The European Physical Journal B最新文献

In recent years, two-dimensional (2D) superconducting materials have garnered significant interest due to their unique properties and potential applications. Here, we conducted thermodynamic and dynamic stability studies on 51 metal-intercalated hexagonal boron carbon (h-BC) compounds, and ultimately identified 22 stable compounds. Among these 22 compounds, 18 materials are metals, while the remaining 4 materials include 1 semiconductor ((hbox {MgB}_{2}hbox {C}_{2})) and 3 semimetals ((hbox {TiB}_{2}hbox {C}_{2}), (hbox {ZrB}_{2}hbox {C}_{2}), and (hbox {HfB}_{2}hbox {C}_{2})). The possible superconductivity of eighteen metals is studied by solving the Allen–Dynes modified McMillan equation to estimate their superconducting transition temperature ((T_{c})). The highest (T_{c}) is observed in (hbox {KB}_{2}hbox {C}_{2}) ((T_{c}) = 53.47 K), followed by (hbox {NaB}_{2}hbox {C}_{2}) ((T_{c}) = 48.30 K), while the lowest (T_{c}) is in (hbox {AlB}_{2}hbox {C}_{2}) ((T_{c}) = 0.04 K). Due to the high (T_{c}) of alkali metal intercalation compounds, this work mainly focuses on them. For alkali metal intercalation compounds, we found that the (T_{c}) rises with the increase of the main group atomic number, mainly due to the degree of metalization of the (sigma )-bonding band at the Fermi level. Another important reason is the softening of the phonon spectrum. These findings enrich the family of 2D superconductors, providing new theoretical insights for experimental synthesis and opening research ideas for 2D superconducting electronic devices.

This paper offers a unique synchronization strategy for synchronizing eight chaotic systems. The new approach is referred to as dual quadratic compound anti synchronization. We additionally employed signal multi-switching to augment the complexity of the suggested technique. In communication theory, the transmission and security of the resulting signal are more effective because of the numerous combinations of chaotic systems and multiswitching that provide such complicated dynamic behavior. To demonstrate the acquired results, Lorenz, Rössler, Lü, and Chen chaotic system are used. Using the Lyapunov stability principle, sufficient conditions are attained and appropriate controllers are built to achieve the required synchronization between eight chaotic systems. To validate the findings from theory, numerical simulations, and graphics are presented using MATLAB.

Motif discovery is a powerful and insightful method to quantify network structures and explore their function. As a case study, we present a comprehensive analysis of regulatory motifs in the connectome of the model organism Caenorhabditis elegans (C. elegans). Leveraging the Efficient Subgraph Counting Algorithmic PackagE (ESCAPE) algorithm, we identify network motifs in the multi-layer nervous system of C. elegans and link them to functional circuits. We further investigate motif enrichment within signal pathways and benchmark our findings with random networks of similar size and link density. Our findings provide valuable insights into the organization of the nerve net of this well-documented organism and can be easily transferred to other species and disciplines alike.

Quantum rings have emerged as a playground for quantum mechanics and topological physics, with promising technological applications. Experimentally realizable quantum rings, albeit at the scale of a few nanometers, are 3D nanostructures. Surprisingly, no theories exist for the topology of the Fermi sea of quantum rings, and a microscopic theory of superconductivity in nanorings is also missing. In this paper, we remedy this situation by developing a mathematical model for the topology of the Fermi sea and Fermi surface, which features non-trivial hole pockets of electronic states forbidden by quantum confinement, as a function of the geometric parameters of the nanoring. The exactly solvable mathematical model features two topological transitions in the Fermi surface upon shrinking the nanoring size either, first, vertically (along its axis of revolution) and, then, in the plane orthogonal to it, or the other way round. These two topological transitions are reflected in a kink and in a characteristic discontinuity, respectively, in the electronic density of states (DOS) of the quantum ring, which is also computed. Also, closed-form expressions for the Fermi energy as a function of the geometric parameters of the ring are provided. These, along with the DOS, are then used to derive BCS equations for the superconducting critical temperature of nanorings as a function of the geometric parameters of the ring. The (T_c) varies non-monotonically with the dominant confinement size and exhibits a prominent maximum, whereas it is a monotonically increasing function of the other, non-dominant, length scale. For the special case of a perfect square toroid (where the two length scales coincide), the (T_c) increases monotonically with increasing the confinement size, and in this case, there is just one topological transition.

We introduce new machine learning techniques for analyzing chaotic dynamical systems. The main goal of this study is to develop a simple method for calculating the Lyapunov exponent using only two trajectory data points, in contrast to traditional methods that require averaging procedures. Additionally, we explore phase transition graphs to analyze the shift from regular periodic to chaotic dynamics, focusing on identifying “almost integrable” trajectories where conserved quantities deviate from whole numbers. Furthermore, we identify “integrable regions” within chaotic trajectories. These methods are tested on two dynamical systems: “two objects moving on a rod” and the “Henon–Heiles” system.