Junction Model Research Articles

Dynamics and comparative study of the synchronization of some Josephson junction models

In this work, the chaotic dynamics of some Josephson junction models and their synchronization are studied. First, the dynamics of the different junctions have been studied through bifurcation diagrams and corresponding Lyapunov exponents. As the case of junctions based on high temperature superconductors, the dynamics of RCLSJ and fractal junctions have been studied by taking into account the non-harmonicity parameter of the super current of the junction. Then, the identical synchronization between two RCLSJ models is realized for the null and non-null values of the non-harmonic parameter. We then showed that the reduced-order synchronization of the RCLSJ model with three other models can be achieved using both feedback constants and Lyapunov’s stability theory for different values of the non-harmonic constant taken in the chaotic domain.

Seismotectonic model of High-Middle Atlas Junction (Morocco) derived from earthquake focal mechanism and stress tensor analysis

Seismotectonic model of High-Middle Atlas Junction (Morocco) derived from earthquake focal mechanism and stress tensor analysis

Hybrid Models in Forecasting Short Term Road Traffic

Objectives: To analyze the road traffic in Hyderabad at a selected junction and fit Hybrid model for forecasting the traffic conditions for the next near future also to compare the proposed model with the existing popular models and identifying the best model for forecasting the Hyderabad road traffic. Methods: This study considers the data on traffic flow at 6.no. junction in Amberpet, Hyderabad, Telangana state, India. The traffic data has been considered for peak hours in the morning for 8 A.M to 12 Noon, for 6 days. Classical Time series models and recent revolution in time series modelling - Artificial Neural Networks have been applied to develop a forecasting model. Then we combined these models to obtain the Hybrid model for forecasting the road traffic at the selected point. SPSS and Zytun softwares have been used for the analysis. The best fit statistics such as RMSE, MAPE and MAE have been used to identify the best model. Findings: Our study indicates the efficacy of the new combinatorial model in acquiring more accurate forecasting as compared to independent models. These results can be considered to monitor traffic signals and explore methods to avoid congestion at that junction. Novelty: Though some research has been done in Hyderabad, no work has been done to develop a model for forecasting the Hyderabad road traffic. Our model can give the best forecasts for the Hyderabad road traffic. Keywords: Multilayer Perceptron; Hybrid model; Exponential smoothing; Artificial Neural Network; Intelligent Transport System

Optical Trapping of a Single Molecule of Length Sub-1 nm in Solution

Optical Trapping of a Single Molecule of Length Sub-1 nm in Solution

Pore-Scale Simulation of Gas and Water Two-Phase Flow in Rough-Walled Fractures Using the Volume of Fluid Method

The gas and water flow behavior in rough-walled hydrophilic fractures at the pore scale is crucial for understanding the gas production characteristics of naturally fractured formations. This paper presents a systematic analysis of the gas and water flow characteristics in both the single-fracture and Y-shaped junction fracture models using the volume of fluid (VOF) method. Numerical simulations showed that the gas/water rate ratio is the most significant factor influencing gas bubble/slug geometry, phase distribution, and saturation. The effect of fracture roughness and tortuosity is less significant than the gas/water ratio, whereas the total fluid rate has a negligible effect. For Y-shaped junction models, the phase distribution and referential pathways are predominantly controlled only by the channel aperture ratio, whereas the effect of the intersecting angle and fluid flow rate can be neglected.

Explaining the climate sensitivity of junction geometry in global river networks

Rivers form characteristic branching patterns as they drain landscapes. Past work has shown that the angles formed between confluent channels at river junctions vary with climate aridity-but why this occurs is contested. We show how this climate sensitivity can be explained by the principle that river networks self-organize toward "optimal" configurations that minimize the hydraulic expenditure of energy. Starting from this energy minimization principle, optimal junction configurations can be calculated given three variables: the drainage area ratio of confluent channels, the scaling exponent relating channel gradient to drainage area (often called the concavity index), and the scaling exponent relating discharge to drainage area. Given that concavity and discharge-drainage area scaling vary with climate aridity, optimal junction angle theory can explain junction angle climate sensitivity. We extracted a global dataset of approximately 26 million junctions and show that the predictions of the optimal junction model are consistent with the sensitivity of junction angles to climate aridity. Our dataset includes not only the junction angle between confluent tributaries but also the "bending angles" between each tributary and the downstream channel, enabling us to quantify junction symmetry. As in the model, the geometric symmetry of real junctions is strongly controlled by the discharge ratio of the confluent channels. However, junctions with strongly asymmetric tributary drainage areas do not exhibit optimal geometries: minor tributaries show a tendency to join large rivers at the outside apex of large-scale bends.

