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Hydrothermally grown NiO nanoflakes have been investigated here for their resistive switching (RS) and photoabsorption characteristics. The formation and disruption of the conducting filament (CF) under an applied external electric field leads to bistable resistive switching in the grown NiO nanoflakes. Comprehensive investigations of the I–V behaviour show that the formation and rupturing of the CF depend on the concentration of the metallic Ni. Interestingly, photoabsorption response demonstrates a nearly similar behaviour in UV and visible regions for nanoflakes grown at low reaction time, but an enhanced UV response for the flakes obtained at larger reaction times. These nanoflakes displaying multifunctional properties of photoabsorption and RS behaviour, that can be modulated with reaction time, are attractive for optoelectronic, electrochromic and RS-based memory applications.

The Yukawa-plus-exponential model (YEM) is the modified form of liquid drop model incorporating parameter to include short-range interaction and surface diffuseness. We have studied two-proton (2p) radioactivity within the YEM for spherical nuclei in our previous work [Mehana and Rajeswari in Eur. Phys. J. A 59, 104 (2023)]. The present study is the extension of the previous work to apply the model to deformed 2p emitters. Deformation is incorporated in YEM through Coulomb potential and Yukawa interaction potential. The calculated half-lives are found to have less deviation than experimental half-lives, when compared to spherical ones. Further, half-lives are also predicted for 2p emitters which are not yet studied experimentally. The calculated half-lives show good match with half-lives predicted by other theoretical models. It is seen that the half-lives of the prolate-shaped daughter nuclei are lower than spherical nuclei of the same parent, whereas the half-lives of oblate daughters are higher than that of the spherical ones.

This research work aims to explain the model and assessment of a differential mathematical system of the magneto-bioconvection of the Williamson nanofluid model (MBWNFM) by capitalising on the strength of the stochastic technique through computational intelligence of Bayesian regularisation back-propagated neural networks (CIBRB-NNs). This facilitates a more accurate, reliable and proficient computation of the dynamics. A reference dataset is built using the Adams technique in the Mathematica software to depict multiple situations and account for numerous influential parameters of the MBWNFM. The reference data results are split into 70% for training and 30% for validation and testing methods. This approach aims to enhance the accuracy of the approximated results and enable them to be compared with established solutions. The demonstration of the accuracy and efficiency of the created CIBRB-NNs involves a comparison of the results obtained from the dataset using the Adams approach, by adjusting several influential parameters which include magnetic parameter ((M)), bioconvection Lewis Number ((L_{b})), thermal diffusivity ((alpha)) and thermal Biot number ((gamma)). The stability and accuracy of CIBRB-NNs are validated using various methodologies, including the analysis of fitness curves depicting mean square error, regression studies, evaluation of error using histogram plots and measurement of absolute errors. The excellent measures of performance in terms of MSE are achieved at levels 4.50e-12, 6.73e-13, 1.07e-13, 7.08e-13, 4.77e-13 and 1.70e-13 against 82, 150, 98, 83, 170 and 189 epochs. The error analysis of the proposed and reference datasets shows that CIBRB-NNS is authentic and precise, ranging from e-09 to e-04 for all scenarios.

Two different control methods are proposed in this paper to effectively control the chaotic phenomenon of nonlinear dynamical system. One is a new Hamilton energy feedback control method based on Helmholtz’s theorem, which reduces the Lyapunov exponents value of the system by adjusting the feedback gain for controlling chaos. The other is to control the chaos of the system by using delayed feedback control method. Based on this method, we consider the local asymptotic stability of the equilibrium point of the system, and give conditions for the existence of the Hopf bifurcation of the system and the stability domain of the delay parameters. By using the centre manifold theorem and the Poincare normal form method, specific formulas for determining the direction of Hopf bifurcation and the stability of the bifurcation periodic solutions are derived. Finally, the simulation results show that chaos can be controlled by choosing appropriate time-delay parameters.

This paper explores the evolution of gravastars within the context of the Lyra geometry. The mathematical formulations of the three regions of a gravastar: (i) the inside region, (ii) the shell region and (iii) the external void region are described separately, along with their physical characteristics and graphical representations. The study explores different aspects of our model by analysing the behaviour of physical parameters. It solves the modified Einstein’s field equations, which are derived from this geometry, under the conditions of gravastar formation. The investigation focusses on the physical properties of the shell region, such as energy density, proper length, full energy, entropy, surface tension, thinness and energy conditions. Additionally, the stability of the gravastar model is examined by analysing the surface red-shift in relation to the shell length.

