Journal of Computational Electronics最新文献

Accurately predicting the resonant frequencies of microstrip antennas is crucial for efficient antenna design and optimisation, yet traditional analytical and numerical methods often face challenges in handling complex parameter interactions. This paper presents a novel approach to predict the resonant frequencies of microstrip antennas using convolutional neural networks (CNNs) and image-based encoding of antenna parameters. The proposed method encodes the key design parameters—length (L), width (W), height (h), and relative permittivity (ε_r)—into 2 × 2 and 4 × 4 RGB images, where each parameter is mapped to specific colour channels or derived spatial features. These encoded images are utilized as inputs to a CNN architecture tailored for regression tasks, predicting the resonant frequency as a continuous output. The model demonstrates superior prediction accuracy for training and testing on a comprehensive dataset of microstrip antenna designs, achieving a low average percentage error (APE). The CNN effectively captures the complex relationships between antenna parameters and their corresponding resonant frequencies by leveraging spatial and feature-derived patterns in the RGB-encoded images. This approach offers a novel perspective on antenna design optimisation, enabling a highly accurate, automated, and scalable solution to predict antenna performance. The results underscore the potential of image-based encoding in enhancing the rapid design and optimisation of microstrip antennas.

The modeling of ion-sensitive field-effect transistors (ISFETs) for pH biosensing applications using a commercial Technology Computer-Aided Design (TCAD) tool has been investigated in this study. A comparative analysis was conducted to evaluate the effect of various high-k inorganic gate materials—SiO₂, Al₂O₃, Si₃N₄, ZrO₂, and Ta₂O₅—as pH-sensitive films on device performance. These materials were selected for their potential to enhance ISFET sensitivity and stability, in contrast to the conventional silicon dioxide (SiO₂) gate layer. To avoid the high cost of physical fabrication, TCAD simulation was employed as an effective and economical alternative for device development and performance evaluation. Simulation results were validated against published experimental data, confirming that ISFETs incorporating high-k materials exhibit superior sensitivity and stability compared to those using SiO₂. A key innovation in this work is the reintroduction and analysis of the site-binding electrolyte model, which is currently not available in standard TCAD platforms but is critical for accurately modeling biosensor behavior in electrolyte environments. The simulation demonstrated that Al₂O₃ and Ta₂O₅ exhibited the highest sensitivity at 59.2 mV/pH, followed closely by ZrO₂ at 59.0 mV/pH, significantly outperforming the conventional SiO₂ layer (44.6 mV/pH) across a wide pH range (approximately 1–13).

Non-fullerene organic chromophores are widely used in photovoltaic materials. In this study, the perylene-based molecules (PBI1-PBI8) with an A–π–A framework were designed by modifying the terminal acceptor of the reference compound (PBIR). Density functional theory (DFT) and time-dependent DFT (TD-DFT) calculations at the M06/6-311G(d,p) level were employed to optimize and verify their true minima structures. Further, the optimized structures were used for investigating the frontier molecular orbitals (FMOs), transition density matrix (TDM), density of states (DOS), open-circuit voltage (V_oc), and binding energy (E_b) to understand their optoelectronic and photovoltaic performances. The HOMO–LUMO energy gap of PBI1-PBI8 was obtained in a range of 2.546–2.610 eV, comparable to the PBIR reference (2.553 eV). Additionally, they showed wide absorption spectra as 571.540–599.972 nm in the gas phase and 598.871–615.031 nm in the chloroform solvent phase. The designed derivatives also exhibited lower binding energies (0.436–0.482 eV). All the new chromophores (PBI1-PBI8) showed a reasonable improvement in photovoltaic response as shown by their prominent open-circuit voltages. These results suggest that the novel perylene-based chromophores may be suitable candidates for highly efficient photovoltaic materials.

This paper presents the dimensional analysis of a micromachined vibrating beam accelerometer (VBA) for early earthquake warning system. Two beam resonators with natural frequencies of 124 kHz are determined. The primary benefit of this type of device over a capacitive accelerometer is its thickness independent sensitivity. This device serves for low-g acceleration detection with minimal noise and high sensitivity. The beams are suspended between two anchors, which support all mechanical and structural operations. The anchor dimensions have a significant impact on VBA’s natural frequency. The movement of proof mass creates an axial load on the beam when there is an external acceleration. The external acceleration application results in a shift in the frequency of vibration of beam. To see the parametric analysis, several single-beam dimensions are modeled. Proposed electromechanical and analytical mechanics of vibrating beam are used to validate the finite element method (FEM) simulation results.

With the continued scaling of integrated circuit (IC) technology nodes, optimizing interconnect performance has become critical for improving overall system performance. To overcome the limitations of single high-k dielectric insertions, we introduce a dual-dielectric approach using two distinct high-k materials within multilayer graphene nanoribbon (MLGNR) interconnects. This strategy improves carrier mobility and suppresses interfacial scattering, thereby enhancing interconnect signal transmission. The paper develops a comprehensive model that incorporates equivalent resistance, capacitance, and inductance. Based on the model, this paper applies the ABCD parameter matrix method to derive the interconnect transfer function and clarify how the dual-dielectric configuration enhances signal propagation, expands bandwidth, and reduces delay. Theoretical derivations are used to evaluate the proposed structure’s impact on key performance indicators, including mean free path (MFP), scattering resistance, delay, gain, 3 dB bandwidth, and energy-delay product (EDP). The results demonstrate that, compared to single-dielectric designs, the dual-dielectric strategy generally improves performance by reducing settling time and expanding the 3 dB bandwidth, leading to significant overall enhancements in signal transmission and efficiency. This paper provides theoretical support and data evidence for multi-dielectric design strategies in nanoscale MLGNR interconnect structures.