Transition of self-passivation and semiconductor property of titanium in the simulated environments of proton exchange membrane fuel cells

In this work, the passivation behaviors of titanium at various solution acidities are investigated in the simulated environments of proton exchange membrane fuel cells. The results show that there is a critical pH value to initiate the self-passivation of titanium, and a mathematic method based on the potentiodynamic polarization curve analysis is proposed to verify this value. The semiconductor type of the passive film changes from n-type to bipolar type, then to p-type as the pH increases, which can be explained by an n/p junction model. In addition, the relationship of the passive film thickness and pH is consistent with the prediction of point defect model.

ВЛИЯНИЕ ПАРАМЕТРОВ YBACUO ДЖОЗЕФСОНОВСКОГО ПЕРЕХОДА НА ХАРАКТЕРИСТИКИ ШИРОКОПОЛОСНОГО ДЕТЕКТИРОВАНИЯ

For Josephson bicrystal YBaCuO junctions 3–1.5 µm in size, the response to an external signal with a frequency of 165 GHz was measured. Receivers with similar ICRN values at helium temperatures and different RN values were chosen for the study. The amplitudes of the Shapiro steps were measured for various external signal powers and sample temperatures. The dependence of the output voltage noise on the operating point, temperature, and external signal power was measured. It is shown that fluctuations of the critical current have the greatest influence on the output noise of the receiver. The volt-watt responsivity and noise-equivalent power were evaluated for a 165 GHz external signal. The experimental results are compared with numerical calculations based on the model of a resistive-capacitive shunted Josephson junction. Optimal temperature operating ranges for the use of each structure were shown.

Identical and reduced-order synchronizations of some Josephson junctions model

Identical and reduced-order synchronizations of some Josephson junctions model

Comparative Insights into the Fundamental Steps Underlying Gelation of Plant and Algal Ionic Polysaccharides: Pectate and Alginate.

Pectate and alginate are among the most important biopolymers able to give rise to ionotropic gelation upon the addition of di- or multivalent counterions. The two ionic polysaccharides exhibit several common aspects of the gelation mechanism with calcium ions, the physiologically and commercially most relevant counterion type. The first one pertains to the role that specific Ca2+/polyion interactions play in the establishment of the ion-mediated chain/chain cross-links. Such interactions include both a specific affinity of the territorially condensed Ca2+ counterions for the polyuronate(s) and the formation of long-lasting chemical bonding (inner ion-sphere complex) of specific interchain sites accompanied by high conformational ordering. As to the first mechanism, it is dominated by the strong desolvation of the interacting ionic species, with concomitant positive variations in both enthalpy and entropy, the contribution of the latter prevailing over the former due to the favorable liberation of a very large number of water molecules of hydration. Both dilatometric and microcalorimetric data point to the higher affinity of Ca2+ for pectate than for alginate. The selective accumulation of calcium ions close to the polyanion(s) favors the onset of the second-chemical bonding-mode, which is associated with charge neutralization at the bonding site. This mode coincides with the largely accepted "egg-box" model for the calcium-mediated interchain junction of pectate and alginate. A new approach was devised for the calculation of the fraction of chemically bound divalent ions; it was based on the available circular dichroism data (further supported by scattering and viscosity results) and successfully tested by comparison with an independently determined fraction in the case of pectate. In detail, the strong bonding mode manifests in two sequential bonding modes. The first one (at low concentrations of added Ca2+ ions) entails a cross-link in which only one calcium ions is bracketed in a "twisted" egg-box between two chains; upon further counterion addition, a series of nearest-neighboring "perfect" egg-box structures develops. Both dilatometric and microcalorimetric changes associated with the latter chemical bonding modes are quantitatively larger for pectate than for alginate; clearly the latter polyuronate suffers from the relevant presence of the weakly calcium-binding mannuronic acid repeating units. Light-scattering experiments provided a clear-cut demonstration of the intermolecular bonding of calcium ions from the very beginning of the linker addition.

Alignment of Skeletal Muscle Cells Facilitates Acetylcholine Receptor Clustering and Neuromuscular Junction Formation with Co-Cultured Human iPSC-Derived Motor Neurons

In vitro neuromuscular junction (NMJ) models are powerful tools for studying neuromuscular disorders. Although linearly patterned culture surfaces have been reported to be useful for the formation of in vitro NMJ models using mouse motor neuron (MNs) and skeletal muscle (SkM) myotubes, it is unclear how the linearly patterned culture surface increases acetylcholine receptor (AChR) clustering, one of the steps in the process of NMJ formation, and whether this increases the in vitro NMJ formation efficiency of co-cultured human MNs and SkM myotubes. In this study, we investigated the effects of a linearly patterned culture surface on AChR clustering in myotubes and examined the possible mechanism of the increase in AChR clustering using gene expression analysis, as well as the effects of the patterned surface on the efficiency of NMJ formation between co-cultured human SkM myotubes and human iPSC-derived MNs. Our results suggest that better differentiation of myotubes on the patterned surface, compared to the flat surface, induced gene expression of integrin α7 and AChR ε-subunit, thereby increasing AChR clustering. Furthermore, we found that the number of NMJs between human SkM cells and MNs increased upon co-culture on the linearly patterned surface, suggesting the usefulness of the patterned surface for creating in vitro human NMJ models.

