Optimization of Dual Field Plate AlGaN/GaN HEMTs Using Artificial Neural Networks and Particle Swarm Optimization Algorithm

Shijie Liu, Xiaoling Duan, Shulong Wang, Jincheng Zhang, Yue Hao

2023IEEE Transactions on Device and Materials Reliability12 citationsDOI

Abstract

Field plate technology is an effective method for improving the breakdown performance of AlGaN/GaN high electron mobility transistor (HEMT). Currently, field plate optimization relies on TCAD simulation, which is time-consuming and difficult to converge. In this study, we propose a fast and efficient method to optimize the gate-source dual field plate (dual-FP) to improve the breakdown performance of the HEMT. Specifically, an artificial neural network (ANN) model was used to fit the relationship between the dual-FP structure parameters and the breakdown voltage (BV), so that the breakdown performance could be predicted quickly and the average prediction error was only 3.06%. Furthermore, the trained ANN model was applied to the particle swarm optimization (PSO) algorithm and a dual-FP HEMT with a breakdown voltage of 1228 V was obtained by optimization. The proposed method shows significant advantages in terms of optimization efficiency and can realize automatic optimization. It also provides a reference for the optimization of other field plate structures of microelectronic devices.

Topics & Concepts

Particle swarm optimizationHigh-electron-mobility transistorArtificial neural networkBreakdown voltageMicroelectronicsVoltageElectronic engineeringField (mathematics)Computer scienceDual (grammatical number)TransistorAlgorithmMaterials scienceEngineeringElectrical engineeringOptoelectronicsArtificial intelligenceMathematicsArtPure mathematicsLiteratureGaN-based semiconductor devices and materialsSilicon Carbide Semiconductor TechnologiesSemiconductor materials and devices