Conductivity Study on PEO Based Polymer Electrolytes Containing Hexafluorophosphate Anion: Effect of Plasticizer

PEO based polymer electrolytes containing ammonium hexafluorophosphate (NH₄PF₆) and hexafluorophosphoric acid (HPF₆), both with PF anion have been studied. The effect of the addition of propylene carbonate (PC) to PEO-NH₄PF₆ and PEO-HPF₆ has been observed to increase in ionic conductivity which is attributed to an increase in free ion concentration due to the dissociation of ion aggregates present at higher acid/salt concentrations. The plasticized polymer electrolytes containing HPF₆ show relatively higher conductivity (σ_max = 1.02 × 10⁻⁴ S/cm at 10 wt% HPF₆) as compared to electrolytes containing NH₄PF₆ (σ_max = 1.09 × 10⁻⁵ S/cm at 10 wt% NH₄PF₆). Presence of free ions, ion aggregates and their dissociation with the addition of PC has been studied by Fourier Transform Infrared Spectroscopy (FTIR). The change in amorphous phase with PC content was also studied by X-Ray Diffraction (XRD). The variation of conductivity with temperature shows Vogel–Tammen–Fulcher (VTF) behavior, which is associated with the highly amorphous nature of electrolytes. ¹H Nuclear magnetic Resonance (NMR) spectra at different temperatures shows line narrowing and suggests the onset of long range ion diffusional motion. Change in surface morphology of polymer electrolytes with the addition of PC is also checked by Scanning Electron Microscopic (SEM) studies.     

Measurement of the neutron capture cross-section of 238U using the neutron activation technique

The ²³⁸U(n, ??)²³⁹U reaction cross-section at average neutron energy of 3.7?±?0.3?MeV from the ⁷Li(p, n)⁷Be reaction has been determined using activation and off-line ??-ray spectrometric technique. The ²³⁸U(n, ??)²³⁹U and ²³⁸U(n, 2n)²³⁷U reaction cross-sections at average neutron energy of 9.85?±?0.38?MeV from the same ⁷Li(p, n)⁷Be reaction have been also determined using the above technique. The experimentally determined ²³⁸U(n, ??)²³⁹U and ²³⁸U(n, 2n)²³⁷U reaction cross-sections were compared with the evaluated data of ENDF/B-VII, JENDL-4.0, JEFF-3.1 and CENDL-3.1. The experimental values were found to be in general agreement with the evaluated value based on ENDF/B-VII, and JENDL-4.0 but not with the JEFF-3.1 and CENDL-3.1. The present data along with literature data in a wide range of neutron energies were interpreted in terms of competition between different reaction channels including fission. The ²³⁸U(n, ??)²³⁹U and ²³⁸U(n, 2n)²³⁷U reaction cross-sections were also calculated theoretically using the TALYS 1.2 computer code and were also found to be in agreement experimental data.     

Formation of the imide [Ta(NMe2)3(μ-NSiMe3)]2 through an unprecedented α-SiMe3 abstraction by an amide ligand

Ta(NMe(2))(4)[N(SiMe(3))(2)] (1) undergoes the elimination of Me(3)Si-NMe(2) (2), converting the -N(SiMe(3))(2) ligand to the ═NSiMe(3) ligand, to give the imide "Ta(NMe(2))(3)(═NSiMe(3))" (3) observed as its dimer 4. CyN═C═NCy captures 3 to yield guanidinates Ta(NMe(2))(3-n)(═NSiMe(3))[CyNC(NMe(2))NCy](n) [n = 1 (5), 2 (6)]. The kinetic study of α-SiMe(3) abstraction in 1 gives ΔH(?) = 21.3(1.0) kcal/mol and ΔS(?) = -17(2) eu.     

The t-analog of the level one string function for twisted affine Kac–Moody algebras

We study Lusztig?s t-analog of weight multiplicities, or affine Kostka–Foulkes polynomials, associated to level one representations of twisted affine Kac–Moody algebras. We obtain an explicit closed form expression for the unique t-string function, using constant term identities of Macdonald and Cherednik. This extends previous work on t-string functions for the untwisted simply-laced affine Kac–Moody algebras.     