Technical note: A sigmoidal soil water retention curve without asymptote that is robust when dry-range data are unreliable

Abstract. In a recently introduced parameterization for the soil water retention curve (SWRC) with a sigmoid wet branch and a logarithmic dry branch, the matric potential at the junction point of the sigmoid and the logarithmic branch (hj) was a fitting parameter, while that at oven dryness (hd) was derived from the fitting parameters. The latter is undesirable, especially if reliable data in the dry range are limited. Therefore, an alternative is presented in which shape parameter α instead of hd is a derived parameter, and hd can be fitted or fixed. The resulting relationship between α and hj is such that it prevents correct fits for hj. Fortunately, an expression for hj is found that allows it to be replaced by α as a fitting parameter. The corresponding parameter space is well behaved and has fewer internal bounds defined by restraining relationships between parameters than the space for hj as a fitting parameter. The few available values of hj in the literature are in line with those according to the new expression. The reformulated SWRC is fitted to data of 21 soils by shuffled complex evolution. The paper gives the main features of an accompanying open source fitting code. The curves fit the data well, except for some clayey soils. A theoretical value of hd performs well for a wide range of soils. The new SWRC simplifies to an earlier junction model of the SWRC based on a well known power-law SWRC if α is very large.

Proposal for Detection of the 0^{'} and π^{'} Phases in Quantum-Dot Josephson Junctions.

The competition between the Kondo correlation and superconductivity in quantum-dot Josephson junctions (QDJJs) has been known to drive a quantum phase transition between 0 and π junctions. Theoretical studies so far have predicted that under strong Coulomb correlations the 0-π transition should go through intermediate states, 0^{'} and π^{'} phases. By combining a nonperturbative numerical method and the resistively shunted junction model, we investigated the magnetic-field-driven phase transition of the QDJJs in the Kondo regime and found that the low-field magnetotransport exhibits a unique feature which can be used to distinguish the intermediate phases. In particular, the magnetic-field driven π^{'}-π transition is found to lead to the enhancement of the supercurrent which is strongly related to the Kondo effect.

Emergence of negative viscosities and colored noise under current-driven Ehrenfest molecular dynamics

Molecules in molecular junctions are subject to current-induced forces that can break chemical bonds, induce reactions, destabilize molecular geometry, and halt the operation of the junction. Theories behind current-driven molecular dynamics simulations rely on a perturbative time-scale separation within the system with subsequent use of nonequilibrium Green's functions (NEGF) to compute conservative, non-conservative, and stochastic forces exerted by electrons on nuclear degrees of freedom. We analyze the effectiveness of this approximation, paying particular attention to the phenomenon of negative viscosities. The perturbative approximation is directly compared to the nonequilibrium Ehrenfest approach. We introduce a novel time-stepping approach to calculate the forces present in the Ehrenfest method via exact integration of the equations of motion for the nonequilibrium Green's functions, which does not necessitate a time-scale separation within the system and provides an exact description for the corresponding classical dynamics. We observe that negative viscosities are not artifacts of a perturbative treatment but also emerge in Ehrenfest dynamics. However, the effects of negative viscosity have the possibility of being overwhelmed by the predominantly positive dissipation due to the higher-order forces unaccounted for by the perturbative approach. Additionally, we assess the validity of the white-noise approximation for the stochastic forces, finding that it is justifiable in the presence of a clear time-scale separation and is more applicable when the current-carrying molecular orbital is moved outside of the voltage window. Finally, we demonstrate the method for molecular junction models consisting of one and two classical degrees of freedom.

Geometric quantum thermodynamics.

Building on parallels between geometric quantum mechanics and classical mechanics, we explore an alternative basis for quantum thermodynamics that exploits the differential geometry of the underlying state space. We focus on microcanonical and canonical ensembles, looking at the geometric counterpart of Gibbs ensembles for distributions on the space of quantum states. We show that one can define quantum heat and work in an intrinsic way, including single-trajectory work. We reformulate thermodynamic entropy in a way that accords with classical, quantum, and information-theoretic entropies. We give both the first and second laws of thermodynamics and Jarzynki's fluctuation theorem. Overall, this results in a more transparent physics than conventionally available. The mathematical structure and physical intuitions underlying classical and quantum dynamics are seen to be closely aligned. The experimental relevance is brought out via a stochastic model for chiral molecules (in the two-state approximation) and Josephson junctions. Numerically, we demonstrate this invariably leads to the emergence of the geometric canonical ensemble.

