Journal of Experimental and Theoretical Physics最新文献

Classical viscoelastic models constructed using linear springs and dashpots not only lay an important foundation of the theory of viscoelasticity, but also are the most common models adopted to describe the mechanical behaviors of viscoelastic materials in scientific research and engineering. Due to the complicated nature of time-dependent mechanical behaviors of viscoelastic materials and their sensitive dependence on the initial conditions, it is essential to rigorously consider the effects of the initial conditions when using those models in order to achieve accurate analysis results. The purpose of this article is to present the general form of the constitutive equations of classical viscoelastic models in the Laplace domain that is rigorously incorporated with the effects of the initial conditions. The constitutive equations of some fundamental classical viscoelastic models in the Laplace domain are presented as examples. Compared to the general form of the constitutive equations of classical viscoelastic models in the Laplace domain without considering the initial conditions reported in literature, two examples of analysis demonstrate that the newly introduced form incorporated with the effects of the initial conditions can provide accurate analysis results. The newly introduced general form of the constitutive equations of classical viscoelastic models in the Laplace domain not only helps to improve the understanding of concepts in the theory of viscoelasticity, but also provides a tool for accurately describing the mechanical behaviors of viscoelastic materials.

In this study, the light shift of coherent population trapping (CPT) resonances is studied in a miniature glass cell (~0.1 cm³) filled with ¹³³Cs vapor. The atoms exposed to the radiation from a vertical-cavity surface-emitting laser (VCSEL). The laser current is modulated at a microwave frequency (≈4.6 GHz), which leads to the frequency modulation (FM) of output radiation. In addition, the light beam is transmitted through an electro-optic modulator (EOM), which is assembled as a Mach–Zehnder interferometer, acquiring amplitude modulation (AM). This dual (FM–AM) modulation leads to essentially nonlinear behavior of the function describing the light shift of the CPT resonance versus the total optical power in the cell. In particular, this function has an extremum that can be used to suppress the influence of small optical power variations in the cell on the stability of the CPT-based quantum frequency standard (QFS). The proposed scheme is characterized by a number of parameters such as the phase difference between the FM and AM signals as well as the bias voltage at EOM, which are additional degrees of freedom for controlling the behavior of the light shift of the CPT resonance. This can be used for the optimization of the QFS operation regime.

An elastic mechanical deformation has been applied to a single walled carbon nanotube (SWCNT) in this research to investigate its electronic properties using the tight binding model. This work involves torsional and uniaxial deformation that change the energy spectrum of zigzag, armchair and chiral carbon nanotubes and thus their electronic transport properties. In this paper, we look at the I–V characteristics of a single-walled carbon nanotube field effect transistor (CNTFET) in ballistic conduction at room temperature. The effect of torsional and uniaxial deformation on the performance of carbon nanotube field effect transistors is examined.

In this study, we investigate the emergence of convective flows in graphene-modified hydrogels experiencing phase transition and determine the thermophysical characteristics of such systems; the results are compared with numerical simulation data. We analyze the effect of graphene on the heat-transfer properties of hydrogel materials as applied to 3D bioprinting technologies. Using holographic interferometry, gradient calorimetry, and resulting temperature dependences of refractive indices, we have developed the computational complex for calculating the thermophysical parameters of hydrogel materials with graphene admixtures. It has been established that even insignificant concentrations of graphene admixture substantially affects the thermophysical properties. It is also shown that a graphene admixture reduces the viscosity of hydrogel samples, which is measured by the Höppler viscometer. Using the experimentally obtained thermophysical and rheological properties of hydrogels with graphene and the results of numerical simulation, we have calculated the Rayleigh numbers for the corresponding convective heat-exchange modes in the experimental cells with a hydrogel. The Rayleigh number (Ra) demonstrates substantial differences in the heat transfer of the material and its convective properties that depend on the viscosity, density, thermal conductivity, and other parameters of the system. In our case, the variations of the Rayleigh number indicate the difference in the thermal and hydrodynamic properties of different hydrogels with graphene.

In the framework of the consistent microscopic theory, universal analytic expressions describing absorption of laser pulses of an arbitrary duration in an optically dense medium have been derived, and their limiting cases have been considered. For the Gaussian and Lorentzian spectral profiles, simple expressions have been obtained for the absorption coefficient as a function of dimensionless parameters (optical thickness of the medium, the pulse duration and carrier frequency). Based on the performed calculations, the effect of the optical thickness of the medium on the dependences of the absorption coefficient on the pulse parameters has been revealed.

