Journal of the Korean Physical Society最新文献

Recently, considerable interest in Janus 2D materials has sparked various research investigations. Using density functional theory calculations, we study the atomic and electronic structure of six two-dimensional Janus GaInXO (X = S, Se, Te) materials to investigate their structural, vibrational, and piezoelectric properties. Their structural stability is evaluated through phonon calculations and molecular dynamics (MD) simulations at room temperature. The results show that OGaInTe is unstable, which is examined through crystal orbital Hamilton population (COHP) analysis. For the stable materials, Raman spectra are calculated for comparison with synthesis results. Furthermore, band-structure calculations with spin–orbit coupling are performed for SGaInO, SeGaInO, and OGaInS with bandgaps to evaluate their potential applications. Finally, calculations for piezoelectric properties reveal that OGaInSe exhibits the highest piezoelectric strain coefficient, confirming its strong potential as a piezoelectric device.

A computational study is presented for the impact of thermal radiation on incompressible magnetohydrodynamic (MHD) free convection within a square-shaped enclosure that is differentially heated and contains a non-Darcian porous medium saturated with an electrically conducting fluid. The Rosseland algebraic flux model is used to simulate radiative heat transport. The mass, momentum, and energy conservation equations, along with the corresponding boundary conditions, have been transformed into non-dimensional forms. The emerging dimensionless nonlinear boundary value problem is solved with the D2Q9-based lattice Boltzmann method. The main objectives are to determine the effects of Hartmann number, thermal radiation parameter, Darcy number, and Rayleigh number on the thermofluid characteristics for ionized hydrogen gas (Prandtl number, P (r=0.69)) in terms of the distributions of isotherms and streamlines. D2Q9-LBM code accuracy has been validated using a grid independence test. The current research’s findings are pertinent to the simulation of hybrid ionised MHD fuel cells and the production of magnetic materials.

Fe₂O₃@ZnO core–shell nanoparticles were synthesized in spherical and spindle shape and their performance in rhodamine B degradation was investigated. The average diameter of nanoparticles for the spherical samples was 47 and 28 nm, and for the spindle-shaped sample was 19 nm. By increasing the thickness of the ZnO shell in core–shell samples, the amount of absorption increases in both regions. The amount of absorption in the spindle-shaped samples was much higher than that of the spherical samples. The optical gap for spherical nanoparticles was 2.63 and 2.79 and for spindle shaped nanoparticles it was 3.07 eV. Finally, photocatalytic performance of Fe₂O₃@ZnO core–shell nanoparticles and Fe₂O₃–ZnO nanocomposites with ratios of (5:95), (10:90), (20:80) and (30:70) in degradation of rhodamine B (RhB) was investigated. The Fe₂O₃–ZnO nanocomposite (10:90) with 97% degradation of RhB in 180 min showed much better photocatalytic performance than the other nanocomposites and core–shell nanoparticles.

We investigate the dynamics of the SIRS epidemic model through both deterministic and stochastic frameworks, focusing on the effects of random fluctuations in key epidemiological parameters. After presenting the deterministic SIRS model using differential equations, the model is extended to include stochasticity by incorporating Itô stochastic differential equations (SDEs), where infection, recovery, and loss-of-immunity rates are treated as random variables. The corresponding Fokker–Planck equation is derived, capturing the evolution of the probability distribution of the infected population over time. We perform a linear stability analysis of the deterministic model and apply the fast-variable elimination method to reduce the two-variable SDE system to a single slow variable, leading to a simplified Fokker–Planck equation that describes the stationary distribution of the infected population. This reduction reveals that the stochastic epidemic threshold depends on the variances in the infection and recovery rates, but not on the variability in the loss-of-immunity rate. Simulation results, conducted using a Gillespie-type algorithm, validate the theoretical findings.

To synthesize highly crystalline carbon quantum dots (CQDs), we established a two-step process that integrates hydrothermal reactions and photothermal annealing with a xenon flash lamp. A xenon flash lamp enabled rapid and uniform heating, effectively enhancing crystallinity in a way that contrasts with conventional furnace annealing, which requires extended processing times. Transmission electron microscopy (TEM) analysis revealed that the high-temperature environment with a xenon flash lamp facilitated the conversion of the amorphous carbon structure into a more ordered crystalline form of CQDs. A comparison of Raman spectra and photoluminescence (PL) of amorphous CQDs and crystalline CQDs revealed significant differences between the two states. PL intensity of the crystalline CQDs was approximately ten times higher than that of amorphous CQDs, and this notable difference highlights an advantage of crystallizing CQDs: their optical performance is significantly enhanced.

Proton therapy is an advanced radiation therapy technique that allows for precise treatment of the tumor site. 3D water phantom system is the important testing equipment for proton therapy, which can guarantee the dose before treatment, and realize dose distribution scanning detection. It includes a lifting platform, a high-precision three-dimensional servo, ionization chambers, a control system, and a water tank. The lifting platform and high-precision three-dimensional servo are the key factors which can affect the accuracy of proton beam measurement. The 3D water phantom structure design is carried out to realize proton beam dose detection. Finite element analysis model is established to carry out mechanical mechanics analysis of the 3D water phantom structure. During scanning detection, the vibration generated by the servo motor operation may cause the 3D water phantom structure resonance, carry out modal analysis and harmonic response analysis, and calculate the 3D water phantom intrinsic frequency and motor operation vibration frequency within the possible resonance intervals. In addition, the 3D water phantom model was utilized to carry out Bragg peak detection experiments at different energies for proton therapy.

