in predicting rock depth.