Effect of concentration and particle size on nonlinearity of Au nano-fluid prepared by γ (Co) radiation

Nonlinear properties of Au nano-fluid prepared by γ-radiation method at different concentrations were investigated. Measurements of nonlinear refractive index and nonlinear absorption coefficient were carried out using a single beam Z-scan technique. A green CW laser beam operated at 532 nm was used as excitation source. The Au nano-fluid shows a good third order nonlinear response. The sign of the nonlinear refractive index is found to be negative and the magnitude is in the order of 10⁻⁷ cm²/W. This nonlinear effect increases as the concentration increases from 3.119 × 10⁻⁴ to 2.354 × 10⁻³ M which correspond to particle sizes of 4.0-30.5 nm, respectively. A good linear relationship was obtained between nonlinear refractive index and concentration. However the relationship between nonlinear refractive index and particle size was nonlinear behavior.     

Effect of quantization and positron concentration on shielding potentials in electron-positron-ion plasma

The kinetic theory of plasma has been employed to compute the test-charge potential distributions accounting for quantization effects in magnetized electron-positron-ion (EPI) plasmas. In this regard, the degenerate positrons and electrons are assumed to follow the Fermi-Dirac distribution, while inertial ions are modelled by Maxwellian velocity distribution. By solving the Fourier-transformed Vlasov–Poisson equations, a modified dielectric function and electrostatic potential is obtained. By imposing various constraints on the test-charge speed, the potential profile has been analysed in terms of Debye–Hückel (DH), far-field (FF), and wake-field (WF) potentials. It has been found that the amplitude of DH and FF potentials increases by the inclusion of quantization effects, and it becomes the opposite for the WF potential profile. Furthermore, the variation of positron concentration significantly affects the DH, FF, and WF potentials. The present findings are important to understand the shielding phenomenon in degenerate multi-species plasmas.     

Alfvén waves in temperature anisotropic Cairns distributed plasma

The dispersion relations and Landau damping of Alfven waves in kinetic and inertial limits are studied in temperature anisotropic Cairns distributed plasma.In the case of kinetic Alfven waves(KAWs),it is found that the real frequency is enhanced when either the electron perpendicular temperature or the non-thermal parameter A increases.For inertial Alfven waves(IAWs),the real frequency is slightly affected by the electron temperature anisotropy and A.Besides the real frequency,the damping rate of KAWs is reduced when the electron perpendicular temperature or A increases.In the case of IAWs,the temperature anisotropy and A either enhance or reduce the damping rate depending upon the perpendicular wavelength.These results may be helpful to understand the dynamics of KAWs and IAWs in space plasmas where the non-Maxwellian distribution of particles are routinely observed.     

Brownian motion and thermophoresis effects on unsteady stagnation point flow of Eyring-Powell nanofluid: a Galerkin approach

This article concerns the analysis of an unsteady stagnation point flow of Eyring-Powell nanofluid over a stretching sheet. The influence of thermophoresis and Brownian motion is also considered in transport equations. The nonlinear ODE set is obtained from the governing nonlinear equations via suitable transformations. The numerical experiments are performed using the Galerkin scheme. A tabular form comparison analysis of outcomes attained via the Galerkin approach and numerical scheme (RK-4) is available to show the credibility of the Galerkin method. The numerical exploration is carried out for various governing parameters, namely, Brownian motion, steadiness, thermophoresis, stretching ratio, velocity slip, concentration slip, thermal slip, and fluid parameters, and Hartmann, Prandtl and Schmidt numbers. The velocity of fluid enhances with an increase in fluid and magnetic parameters for the case of opposing, but the behavior is reversed for assisting cases. The Brownian motion and thermophoresis parameters cause an increase in temperature for both cases (assisting and opposing). The Brownian motion parameter provides a drop-in concentration while an increase is noticed for the thermophoresis parameter. All the outcomes and the behavior of emerging parameters are illustrated graphically. The comparison analysis and graphical plots endorse the appropriateness of the Galerkin method. It is concluded that said method could be extended to other problems of a complex nature.     

