Autonomous Numerical Methods for Solving Electrical Circuits, A Taylor Series-Based Approach
Advancements in Oxide-Based Resistive Random-Access Memory (RRAM): A Modern Perspective on Resistive Switching Mechanisms and Conduction Models
Enhanced Circuit Topologies for Maximizing Power Output in Piezoelectric Energy Harvesters
Analyzing Performance Free Biosensor Utilizing a Split-Gate T-Shape and Modeling of a Label-Channel Design with DM DPDG-TFET Technology
Simulation of Matrix Converter Control by Fuzzy Logic Control for Induction Heating System
Loss Distribution Methodology with a Sense Of Emission Dispatch
Low Power Optimization Technique Based Linear Feedback Shift Register
Leakage Power Reduction Using Multi Modal Driven Hierarchical Power Mode Switches
Validation of IOV chain using OVM Technique
Performance of Continuous and Discontinuous Space Vector Pwm Technique for Open End Winding Induction Motor Drive
Electronic Circuit Design for Electromagnetic Compliance through Problem-Based Learning
Trioinformatics: The Innovative and Novel Logic Notation That Defines, Explains, and Expresses the Rational Application of The Law of Trichotomy for Digital Instrumentation and Circuit Design
Design Of a Novel Gated 5T SRAM Cell with Low Power Dissipation in Active and Sleep Mode
A Two Stage Power Optimized Implantable Neural Amplifier Based on Cascoded Structures
An Efficient Hybrid PFSCL based Implementation of Asynchronous Pipeline
Electrical circuit analysis is a fundamental aspect of engineering, requiring accurate and efficient computational methods for solving differential equations governing circuit behaviour. Traditional numerical methods, such as Euler's and Runge-Kutta approaches, have limitations in accuracy and computational efficiency. This paper explores an autonomous numerical approach using the Taylor Series Method, implemented in the TKSL simulation system. The study compares the Taylor Series Method with conventional numerical techniques, evaluating accuracy, computational complexity, and stability. The results indicate that the Taylor expansion method enhances precision while reducing computational overhead. This work contributes to the development of efficient circuit simulation tools, with potential applications in power systems, embedded electronics, and real-time circuit analysis. Future studies will focus on extending this approach to nonlinear circuit systems and optimizing computational performance.
Resistive Random-Access Memory (RRAM) is a promising non-volatile memory technology due to its high-speed operation, low power consumption, and scalability. Since the early study on oxide-based RRAM, significant advancements have been made in understanding resistive switching mechanisms, improving material compositions, and integrating RRAM for neuromorphic computing applications. This paper revisits the resistive switching and conduction mechanisms in oxide-based RRAM and updates previous study findings with modern developments in interface engineering, multi-layer stacking, and novel material innovations such as graphene oxide and high-k dielectrics. Key advancements in conduction models, including filamentary conduction, Poole-Frenkel emission, and trap-assisted tunneling, are discussed, supported by recent experimental and theoretical findings. Furthermore, existing experimental data are reanalyzed using modern insights, and potential applications of RRAM in artificial intelligence accelerators and edge computing are proposed. The results highlight the improved endurance, retention, and switching dynamics of oxide-based RRAM, making it a viable candidate for next-generation memory solutions.
Piezoelectric energy harvesting has gained significant attention for powering small-scale electronic devices by converting mechanical vibrations into electrical energy. However, the electrical interface plays a crucial role in maximizing power transfer efficiency. This paper explores optimized circuit topologies, particularly the use of inductors to mitigate capacitive impedance effects and enhance power output. A comparative analysis of Simple Resistive Load (SRL), Inductive Load (IL), and AC-DC converter circuits is conducted, both numerically and experimentally. Results indicate that inductive circuits significantly improve power output by reducing the negative reactance of piezoelectric harvesters. The findings contribute to the development of more efficient self-powered systems for wireless sensors and low-energy electronics.
This paper introduces a novel split gate T-shape channel dielectrically modulated (DM) double-gate tunnel field-effect transistor (DGTFET) with a drain pocket (DP), proposing its application as a label-free biosensor. Through the development and validation of an analytical model using Silvaco TCAD simulation software, the focus is on both the biosensor's sensitivity and its performance as a TFET device. By innovatively shaping the channel, the device demonstrates improved sensitivity, a higher ION/IOFF current ratio, and a reduced sub threshold slope. Notably, the inclusion of the drain pocket at the drain–channel junction effectively eliminates ambipolarity, enhancing ON current performance. Through optimization of the drain pocket length and doping concentration, the device achieves high ON current without ambipolarity. The proposed T-shape DM DPDGTFET surpasses several existing devices in both biosensor and FET device performance. Evaluation of device sensitivity as a label-free biosensor considers the presence or absence of charge in various biomolecules.
This paper proposes the modeling and simulation of a single-phase matrix converter as a converter for domestic AC induction heating applications. In this paper, a single-phase matrix converter employing IGBT-based bi-directional switches is used for this purpose. The technique employed to generate the pulses for the matrix converter is Fuzzy Logic, which is illustrated in detail. The performance and content analysis of the single-phase matrix converter have been carried out in MATLAB/SIMULINK, and the results have been successfully verified. Additionally, the working principle and control strategy of the Fuzzy Logic-based matrix converter are explained in detail.
