International Journal of Numerical Modelling-Electronic Networks Devices and Fields最新文献

NiO/Ga₂O₃ heterojunctions are of significant interest due to their potential applications in power electronics and optoelectronics. Accurate extraction of capacitance-voltage (C-V) parameters is crucial for understanding their electrical characteristics and fundamental physical phenomena involved. In this context, this work investigates the temperature-dependent C-V characteristics of NiO/Ga₂O₃ heterojunction diodes (HJDs) before and after thermal annealing. The voltage barrier (V_B) and the effective doping density (N_eff) are extracted from these characteristics using the familiar analytical modeling (CAM) as well as an artificial intelligence (AI) based on particle swarm optimization (PSO) algorithm. N_eff showed a decrease with increasing temperature, which is unusual behavior and is related to deep defects in Ga₂O₃. Traps revealed by deep-level transient spectroscopy (DLTS) and Laplace-DLTS (LDLTS) measurements were exploited to perform simulation using SCAPS. First, an ideal NiO/Ga₂O₃ HJD is considered, and then the defects of the fresh and annealed samples are considered. The results confirmed the influence of traps and exhibited consistent behavior with the observed pattern. The band diagram evolution with temperature has provided further insight into this phenomenon. Furthermore, PSO results were compared with those of CAM and demonstrated that the PSO algorithm offers superior accuracy in parameter extraction, as evidenced by lower root mean square error (RMSE) values, reaching a minimum of 4.65 × 10⁻¹³. This approach provides a better method for evaluating the extracted parameters from the C-V characteristics of Ga₂O₃-based heterojunction devices.

In multi-distributed energy resource (DER) based microgrids, accurate islanding detection is critical to ensure personnel safety, equipment protection, and overall system stability. However, existing methods often struggle to reliably detect islanding under non-detection zone (NDZ) conditions and may suffer from false detections during non-islanding events (NIEs) such as load or capacitor switching. To address these limitations, this paper proposes a novel hybrid islanding detection technique combining passive and active approaches. The passive component utilizes the rate of change of total harmonic distortion (ROCTHD) to monitor voltage and current signals for islanding detection across various load conditions, including NDZ scenarios. However, to mitigate the possibility of false positives where NIEs are misclassified as islanding events (IEs) the method integrates an active current injection mechanism. This active component is triggered only when the passive method indicates a potential IE, thereby confirming the condition with minimal system disturbance. The proposed hybrid method is implemented in a multi-DER (MDER) test system modeled in MATLAB Simulink and validated using a real-time simulator (OP4510). The results demonstrate that the technique offers fast and more reliable islanding detection compared to traditional methods, with high accuracy under a wide range of operating conditions and negligible disruption during non-IEs.

This paper presents an efficient approach for solving a two-dimensional time-fractional pseudo-parabolic equation using a linearized finite difference scheme on variable time steps. The equation incorporates fractional derivatives in temporal dimensions to accurately model anomalous diffusion and memory effects in diverse physical phenomena. The study focuses on the challenges associated with solving multidimensional nonlinear time-fractional pseudo-parabolic equations, emphasizing the need for advanced numerical techniques to overcome computational complexities. Considering the localized characteristics of the fractional derivative and the memory property of fractional differential equations, the proposed method offers an efficient and accurate solution strategy tailored for time-fractional pseudo-parabolic equations. Building on previous research on nonuniform finite difference schemes for time-fractional diffusion problems, this study highlights the effectiveness of nonuniform time-stepping methods in achieving higher convergence orders in discretization schemes. The results demonstrate the utility of the proposed approach in accurately capturing the dynamics of complex transport processes in various physical systems. We rigorously prove that the proposed method has a convergence rate of order $��O�\left(�N^{�-�2�}�+�h_{x_1}^2�+�h_{x_2}^2�\right)�$. In addition, several numerical simulations are presented to verify the efficiency of the proposed method. The numerical results confirm the theoretical analysis.

In order to describe the RF behavior of active devices, accurate on-wafer characterization is essential. In this paper, four de-embedding methods are compared and their impacts on a gallium nitride high-electron-mobility transistor (GaN HEMT) are investigated. The S-parameters of the passive test structures are obtained using a 3-D electromagnetic (EM) simulator. On this basis, small-signal equivalent circuit models are established to compare the effects of these four de-embedding methods in the frequency range of 1 to 50 GHz. In addition, the influence on the calculation of the cutoff frequency $��f_T�$ and the maximum oscillation frequency $��f_{\max }�$ is also investigated. Subsequently, corresponding nonlinear models are established. The results indicate that these de-embedding methods affect the model parameters, but their effect on the simulation results of the device models is relatively minor.

We present a MATLAB-based simulation framework for structured light 3D measurement, designed to model complex scenarios and support algorithm evaluation and dataset generation. While structured light methods are widely used for 3D acquisition, existing simulation tools are limited to specific hardware or narrow use cases, restricting their utility. Our work addresses this gap by introducing (1) a unified abstract model that modularizes and encapsulates heterogeneous system components, balancing flexibility with consistent behavioral implementation, and (2) an open-architecture framework centered on a task-scheduling arbitrator, enabling scalable and evolvable simulations. The framework's design prioritizes practical extensibility, offering developers a reusable “how-to” model for building customizable simulations. We detail its implementation challenges and solutions, demonstrating how our approach reduces development overhead while accommodating diverse measurement scenarios. By enabling large-scale synthetic data generation and performance testing, the tool benefits both traditional algorithm designers and data-driven 3D vision pipelines. This work contributes a reusable software foundation for the 3D measurement community, with insights applicable to other simulation-driven domains.

