Particle Swarm Optimization Based Design Optimization for Enhanced Breakdown Voltage in GaN High Electron Mobility Transistors
Description
The dataset used for Particle Swarm Optimization (PSO)-based design optimization of GaN High Electron Mobility Transistors (HEMTs) consists of simulated device parameters and corresponding electrical performance metrics. The data is generated through Technology Computer-Aided Design (TCAD) simulations or extracted from experimentally validated models of GaN HEMTs. Input Parameters (Design Variables) These represent the structural and material properties of the device that are optimized using PSO: Gate length (Lg) Gate-to-drain distance (Lgd) Barrier layer thickness AlGaN composition (Al mole fraction) Doping concentration Passivation layer thickness Field plate dimensions (if applicable) These parameters directly influence the electric field distribution and breakdown characteristics of the device. Output Parameters (Performance Metrics) These are the target values evaluated for optimization: Breakdown voltage (Vbr) (primary objective) Drain current (Id) Threshold voltage (Vth) Electric field peak distribution Leakage current Nature of Data The dataset is numerical and continuous Each row corresponds to a unique device configuration Data is typically nonlinear and high-dimensional, making it suitable for optimization using metaheuristic algorithms like PSO Role in PSO Optimization The dataset acts as the fitness evaluation base PSO iteratively adjusts input parameters to maximize breakdown voltage while maintaining acceptable electrical performance Fitness function is defined primarily based on maximizing Vbr with constraints on other parameters