Journal of Computational Electronics最新文献

The semiconductor laser (SCL) is a promising light source in photodynamic therapy (PDT). Overcoming the limitation of the low-penetration depth of PDT and enhancing its therapeutic effect on cancer treatment at a deep level requires enhancing the laser power beyond 100 mW in the CW and/or pulse mode. In this paper, we presented a theoretical guide for designing and optimizing SCL parameters to achieve high CW power and high-power short-time pulses to promote laser performance in PDT. High-power CW output was achieved by optimizing the parameters that control the light–current (L–I) characteristics. Picosecond high-power pulses were predicted based on the simulation of the laser signal under sinusoidal current modulation using the optimized CW parameters along with an appropriate selection of the modulation frequency and index signal class. The characteristics of the laser signal under intensive simulations over wide ranges of modulation frequency and index were used to classify the dynamic types of the laser signal. The operating domain of each of these types was mapped over a (modulation frequency versus index), and bifurcation diagrams were constructed to illustrate the flow among these domains. We spotted the variation of both peak power and pulse width of the periodic pulses with modulation parameters. CW output with power reaching ~ 360 mW was predicted using facet reflectivities of 0.01 and 0.99, cavity length as short as 120 µm, internal loss as small as 100 m⁻¹, and confinement factor greater than 0.2. Periodic picosecond pulses with peak power reaching ~ 440 mW were predicted when the modulation index exceeds unity and the modulation frequency is higher than one-half of the relaxation oscillation. The pulse gets narrower with the increase in the modulation index and/or frequency. The obtained results would help design SCL with high power for efficient use in PDT.

Tunnel field-effect transistors (TFETs) have been explored extensively as a possible substitute for MOSFETs, especially for digital system design applications. Unlike conventional MOSFET devices, TFETs exhibit certain unique characteristics which are suitable for energy-efficient digital system design. In this paper, we report the use of a single device with both terminals biased independently for basic two-input Boolean logic operations AND, OR, NAND, and NOR using technology computer-aided design (TCAD) simulations. It is shown that these basic Boolean operations can be realized by minimally altering the design of a double-gate vertical TFET (DGVTFET) device and by selecting the appropriate device characteristics. The results show that when the Boolean functions are implemented, the I_ON/I_OFF ratio is in the range of 10⁹ to 10¹³ at a supply voltage V_DD = 1 V. Simulation results show that the use of a gate–source overlap technique and the selection of a suitable silicon body thickness are vital to obtaining distinct logic functions using a DGVTFET.

Theoretical and experimental investigations are critical for accurately investigating the structure and physical properties of semiconductors, allowing their widespread use in power electronic devices. The heat capacities are important thermal properties needed to examine the electronic and electrical properties of device materials. The specific heat capacities of power electronic semiconductors, such as (({text{GaN}})) gallium nitride, (({text{SiC}})) silicon carbide, (({text{Ga}}_{2} {text{O}}_{3})) gallium oxide, and diamond, have been evaluated theoretically using the recently developed Einstein–Debye approximation. On the grounds of the Einstein–Debye approach, the derived general analytical expression for the calculation of the heat capacities is valid for the entire temperature range. The calculation results are compared with the previously available experimental and theoretical data for illustrating the correctness of the method. The evaluation and literature analysis confirm the effectiveness of the proposed method. As seen from the comparison with various results reported in the literaure, the results obtained from this approach are convenient and competitive.

This paper presents a numerical framework for the analysis of quantum devices based on the Von Neumann (VN) equation, which involves the concept of the Tight-Binding Method (TBM). The model is based on the application of the Tight-Binding Hamiltonian within Quantum Liouville Type Equations and has the advantage that the atomic structure of the materials used is taken into account. Furthermore, the influence of a Complex Absorbing Potential (CAP) as a complementary boundary condition and its essential contribution to the system stability with respect to the eigenvalue spectrum is discussed.

In this work, a charge-based memristor emulator is designed using a single active current mode component Differential Voltage Current Conveyor Transconductance Amplifier with one capacitor and two resistors as passive components. Importantly, the proposed circuit topology can be changed to either grounded or floating configuration using a single switch. Moreover, the proposed memristor design can be operated either in incremental or decremental configuration by using another switch. Therefore, using only two switches, the same circuitry can be utilized to design the floating/grounded incremental/decremental memristor. The pinched hysteresis loop area can be controlled by applying different biasing voltages. Further, the mathematical analysis is performed to drive the theoretical TiO₂ based results for the proposed memristor emulator. In addition, simulations confirming the theoretical analysis are conducted in PSPICE using the 180 nm TSMC technology with a supply voltage of ± 0.9 V by varying frequencies and capacitances to obtain a pinched hysteresis loop. The presented circuit performs effectively for frequencies upto 500 MHz while operating with grounded type memristor and 300 MHz with floating type design. To check the ability to remember the history of the proposed memristor, the non-volatility test is performed for both the incremental and decremental configurations. Moreover, the suggested memristor design is applied in an adaptive learning circuit to prove its feasibility in neuromorphic applications.