In this work, we use quantum mechanics theory to investigate and calculate the resistivity of the electron gas in a GaP/AlP/GaP quantum well at zero temperature and arbitrary temperatures under the influence of a magnetic field parallel to the layer. The calculations are performed considering the surface roughness scattering mechanism and the ionized impurity scattering mechanism. The results indicate that the temperature and magnetic field significantly affect the electronic properties of the two-dimensional electron gas. Moreover, the investigation results also reveal the influence of scattering mechanisms on the resistivity of a two-dimensional electron gas. The effects of the localization field correction also impact the electronic properties of the two-dimensional electron system in the quantum well structure. The results of this study are highly important for gathering information about layer structure for electronic applications.

The influence of the dense plasma environment on the energy levels and transition rates of H-like N⁶⁺, Ne⁹⁺, and Al¹²⁺ ions have been examined. The structural and spectral properties have been analyzed by employing the relativistic configuration interaction (RCI) technique using the ion sphere model as the modified interactive potential between the nucleus and the electron. It is observed that for every transition, the transition energies are red shifted. The plasma screening effect on weighted oscillator strengths has also been examined. Additionally, the ground state thermodynamic pressure within the ion sphere and the radial wavefunctions of the spectral electron for the various states of N⁶⁺, Ne⁹⁺, and Al¹²⁺ ions at plasma density 1 × 10²³ cm^–3 were also studied. The line intensity ratio has also been computed for the first two spectral lines: [1s_1/2 – 2p_3/2 (1–3)] and [1s_1/2 – 2p_1/2 (1–2)]. Our computed data exhibits a good quantitative agreement with the other results reported in the literature as well as with the experimental results reported in the National Institute of Science and Technology (NIST) database. The current findings will be helpful in laboratory and astrophysical plasma modelling and characterization of hot dense plasma.

The magnetic-field dependence of the superparamagnetic-blocking temperature T_B of systems of antiferromagnetically ordered ferrihydrite nanoparticles has been investigated and analyzed. We studied two powder systems of nanoparticles: particles of “biogenic” ferrihydrite (with an average size of 2.7 nm), released as a result of vital functions of bacteria and coated with a thin organic shell, and particles of biogenic ferrihydrite subjected to low-temperature annealing, which cause an increase in the average particle size (to 3.8 nm) and burning out of the organic shell. The character of the temperature dependences of magnetization, measured after cooling in a weak field, as well as the shape of the obtained dependences T_B(H), demonstrate peculiar features, indicating the influence of magnetic interparticle interactions. A detailed analysis of the dependences T_B(H) within the random magnetic anisotropy model made it possible to estimate quantitatively the intensity of magnetic particle–particle interactions and determine the magnetic anisotropy constants of individual ferrihydrite particles.

In several recent years, a significant progress has been made in atomistic simulation of materials, involving the application of machine learning methods to constructing classical interatomic interaction potentials. These potentials are many-body functions with a large number of variable parameters whose values are optimized with the use of energies and forces calculated for various atomic configurations by ab initio methods. In the present paper a machine learning potential is developed on the basis of deep neural networks (DP) for Al–Cu alloys, and the accuracy and performance of this potential is compared with the embedded atom potential. The analysis of the results obtained implies that the DP provides a sufficiently high accuracy of calculation of the structural, thermodynamic, and transport properties of Al–Cu alloys in both solid and liquid states over the entire range of compositions and a wide temperature interval. The accuracy of the embedded atom model (EAM) in calculating the same properties is noticeably lower on the whole. It is demonstrated that the application of the potentials based on neural networks to the simulation on modern graphic processors allows one to reach a computational efficiency on the same order of magnitude as those of the embedded atom calculations, which at least four orders of magnitude higher than the computational efficiency of ab initio calculations. The most important result is that about the possibility of application of DP parameterized with the use of configurations corresponding to melts and perfect crystals to the simulation of structural defects in crystals and interphase surfaces.

We proposed a theoretical model and a method for its approximate analysis for flows induced by a uniform rotating magnetic field in a channel filled with a nonmagnetic fluid with a ferrofluid layer injected into it. One end of the channel is assumed to be blocked (thrombosed). This study is aimed at the development of the scientific basis of the magnetically induced intensification of drug transport in blocked blood vessels.