Cognitive learning in differential evolution and its application to model order reduction problem for single-input single-output systems

Differential evolution (DE) is a well known and simple population based probabilistic approach for global optimization over continuous spaces. It has reportedly outperformed a few evolutionary algorithms and other search heuristics like the particle swarm optimization when tested over both benchmark and real world problems. DE, like other probabilistic optimization algorithms, has inherent drawback of premature convergence and stagnation. Therefore, in order to find a trade-off between exploration and exploitation capability of DE algorithm, a new parameter namely, cognitive learning factor (CLF) is introduced in the mutation process. Cognitive learning is a powerful mechanism that adjust the current position of individuals by the means of some specified knowledge (previous experience of individuals). The proposed strategy is named as cognitive learning in differential evolution (CLDE). To prove the efficiency of various approaches of CLF in DE,?CLDE is tested over 25 benchmark problems. Further, to establish the wide applicability of CLF,?CLDE is applied to two advanced DE variants. CLDE is also applied to solve a well known electrical engineering problem called model order reduction problem for single input single output systems.     

Fitness based Differential Evolution

Differential Evolution (DE) is a well known and simple population based probabilistic approach for global optimization. It has reportedly outperformed a few Evolutionary Algorithms and other search heuristics like Particle Swarm Optimization when tested over both benchmark and real world problems. But, DE, like other probabilistic optimization algorithms, sometimes exhibits premature convergence and stagnates at suboptimal point. In order to avoid stagnation behavior while maintaining a good convergence speed, a new position update process is introduced, named fitness based position update process in DE. In the proposed strategy, position of the solutions are updated in two phases. In the first phase all the solutions update their positions using the basic DE and in the second phase, all the solutions update their positions based on their fitness. In this way, a better solution participates more times in the position update process. The position update equation is inspired from the Artificial Bee Colony algorithm. The proposed strategy is named as Fitness Based Differential Evolution ( $FBDE$ ). To prove efficiency and efficacy of $FBDE$ , it is tested over 22 benchmark optimization problems. A comparative analysis has also been carried out among proposed FBDE, basic DE, Simulated Annealing Differential Evolution and Scale Factor Local Search Differential Evolution. Further, $FBDE$ is also applied to solve a well known electrical engineering problem called Model Order Reduction problem for Single Input Single Output Systems.     

Singularity-free dark energy star

We propose a model for an anisotropic dark energy star where we assume that the radial pressure exerted on the system due to the presence of dark energy is proportional to the isotropic perfect fluid matter density. We discuss various physical features of our model and show that the model satisfies all the regularity conditions and is stable as well as singularity-free.     

Development of a tyre traction testing facility

An experimental setup comprising up of an indoor soil bin, a single wheel tester (SWT), a soil processing trolley, a drawbar pull loading device and an instrumentation unit was developed to perform traction tests in the soil bin to study the effect of soil, tyre and system parameters on the performance of tyres. The design of the single wheel tester was such that the dynamic weight reaction force is equal to that measured statically. It is a simple wheeled device, capable of testing tyres of up to 1.5 m in diameter, vertical force up to 19 kN, net pull up to 7.2 kN, torque up to 5.5 kN m, and speed up to 3.5 km/h.     

各向异性粘弹性多孔截止中平面波的传播

This study discusses wave propagation in perhaps the most general model of a poroelastic medium. The medium is considered as a viscoelastic, anisotropic and porous solid frame such that its pores of anisotropic permeability are filled with a viscous fluid. The anisotropy considered is of general type, and the attenuating waves in the medium are treated as the inhomogeneous waves. The complex slowness vector is resolved to define the phase velocity, homogeneous attenuation, inhomogeneous attenuation, and angle of attenuation for each of the four attenuating waves in the medium. A non-dimensional parameter measures the deviation of an inhomogeneous wave from its homogeneous version. An numerical model of a North-Sea sandstone is used to analyze the effects of the propagation direction, inhomogeneity parameter, frequency regime, anisotropy symmetry, anelasticity of the frame, and viscosity of the pore-fluid on the propagation characteristics of waves in such a medium.