A memristor is a passive electrical component that connects an electric charge and the magnetic flux linkage. Due to its unique features, much research has been done on the prospects of its use in the field, including neuromorphic computing systems and memory technologies, among others. In this article, we discussed the memristive model and its modelling equations and explored the current–voltage relationships. Subsequently, we elucidated the necessity of a window function and the challenges associated with previously reported window functions. Finally, we have proposed a novel window function in this article, highlighting its advantages over numerous existing ones. The proposed window function effectively resolves the boundary lock issue, boundary effect issue, limited flexibility issue and distorted pinched hysteresis issue. Using this window function, the synaptic learning capabilities of a memristive system have also been demonstrated. The flexibility offered by this window function with just two control parameters is considerable.

Lateral superjunctions (LSJ) are potential candidates for CMOS compatible high voltage devices in next-generation power integrated circuits. The prior works have modeled and developed design guidelines only for an ideal balanced LSJ, i.e., having equal charge in the n- and p-pillars. However, inevitable process variation during fabrication results in charge imbalance, ({k_{N}}), that yields a breakdown voltage, ({V_textrm{BR}}), significantly lower than the target breakdown voltage, ({V_textrm{BR,target}}). In this work, we use the method of Lagrange multipliers to derive analytical equations for the optimum pillar parameters of an LSJ; these parameters yield the minimum specific ON-resistance, ({R_textrm{ONSP}}), for a ({V_textrm{BR,target}}) and ({k_{N}}). The analytical solutions are verified using well-calibrated TCAD simulations for 0.1–1 kV Si LSJs and 1–10 kV 4H-SiC LSJs for ({k_{N}}) from 0.05 to 0.30 (signifying 5 to 30% imbalance between the n- and p-pillar charge). Our solutions show that the optimum aspect ratio, ({r_{0}}), varies between 8–12 for Si LSJs and 10–15 for 4H-SiC LSJs. Notably, our solution for an LSJ is found to yield significantly different optimum pillar parameters than our earlier solution for a vertical SJ for the same ({V_textrm{BR}}) and ({k_{N}}), due to the difference in their dependency of ({R_textrm{ONSP}}) on the pillar parameters. This justifies the need for customized solution for the design of LSJ.

In this paper, we study the dynamic of a position-dependent mass system confined in harmonic oscillator potential. We derive the eigensystems by solving the Schrödinger-like equation which describes this system. We construct coherent states à la Gazeau-Klauder for this system. We show that these states satisfy the Klauder’s mathematical condition to build coherent states. We compute and analyze some statistical properties of these states. We find that these states exhibit sub-Poissonian statistics. We also evaluate quasiprobability distributions such as the Wigner function to demonstrate graphically nonclassical features of these states.

As digital technology advances, the demand for high-performance, high-density, and low-power memory technologies continues to grow. To address these needs, the 2 Transistor 0 Capacitor (2T0C) DRAM architecture, featuring nondestructive read operations, has emerged as a promising alternative to conventional 1 Transistor 1 Capacitor DRAM. The InGaZnO (IGZO) channel material, known for low off-current and high mobility, enables long data retention and enhanced power efficiency in 2T0C DRAM. In this study, IGZO-based channel-all-around (CAA) and gate-all-around (GAA) FET structures were implemented using TCAD simulations, which were based on the well-calibrated physical carrier transport models with the measured IGZO channel device. The electrical characteristics, including the on/off-current ratio (I_on/I_off), were compared at the single-transistor level. For the 2T0C DRAM cell, variations in the gate length, critical dimension (CD), and underlap structure of the writing transistor (WTR) and reading transistor (RTR) were investigated, to evaluate memory characteristics such as data writing speed, retention, and single-cell disturbance, along with the feasibility of multi-bit operation. The analysis showed that the CAA structure provides faster data writing speeds, whereas the GAA structure—especially in the WTR configuration and 3 × 3 array design—offers significantly better retention and single-cell disturbance immunity. This study provides clear guidance for the structural optimization of IGZO-based 2T0C DRAM and practical insights into the designing next-generation high-density memory technologies.

The breakdown of GaN-based Schottky barrier diodes associated with impact ionization events initiated by electrons injected by tunneling is physically analyzed by means of a Monte Carlo simulator self-consistently coupled with a two-dimensional solution of the Poisson equation. Simulations of a realistic topology where different geometrical parameters are modified allow to identify their influence on the breakdown voltage. The correct physical modeling of two-dimensional effects is essential for a proper prediction of the breakdown. Epilayer doping and thickness, dielectric used for the passivation and lateral extension of the epilayer are analyzed. As expected, the lower the doping and the thicker the epilayer, the higher the value found for the breakdown voltage, but, interestingly, the results also indicate that the peak electric field present at the edge of the Schottky contact, which may be reduced by means of high-k dielectric passivation and a short lateral extension of the epilayer, plays a key role in the breakdown.