Dynamic magnetic properties of the kinetic cylindrical Ising nanotube

The nature (time variation) of response magnetizations m(wt) of the kinetic cylindrical Ising nanotube in the presence of a periodically varying external magnetic field h(wt) is studied by employing the effective-field theory (EFT) with correlations as well as the Glauber-type stochastic dynamics. We have determined the time variations of m(wt) and h(wt) for various temperatures, and investigated the dynamic magnetic hysteresis behavior. Temperature dependence of the dynamic magnetizations, hysteresis loop areas and correlations are investigated in order to characterize the nature (first- or second-order) of the dynamic transitions as well as to obtain the dynamic phase transition temperatures. We also present the dynamic phase diagrams in the three different planes and compare the results of the equilibrium and nonequilibrium states. The phase diagrams exhibit dynamic tricritical, isolated critical, multicritical and triple points. The results are in good agreement with some experimental and theoretical results.     

Investigation of energetic ion-induced mixing in Bi/Ge system

The present study is carried out for the investigation of energetic ion beam mixing in the Bi/Ge system, induced by electronic excitation. The system Ge/Bi/C was deposited on Si substrate at room temperature in the high vacuum deposition system and irradiated using Au ions of 120?MeV at the fluences 1?×?10¹³, 5?×?10¹³ and 1?×?10¹⁴?ions/cm². The top layer of carbon was deposited as the protecting layer to avoid oxidation. The swift heavy ions (SHI)-induced interface mixing was studied by Rutherford backscattering spectroscopy (RBS) for depth profiles and compositions, grazing incidence X-ray diffraction (GIXRD) for phase identification and atomic force microscopy (AFM) for surface roughness. We have calculated the mixing rate, mixing efficiency and inter-diffusion coefficient for the Bi/Ge system. We observed that the thickness of the mixed region increased with increasing fluence. In the GIXRD pattern, no new crystalline phase formation was observed after irradiation, the mixed region may be in an amorphous form. The mixing effect is explained in the framework of the thermal spike model.     

New class of generating functions associated with generalized hypergeometric polynomials

In this paper authors prove a general theorem on generating relations for a certain sequence of functions. Many formulas involving the families of generating functions for generalized hypergeometric polynomials are shown here to be special cases of a general class of generating functions involving generalized hypergeometric polynomials and multiple hypergeometric series of several variables. It is then shown how the main result can be applied to derive a large number of generating functions involving hypergeometric functions of Kampé de Fériet, Srivastava, Srivastava-Daoust, Chaundy, Fasenmyer, Cohen, Pasternack, Khandekar, Rainville and other multiple Gaussian hypergeometric polynomials scattered in the literature of special functions.     

Intelligent reversible watermarking technique in medical images using GA and PSO

The advances in recording, editing, and broadcasting multimedia contents in digital form motivate to protect these digital contents from illegal use, such as duplication, manipulation, and redistribution. However, watermarking algorithms are designed to satisfy requirements of applications, as different applications have different concerns. We intend to design a watermarking algorithm for applications which require high embedding capacity and imperceptibility, to maintain the integrity of the host signal as well as embedded information. Reversible watermarking is a promising technique which satisfies our requirements. In this paper, we concentrate on improving the watermark capacity and reducing the perceptual degradation of an image. We investigated the Luo's [1] additive interpolation-error expansion algorithm and enhanced it by incorporating with two intelligent techniques: genetic algorithm (GA), and particle swarm optimization (PSO). Genetic algorithm is applied to exploit the correlation of image pixel values to obtain better estimation of neighboring pixel values, which results in optimal balance between information storage capacity and imperceptibility. Particle swarm optimization (intelligent technique) is also applied for the same purpose. Experimental results show that PSO and GA nearly give the same results, but GA outperforms the PSO. Experimental results also reveal that the proposed strategy outperforms the state of art works in terms of perceptual quality and watermarking payload.     

Four-dimensional parameter estimation of plane waves using swarming intelligence

This paper proposes an efficient approach for four-dimensional(4D) parameter estimation of plane waves impinging on a 2-L shape array. The 4D parameters include amplitude, frequency and the two-dimensional(2D) direction of arrival,namely, azimuth and elevation angles. The proposed approach is based on memetic computation, in which the global optimizer, particle swarm optimization is hybridized with a rapid local search technique, pattern search. For this purpose,a new multi-objective fitness function is used. This fitness function is the combination of mean square error and the correlation between the normalized desired and estimated vectors. The proposed hybrid scheme is not only compared with individual performances of particle swarm optimization and pattern search, but also with the performance of the hybrid genetic algorithm and that of the traditional approach. A large number of Monte–Carlo simulations are carried out to validate the performance of the proposed scheme. It gives promising results in terms of estimation accuracy, convergence rate, proximity effect and robustness against noise.