In recent years, the requirement for greater scalability of transistor technology for the continuation of Moore’s law has led researchers toward the investigations of several innovative advanced semiconductor device as potentially superior alternatives to conventional transistors. Among them, single-electron transistors (SETs) have shown considerable promise in terms of performance and reliability with significant device dimension scaling. However, realistic modeling and simulation are the primary steps toward the practical implementation of SET designs. In this work, a technology computer-aided design simulation-based analytical study of silicon quantum dot SETs is developed to improve the electrical characteristics of the devices through optimization of different device parameters. Further, the investigation is extended to explore the temperature dependency of quantum tunneling by analysis of the characteristic plots of such quantum dot-based nano-devices. Moreover, a machine learning (ML)-based approach has been implemented and validated through development and testing of ML models predicting SET device performance by examining dependence of relevant design parameters on device performance. Hence, the proposed model of SETs provides the analytical understanding for a sustainable and realistic design of SETs allowing approaches to future nano-device-based IC design.

RF-MEMS switches can be categorized into two types based on their connection: metal-to-metal and capacitive. Metal-to-metal switches typically exhibit suboptimal performance compared to capacitive types, as they struggle to efficiently transmit high-frequency signals and power. Conversely, capacitive switches utilize a thin dielectric layer to prevent the beam from attaching to the transmission line in the off-state, facilitating easy release. This paper presents a novel design for a capacitive switch that effectively leverages RF MEMS technology, incorporating an innovative spring design. The proposed capacitive switch offers several advantages over its counterparts, including high isolation, low loss, low actuation voltage, and compact size and weight. Specifically tailored for Ka-band applications, the switch utilizes a spring mechanism to minimize the distance between the cantilever and the transmission line in CPW, thereby reducing the required activation voltage to just 1.5 V. A dielectric layer of SiO₂ with a thickness of 0.1 um is employed to enhance isolation and down-state capacitance. The proposed structural design not only enhances switch performance but also extends its lifespan by reducing stress levels, particularly in the spring component. The dynamic behavior and RF characteristics of the switch are analyzed using the COMSOL Multiphysics package and HFSS software, respectively, according to the findings, the switch demonstrates an S₁₁ value below − 8.75 dB and an S₂₁ value above − 1.06 dB across the frequency range of 1 to 40 GHz in the up-state configuration. In the down-state, the switch exhibits remarkable isolation in the Ka-band, with a resonance frequency of 19.53 GHz and an isolation value of − 43.3 dB.

We study the absorption coefficient of a diluted magnetic semiconductor ellipsoidal quantum dot with Rashba spin–orbit coupling. The Schrödinger equation for a one-electron ellipsoidal quantum dot was solved within the framework of the effective mass approximation method. The wave vector and electron energy found during the solution were used to find an expression for the absorption coefficient. The article examines intraband optical transitions relative to changes in external parameters. The decrease in the absorption coefficient as a function of the energy of the incident photon was studied at different values of the magnetic field, the Rashba parameter, temperature, concentration of Mn atoms and the radius of the ellipsoid. According to the results obtained, these parameters significantly affect intraband optical transitions.

This article proposes a parameter extraction method suitable for Si substrate based GaN HEMT small signal equivalent circuit models. The proposed method is based on a swarm intelligence optimization algorithm, which improves efficiency and accuracy by introducing a slope penalty factor (SPF) method for the objective function, rather than simply minimizing the error between simulation and measurement. By using PSO, WOA, and PNC-WOA for validation, we have demonstrated the advantages of the SPF method in extracting small signal parameters using swarm intelligence optimization algorithms. It is suitable for complex small-signal models that can describe the GaN HEMT-on-Si substrates, even if working up to 40 GHz.

This paper presents two equivalent electrical circuit models of a dye-sensitized solar (DSS) module (150B-3 390). The module, which uses a third-generation solar cell, has several advantages over the earlier two generations. The equivalent model increases the research opportunities on solar cell technology development even without an existing solar plant. The paper highlights the development of an equivalent model of the module with the proposed method, as no such model is currently available to carry out further research with the module. The single-diode model (SDM) is a widely utilized simple approach that describes solar cell behavior very well. Model I in the paper is developed using only the SDM approach. It consists of a few unknown parameters estimated with the Gauss–Seidel method. The results from Model I show that the model requires certain improvements, due to the fundamental differences in the characteristic curves between conventional solar cells and DSS cells. The proposed model can more precisely describe the behavior of the module. Gauss–Seidel, curve fitting, and theoretical methods were used to develop the proposed model. It describes the irradiance effect of the module by introducing two newly developed parameters to Model I. The proposed model, with the theoretically modified characteristic equation of Model I, illustrates the temperature effect. The experimental work for the modeling is carried out on the DSS module inside a laboratory environment with standard test conditions. A Raspberry Pi 4 B with sensing devices is used to extract the measurable parameters from the module. Both models are based on an SDM design approach. Characteristic curves of the module from measured data validate the output characteristics of both models at various irradiance and temperature values. The results confirm the superiority of the proposed model over Model I.