Structural dependence of microwave dielectric properties of spinel structured Mg2(Ti1-xSnx)O4 solid solutions: Crystal structure refinement,Raman spectra study and complex chemical bond theory

Mg₂(Ti_1-xSn_x)O₄ (x?=?0–1) ceramics were prepared through conventional solid-state method. This paper focused on the dependence of microwave dielectric properties on crystal structural characteristics via crystal structure refinement, Raman spectra study and complex chemical bond theory. XRD spectrums delineated the phase information of a spinel structure, and structural characteristic of these compositions were achieved with the help of Rietveld refinements. Raman spectrums were used to depict the correlations between vibrational phonon modes and dielectric properties. The variation of permittivity is ascribed to the Mg₂(Ti_1-xSn_x)O₄ average bond covalency. The relationship among the B-site octahedral bond energy, tetrahedral bond energy and temperature coefficient are discussed by defining on the change rate of bond energy and the contribution rate of octahedral bond energy. The quality factor is affected by systematic total lattice energy, and the research of XPS patterns illustrated that oxygen vacancies can be effectively restrained in rich oxygen sintering process. Obviously, the microwave dielectric properties of Mg₂(Ti_1-xSn_x)O₄ compounds were obtained (${\epsilon }_r$= 12.18, $Q\times f$?=?170,130?GHz, ${\tau }_f$?=??53.1?ppm/°C, x?=?0.2).     

Migration of Point Defects in the Field of a Temperature Gradient

The influence of the temperature gradient over the thickness of the cladding of a fuel element of a fast-neutron reactor on the migration of point defects formed in the cladding material due to neutron irradiation has been studied. It has been shown that, under the action of the temperature gradient, the flux of vacancies onto the inner surface of the cladding is higher than the flux of interstitial atoms, which leads to the formation of a specific concentration profile in the cladding with a vacancy-depleted zone near the inner surface. The experimental results on the spatial distribution of pores over the cladding thickness have been presented with which the data on the concentration profiles and vacancy fluxes have been compared.     

A Giant Frequency Shift in the Raman Spectrum of Water Adsorbed on a Metallic Silver Surface

The Raman spectrum of water adsorbed on a metallic silver surface reveals an anomalously large shift of the vibrational frequency as compared to that in the bulk. The results are compared to data reported by other researchers, and possible interpretations of the observed phenomenon are discussed.     

Strain Concentration Effect in Cu–Al–Ni Single Crystals under a Longitudinal Bending Force

The behavior of a superelastic Cu?14.2% Al?4%Ni single crystal in the case of high reversible strains under a longitudinal bending force was investigated. The effect of strain confinement along the crystal length was revealed and studied. The highest reversible strains (up to 10%) were shown to be confined within the central part of the bent crystal.     

Role of Elastic Interphase Deformations in the Formation of Crystal Structure of β-Nb Particles Precipitating in a Zr–2.5% Nb Alloy

X-ray diffraction analysis has been used to study the structure of the α-Zr matrix phase and the precipitation of β-Nb particles upon the annealing of a Zr–2.5% Nb deformed alloy. It has been found that the process of the precipitation of the strengthening β-Nb particles in the alloy is accompanied by the appearance of fields of elastic interphase deformations in the matrix α phase of the alloy due to the difference in the specific atomic volumes of the crystal structures of the matrix and precipitated phases. It has been shown experimentally that, as a result of the presence of interphase deformations in the alloy, the bcc crystal structure of the precipitating β-Nb particles undergoes monoclinic distortions.     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.