Deep learning-based asm-hemt iv parameter extraction
A fast and accurate deep learning (DL) based ASM-HEMT IV model parameter extraction is
presented for the first time. DL-based extraction starts with 120k training data-sets …
presented for the first time. DL-based extraction starts with 120k training data-sets …
Device performance prediction of nanoscale junctionless FinFET using MISO artificial neural network
This paper investigates the way to use Multi-layer neural network as a possible replacement
of numerical TCAD device simulation to study device characteristics using limited …
of numerical TCAD device simulation to study device characteristics using limited …
Neural network estimations of annealed and non-annealed Schottky diode characteristics at wide temperatures range
Abstract In this study, Artificial Neural Network (ANN) model has been proposed to
characterize the annealed and the non-annealed Schottky diode from experimental data …
characterize the annealed and the non-annealed Schottky diode from experimental data …
Artificial neural network models for metal-ferroelectric-insulator-semiconductor ferroelectric tunnel junction memristor
Abstract Metal-Ferroelectric-Insulator-Semiconductor (MFIS) structure ferroelectric tunnel
junction (FTJ) memristor becomes one of the most promising candidates for next-generation …
junction (FTJ) memristor becomes one of the most promising candidates for next-generation …
Algorithmic optimization of transistors applied to silicon LDMOS
We propose a pioneering approach that integrates optimization algorithms and technology
computer-aided design to automatically optimize laterally-diffused metal-oxide …
computer-aided design to automatically optimize laterally-diffused metal-oxide …
Using U-Net convolutional neural network to model pixel-based electrostatic potential distributions in GaN power MIS-HEMTs
BR Chen, YS Hsiao, WC Lin, WJ Lee, NY Chen… - Scientific Reports, 2024 - nature.com
This study demonstrates a novel use of the U-Net convolutional neural network (CNN) for
modeling pixel-based electrostatic potential distributions in GaN metal–insulator …
modeling pixel-based electrostatic potential distributions in GaN metal–insulator …
Optimization of dual field plate AlGaN/GaN HEMTs using artificial neural networks and particle swarm optimization algorithm
S Liu, X Duan, S Wang, J Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
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 …
AlGaN/GaN high electron mobility transistor (HEMT). Currently, field plate optimization relies …
Accurate Modeling for GaN HEMTs and MMICs for C ryogenic Electronics Applications Utilizing Artificial Neural Network
Z Xiang, H Zhang, B Zeng, M Zhang… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
The prosperity of quantum computing has boosted the development of cryogenic electronics.
The wide bandgap GaN-based devices show the potential to develop such cryogenic …
The wide bandgap GaN-based devices show the potential to develop such cryogenic …
Deep-learning Model for Buildup of Ionization Defects in Bipolar Junction Transistors
L Li, XC Chen, GX Yang - IEEE Transactions on Nuclear …, 2023 - ieeexplore.ieee.org
The ionization defects in bipolar junction transistors (BJTs) are sensitive to ionization dose
rate and molecular hydrogen in oxides. The bimolecular reaction model, a physical model …
rate and molecular hydrogen in oxides. The bimolecular reaction model, a physical model …
Efficient Automatic Design of IGBT Structural Parameters Using Differential Evolution and Machine Learning Model
Q Yao, J Chen, K Yang, J Yao, J Zhang… - … on Computer-Aided …, 2024 - ieeexplore.ieee.org
Insulated gate bipolar transistors (IGBTs) are the key component in power electronics, and
the intricate relationship between their performance and structural parameters poses a …
the intricate relationship between their performance and structural parameters poses a …