Study of the electronic structures of high Tc cuprate superconductors by electron energy loss and secondary electron emission spectroscopies

Energy loss spectra of superconducting YBa2Cu3O6.9' Bi1.5Pb0.5Ca2.5Sr1.5Cu3O10+δ and Tl2CaBa2Cu3O8 obtained at primary electron energies in the 170–310 eV range show features reflecting the commonalities in their electronic structures. The relative intensity of the plasmon peak shows a marked drop across the transition temperature. Secondary electron emission spectra of the cuprates also reveal some features of the electronic structure.

Electronic-Transitions In Hydrogen-Bonded Dimers Of Carboxylic-Acids In The Vapor-Phase - An Electron-Energy Loss Spectroscopic Study

An electron energy loss spectroscopic study of the formic acid dimer has shown bands centred around 7.2, 8.5, 9.8, and 11.1 eV, of which the first and the third bands are assigned to n- rc* transitions and the other two to n-n* transitions; similar transitions are found in the acetic acid dimer.

Performance prediction and loss analysis of low specific speed submersible pumps

A performance prediction procedure is presented for low specific speed submersible pumps with a review of loss models given in the literature. Most of the loss theories discussed in this paper are one dimensional and improvements are made with good empiricism for the prediction to cover the entire range of operation of the low specific speed pumps. Loss correlations, particularly in the low flow range, are discussed. Prediction of the shape of efficiency-capacity and total head-capacity curves agrees well with the experimental results in almost the full range of operating conditions. The approach adopted in the present analysis, of estimating the losses in the individual components of a pump, provides means for improving the performance and identifying the problem areas in existing designs of the pumps. The investigation also provides a basis for selection of parameters for the optimal design of the pumps in which the maximum efficiency is an important design parameter. The scope for improvement in the prediction procedure with the nature of flow phenomena in the low flow region has been discussed in detail.

Electron energy loss spectroscopic study of Cr(CO)6, Mo(CO)6 and W(CO)6 in the vapour phase

Electron energy loss spectra (EELS) of Cr, Mo and W hexacarbonyls in the vapour phase are reported. Most of the bands observed are similar to those in optical spectra, but the two high energy transitions in the 9·8–11·2 eV region are reported here for the first time. Based on the orbital energies from the ultraviolet photoelectron spectra and the electronic transition energies from EELS and earlier optical studies, the molecular energy level schemes of these molecules are constructed.

Anomalous viscous loss in emulsions

We propose a model for concentrated emulsions based on the speculation that a macroscopic shear strain does not produce an affine deformation in the randomly close-packed droplet structure. The model yields an anomalous contribution to the complex dynamic shear modulus that varies as the square root of frequency. We test this prediction using a novel light scattering technique to measure the dynamic shear modulus, and directly observe the predicted behavior over six decades of frequency and a wide range of volume fractions.

Dielectric function and optical conductivity of TiOx (0.8loss spectroscopy

Reflection electron energy-loss spectra are reported for the family of compounds TiOx over the entire homogeneity range (0.8 < a: < 1.3). The spectra exhibit a plasmon feature on the low-energy side, while several interband transitions are prominent at higher energies. The real and imaginary parts of dielectric functions and optical conductivity for these compounds are determined using the Kramers-Kronig analysis. The results exhibit systematic behavior with varying oxygen stoichiometry.

Constraint loss under dynamic loading in rate independent plastic solids

The objectives of this paper are to examine the loss of crack tip constraint in dynamically loaded fracture specimens and to assess whether it can lead to enhancement in the fracture toughness at high loading rates which has been observed in several experimental studies. To this end, 2-D plane strain finite element analyses of single edge notched (tension) specimen and three point bend specimen subjected to time varying loads are performed. The material is assumed to obey the small strain J(2) flow theory of plasticity with rate independent behaviour. The results demonstrate that a valid J-Q field exists under dynamic loading irrespective of the crack length and specimen geometry. Further, the constraint parameter Q becomes strongly negative at high loading rates, particularly in deeply cracked specimens. The variation of dynamic fracture toughness K-dc with stress intensity rate K for cleavage cracking is predicted using a simple critical stress criterion. It is found that inertia-driven constraint loss can substantially enhance K-dc for (K) over dot > 10(5) MPa rootm/s.

Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functions

In this paper we consider the problem of learning an n × n kernel matrix from m(1) similarity matrices under general convex loss. Past research have extensively studied the m = 1 case and have derived several algorithms which require sophisticated techniques like ACCP, SOCP, etc. The existing algorithms do not apply if one uses arbitrary losses and often can not handle m > 1 case. We present several provably convergent iterative algorithms, where each iteration requires either an SVM or a Multiple Kernel Learning (MKL) solver for m > 1 case. One of the major contributions of the paper is to extend the well knownMirror Descent(MD) framework to handle Cartesian product of psd matrices. This novel extension leads to an algorithm, called EMKL, which solves the problem in O(m2 log n 2) iterations; in each iteration one solves an MKL involving m kernels and m eigen-decomposition of n × n matrices. By suitably defining a restriction on the objective function, a faster version of EMKL is proposed, called REKL,which avoids the eigen-decomposition. An alternative to both EMKL and REKL is also suggested which requires only an SVMsolver. Experimental results on real world protein data set involving several similarity matrices illustrate the efficacy of the proposed algorithms.