This study provides an in-depth analysis of HIV and TB coinfection through a mathematical framework based on nonlinear fractional differential equations in the Caputo sense. We perform stability analysis of the equilibrium points using fractional techniques and utilize sensitivity analysis to determine the key parameters that influence disease transmission and control. The findings highlight the importance of controlling transmission rates to effectively reduce the burden of coinfection. The dynamics of both single and coinfection are examined via a fractional optimal control approach. We introduce and evaluate three control strategies aimed at decreasing infection levels, demonstrating the potential to achieve near-elimination. Comparing fractional and traditional models, we identify critical pathways for effective coinfection management. Our results provide valuable insights for policymakers to develop targeted interventions to lessen the impact of HIV and TB in affected communities.

In this article, a compact quad-port multiple-input-multiple-output (MIMO) broadband access wireless systems antenna on Rogers RTDuroid5880 with a dimension of 20 × 24 × 0.0254 mm³ giving impedance bandwidth spanning from 5.3 to 51.64 GHz is proposed. It is designed to cover a variety of frequency bands, including the Wireless LANs Band (5.725–5.85 GHz), X-band (8.00–12.0 GHz), Ku-band (12.0–18.0 GHz), K-band (18.0–27.0 GHz) and Ka-band (27.0–40.0 GHz) and specific frequency bands like FR2: n257 (26.50–29.50 GHz), n258 (24.25–27.50 GHz), n259 (39.5–43.5 GHz), n260 (37–40 GHz), n261 (27.50–28.35 GHz) and n262 (47 GHz). The partial ground is etched with a circular form patch to provide impedance matching, and the radiating patch has two circular shape slots with a dual ellipse formed by a star-shaped slit. Verifying this antenna's conformal capacity demonstrates that it is suitable for single-port, dual-port, and the suggested four-port antenna configurations, appropriate for a variety of applications. The reliable reception of transmitted signals in far-field areas is confirmed by time-domain analysis. Moreover, the antenna exhibits excellent diversity performance, as indicated by parameters like ECC_WMB, DG_WMB, TARC_WMB, and CCL_WMB, all of which meet or surpass permissible standard values. It achieves a maximum peak gain of 7.17 dBi and maintains stable 2D radiation patterns in principal planes. An important consideration for safety, the Specific-Absorption-Rate (SAR) analysis, is conducted at various operating frequencies within the Microwave-Millimeter wave bands. The results indicate that the SAR remains below the limit of 1.60 W/Kg in human phantom tissue. This establishes its suitability for on-body wireless applications, where minimizing SAR is a critical safety concern and can be deployed in mm-Wave infrastructure. The proposed compact bio-medical wearable antenna can also be utilized for receiving or transmitting signals in communication, IoT, and medical systems, thanks to its efficient and ultra-wideband characteristics.

The performance of metal workpieces is crucial in industry, and the evaluation of their surface defects is a key factor in ensuring the safety of industrial production. Eddy Current Testing (ECT) offers a non-contact, non-invasive method for detecting metal surface defects efficiently and accurately. However, the evaluation of metal surface defects often heavily relies on the experience of operators, which is not only inefficient but also susceptible to human factors. To effectively address the above issues, this paper proposes an evaluation method using Deep Learning (DL) technology and designs a CSE-LSTMNet model, which introduces the dilated convolutional layer on top of the traditional CNN-LSTM model, enabling faster training speeds and higher accuracy. Meanwhile, a Squeeze and Excitation Networks (SENet) module is added after each residual block to enable the model to automatically acquire the significance of each feature channel, thus enhancing useful channel features while suppressing unimportant ones. The CSE-LSTMNet model has been tested on the publicly available MDDEECT dataset. The simulation results show that the proposed CSE-LSTMNet model exhibits excellent performance in the metal surface defect classification task. Compared with the traditional CNN-LSTM benchmark model, the model achieves significant performance improvement, with the classification accuracy increasing from 86.67% to 92.78% and the F1 score increasing from 86.69% to 92.79%. This indicates that the CSE-LSTMNet model has higher performance and significant advantages in metal defect evaluation.

This article introduces a novel and compact architecture for generating a highly uniform static magnetic field optimized for nuclear magnetic resonance (NMR) spectroscopy. The design employs the strategic integration of high-performance N52 neodymium magnets within a precision-machined metallic housing to establish a closed magnetic flux circuit, enhancing field homogeneity. A key innovation is the incorporation of coiled iron caps featuring uniquely optimized geometries, facilitating adjustable magnetic flux density via an external DC voltage. It was specifically optimized to mitigate field distortions and maximize the uniformity of the magnetic field within the sample volume, enabling significantly improved spectral resolution compared to conventional designs. The resulting system achieves a static magnetic field of 0.928 T with a measured uniformity of 98% within the sample volume (10 mm gap). The complete assembly, including the magnets, casing, and coils, measures 12 × 13 × 8 cm and weighs 4.5 kg, achieving both high field strength and portability. Finite Element Method (FEM) simulations conducted using COMSOL Multiphysics demonstrate excellent correlation with empirical data, validating the design's robustness and enabling iterative performance optimization. This breakthrough addresses a critical gap in the development of portable NMR devices, offering unparalleled magnetic field uniformity and resolution, thereby expanding the potential for in-field spectroscopic analysis.