A Universal Compact Model for Spin-Transfer Torque-Driven Magnetization Switching in Magnetic Tunnel Junction

Current-induced magnetization switching through spin-transfer torque (STT) has shown great potential for low-power information storage. However, predicting its mesoscopic behavior induced by both electrical current and thermal fluctuation is a fundamental challenge in spintronics. Moreover, the physical models in different switching regimes have not been properly unified. Here, we propose a novel analytical model to describe the mean magnetization switching time in general terms. By incorporating a nondimensional parameter <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> in (0,1) to elucidate the relative impact of thermal activation and current, the unified model shows good agreement with the experimental data in all the regimes, including high current regime, thermal activation regime, and the intermediate regime between them. Finally, we develop an electrical model of magnetic tunnel junction (MTJ) device with Verilog-A language and perform transient simulation to demonstrate its functionality with Spectre. The Monte Carlo simulations have also been implemented to confirm their stochastic switching behavior. This model will be greatly beneficial for accurate and efficient designs for spintronic-based integrated circuits.

MFA-MTJ Model: Magnetic-Field-Aware Compact Model of pMTJ for Robust STT-MRAM Design

The popularity of perpendicular magnetic tunnel junction (pMTJ)-based spin-transfer torque magnetic random access memories (STT-MRAMs) is growing very fast. The performance of such memories is very sensitive to magnetic fields, including both internal and external ones. This article presents a magnetic-field-aware compact model of pMTJ, named the MFA-magnetic tunnel junction (MTJ) model, for magnetic/electrical co-simulation of MTJ/CMOS circuits. Magnetic measurement data of MTJ devices, with diameters ranging from 35 to 175 nm, are used to calibrate an in-house magnetic coupling model. This model is subsequently integrated into our developed compact pMTJ model, which is implemented in Verilog-A. The superiority of the proposed MFA-MTJ model for device/circuit co-design of STT-MRAM is demonstrated by simulating a single pMTJ as well as STT-MRAM full circuits. The design space is explored under PVT variations and various configurations of magnetic fields.

Josephson Diode Effect in High-Mobility InSb Nanoflags.

We report nonreciprocal dissipation-less transport in single ballistic InSb nanoflag Josephson junctions. Applying an in-plane magnetic field, we observe an inequality in supercurrent for the two opposite current propagation directions. Thus, these devices can work as Josephson diodes, with dissipation-less current flowing in only one direction. For small fields, the supercurrent asymmetry increases linearly with external field, and then it saturates as the Zeeman energy becomes relevant, before it finally decreases to zero at higher fields. The effect is maximum when the in-plane field is perpendicular to the current vector, which identifies Rashba spin-orbit coupling as the main symmetry-breaking mechanism. While a variation in carrier concentration in these high-quality InSb nanoflags does not significantly influence the supercurrent asymmetry, it is instead strongly suppressed by an increase in temperature. Our experimental findings are consistent with a model for ballistic short junctions and show that the diode effect is intrinsic to this material.

Revealing Intrinsic Superconductivity of the Nb/BiSbTe2Se Interface

AbstractTypically, topological superconductivity is reachable via proximity effect by a direct deposition of superconductor (S) on top of a topological insulator (TI) surface. Here, the double critical current in the Josephson junctions based on the topological insulator is observed in the fabricated planar Superconducting Quantum Interference Devicea. By measuring critical currents as a function of temperature and magnetic field, it is shown that the second critical current stems from the intrinsic superconductivity of the S–TI interface, which is supported by the modified Resistively Shunted Junction model and Transmission Electron Microscopy studies. This complex structure of the interface should be taken into account when the technological process involves Ar‐plasma cleaning.

Safety and Sustainable Development of Automated Driving in Mixed-Traffic Urban Areas—Considering Vulnerable Road Users and Network Efficiency

Next to environmental aspects, establishing areas for safe and economically viable automated driving in mixed-traffic settings is one major challenge for sustainable development of Autonomous Vehicles (AVs). This work investigates safety in the interactions between AVs, human-driven vehicles, and vulnerable road users, including cyclists and pedestrians, within a simulated urban environment in the Dutch city of Rotterdam. New junction and pedestrian models are introduced, and virtual AVs with an occlusion-aware driving system are deployed to deliver cargo autonomously. The safety of applying this autonomous cargo delivery service is assessed using a large set of Surrogate Safety Indicators (SSIs). Furthermore, Macroscopic Fundamental Diagrams (MFDs) and travel time loss are incorporated to evaluate the network efficiency. By assessing the impact of various measures involving Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), Vehicle-to-Everything (V2X) communications, infrastructure modifications, and driving behavior, we show that traffic safety and network efficiency can be achieved in a living lab setting for the considered case. Our findings further suggest that V2X gets implemented, new buildings are not placed close to intersections, and the speed limit of non-arterial roads is lowered.