Computer model has been extensively adopted to overcome the time limitation of language evolution by transforming language theory into physical modelling mechanism, which helps to explore the general laws of evolution. In this paper, a model is designed to simulate the evolution process of languages in human settlements, with the associated network topology being lattice. The language of each node in the lattice will evolve gradually under the influence of its own fixed evolutionary direction and neighbours. According to the computational experiment results, it is discovered that the state points of languages always converge into several clusters during the evolution process, which gives us an insight into language evolution.

This article presents an analysis and control approach for a non-smooth air-gap permanent magnet synchronous motor (NSAG-PMSM) in the absence of external disturbances. The analytical study of NSAG-PMSM shows the existence of equilibrium points. Based on the Routh–Hurwitz criterion, the stability of the equilibrium points reveals the existence of transcritical bifurcation. NSAG-PMSM exhibits various dynamical behaviours, such as bistable chaos, periodic spiking oscillations, chaotic spiking characteristics, coexistence between periodic and chaotic behaviours and periodic evolution towards monostable chaos as system parameters change. The research uses microcontroller implementation to validate the dynamical characteristics observed during the numerical simulations of the NSAG-PMSM. The study of NSAG-PMSM proposes a strategy to mitigate chaos and stabilise the system using two simple controllers, with a comparative study presented using peak overshoot and settling time diagrams. By combining these different aspects, this article significantly contributes to the understanding of the operation in NSAG-PMSM, highlighting specific aspects related to the application of microcontroller techniques in the field of electrical engineering and solutions to chaos control.

In this paper, we study the travelling wave parametric amplifier-superconducting nonlinear asymmetric inductive element (TWPA-SNAIL) transmission line circuit equation and its variable coefficients form, which may describe transmission line circuits for travelling wave parametric amplifiers including superconducting nonlinear asymmetric inductive elements. We derive some exact solutions, including dark soliton, bright soliton, periodic, trigonometric function and hyperbolic function solutions using Jacobi elliptic function expansion method. The soliton solutions of this circuit equation are useful to analogue black–white hole event horizon pairs. To better describe the dynamical behaviour of these solutions, we plot three-dimensional density and two-dimensional images. By varying the parameters, we find that some parameters have an effect on the structure of the solution. In addition, for the variable coefficient equations, we present images containing trigonometric and exponential functions in the solution and obtain some satisfactory results by comparing the graphs with the coefficient functions. The results show that the Jacobi elliptic function expansion method is a remarkable, direct and desirable method for solving a class of nonlinear partial differential equations.

Aerospace research is increasingly focusing on propulsion system analysis. Heat transmission at high temperatures controlled by thermal radiation is used in spaceship propulsion systems. Hence, the current work investigates the magneto-Williamson nanofluid peristalsis flow in relation to thermal effect and slip-boundary circumstances with double-diffusion convection. In the flow's opposite direction, a steady, static magnetic field is applied. A mathematical model with appropriate boundary conditions is built by considering the momentum, continuity and energy equations. By considering the long wavelength and low Reynold estimation, the resulting equations are further made simpler. Then a numerical solution to the resulting reduced partial differential equations is obtained. Finally, there is a visual representation of the non-Newtonian propelling flow parameters, which include the Brinkman number, Prandtl number, Hartmann number, radiation parameter, particle volume fraction, electric field and slip parameters. It is highlighted that enhancing the coefficient of thermophoresis strengthens the temperature contour because increasing the number of particles merged enhances thermophoretic power. Furthermore, because of the substantial migration of nanoparticles from a heated region to a cooled one, the distribution of concentration becomes less cumbersome. It is also revealed that the fraction of nanoparticles rises because of rising thermal radiation and Brownian motion because nanofluids have a significant temperature distribution that may affect the system's distribution.

The radiation impact on the thermal distribution of the radial fin with the temperature-dependent thermal conductivity is discussed in this paper. The basic governing heat equation of the radial fin is formulated with the assistance of the Fourier law of heat conduction. The dimensional heat equation of the radial fin is non-dimensionalised utilising appropriate dimensionless variables and this ordinary differential equation (ODE) is tackled by employing the physics-informed neural network (PINN) scheme. The thermal attributes of the radial fin are investigated for different parameters like convection–conduction parameter, radiation–conduction parameter and thermal conductivity parameter. The outcomes of the systematic assessments of these parameters are demonstrated with the support of graphs. The rise in the thermal conductivity variable promotes thermal variation in the fin. A decrease in radiative–conductive variable scales augments the temperature dispersal through the fin. Furthermore, PINN incorporates physics equations directly into its architecture, unlike standard numerical approaches, which frequently require extensive mathematical expertise for accuracy. This approach enables PINN to give precise findings even when working with minimal training data, saving substantial time and resources.