The process of manufacturing junctionless (JL) transistors is easier than inversion mode transistors, although source–channel-drain doping are the same between the two transistors. The decrease in carrier’s mobility/velocity capability in the channel of the JL transistors reduces the transconductance, Gm, as well other analog/radio-frequency parameters. Accordingly, it is recommended to use the Al_xGa_1−xN/GaN materials to improve the JL Gm. The simulation results show that for the thickness of the GaN layer, D = 1 nm, the mole fraction Al, and X = 0.3, the carrier’s mobility/velocity capability in the channel increases and thus results in the maximum transconductance Gm_max of the proposed device. In the proposed Al_xGa_1−xN/GaN, Gm_max = 2.24 mS/µm, and it is increased compared to the silicon-like structure JL-Si. The simulation results of the analog/radio frequency of the merit parameters of the Al_xGa_1−xN/GaN structure show that the maximum output resistance, the maximum intrinsic gain, the maximum unity gain cut-off frequency, and the maximum oscillation frequency are 2.49 TΩ, 34.03 dB, 831.5, and 2661 GHz, respectively. Maximum output resistance, maximum intrinsic gain, the unity gain cut-off frequency, and the maximum oscillation frequency of the Al_xGa_1−xN/GaN structure have all improved compared to their silicon structure counterparts with similar dimensions were 6 decades, 144, 49, and 19%, respectively. The proposed device can be an effective candidate for analog/ radio-frequency applications.

Heat and mass transfer in Newtonian fluid flows across inclined sheets, influenced by a magnetic field and Soret effects (thermal diffusion), is a complex phenomenon with several applications in engineering, geosciences, and industrial processes. This topic covers the foundations of fluid mechanics, thermodynamics, and electromagnetism. The aim of this work is to investigate the effects of the Soret factor on the Newtonian fluid flow across a contracting or extending inclined sheet. In order to solve the partial differential equations, this mathematical model transforms a set of partial differential equations into a set of ordinary differential equations, along with the necessary boundary conditions. The BVP4C approach then finds the problem's numerical and graphical solutions. The Soret effect raises the temperature profile while also boosting the concentration profile, based on the numerical and graphical data. The study's conclusion presents the physical interpretation of important parameters and accompanying numerical solutions. According to this study, as the Soret number grows, mass transfer rates increase, while drag force and heat transfer rates decrease. Slower skin friction results from the Soret number’s ability to lower the velocity gradient close to the surface by generating a concentration gradient. Because of temperature gradients, the Soret number encourages species separation in binary fluids, which lowers effective thermal diffusivity but raises the Sherwood number.

Flavor-changing neutral currents (FCNCs) are forbidden at tree level in the standard model (SM), but they can be enhanced in physics beyond the standard model (BSM) scenarios. In this paper, we investigate the effectiveness of deep learning techniques to enhance the sensitivity of current and future collider experiments to the production of a top quark and an associated parton through the tqg FCNC process, which originates from the tug and tcg vertices. The tqg FCNC events can be produced with a top quark and either an associated gluon or quark, while SM only has events with a top quark and an associated quark. We apply machine learning techniques to distinguish the tqg FCNC events from the SM backgrounds, including qg-discrimination variables. We use the Boosted Decision Tree (BDT) method as a baseline classifier, assuming that the leading jet originates from the associated parton. We compare with a transformer-based deep learning method known as the Self-Attention for Jet-parton Assignment (SaJa) network, which allows us to include information from all jets in the event, regardless of their number, eliminating the necessity to match the associated parton to the leading jet. The SaJa network with qg-discrimination variables has the best performance, giving expected upper limits on the branching ratios ({Br}(t rightarrow qg)) that are 25–35% lower than those from the BDT method.

Paramecia swim along helical trajectories propelled by the coordinated beating of the thousands of cilia covering their bodies. We have investigated how the swimming of populations of paramecium aurelia changes their swimming trajectories with varying viscosity, η, of their swimming medium to obtain their motor characteristics. The swimming speed distributions for 1 cP < η < 5.2 cP are Gaussian. The average instantaneous speed, v, and the variance, Δv, decrease monotonically with η. Simultaneously, their helical trajectories monotonically develop a greater pitch and radius. The product ηv is roughly constant over this factor of 5 change in η, indicating that paramecia aurelia swim with a constant propulsive force. Here, we present a phenomenological model of the beating cilia that produces the helical trajectory with a minimum number of swimming parameters. The model implies that the beat frequency of the body cilia decreases with increasing viscosity. The decrease can account for most of the observed decrease in swimming speed with η. We also find that the frequency of the cilia beating in the oral groove, which draws nutrients in, changes little with viscosity in sharp contrast with the body cilia responsible for propulsion.