Thermal resistance optimization of GaN-on-Si materials for RF HEMTs based on structure function method and static-pulsed I–V measurements

A major obstacle in the commercialization of GaN-on-Si RF HEMTs lies in the elevated thermal resistance introduced by the AlN/AlGaN multi-layer buffer, employed for stress management. This issue adversely impacts device performance and reliability. In this study, the structure function method was utilized to precisely determine the intrinsic thermal resistance of GaN-on-Si materials. Results reveal that a single-layer AlN buffer demonstrates a significantly enhanced heat dissipation capability compared to conventional AlN/AlGaN multi-layer or superlattice buffer. Additionally, the thermal performance of device under operation was quantitatively assessed using static-pulsed I–V measurements. Through theoretical simulations, the influence of GaN buffer structures on heat distribution within GaN-on-Si RF devices was explored, indicating that optimizing GaN buffer thickness can further enhance thermal performance. This research offers a thorough understanding of the relationship between material structures and RF device thermal behavior, providing crucial insights for the thermal management design of GaN-on-Si RF HEMTs.

Authors

Institutions

Publication Details

Journal
Applied Physics Letters
Published
2025-04-01
DOI
https://doi.org/10.1063/5.0263898
Citations
1
Primary Topic
GaN-based semiconductor devices and materials
Type
article
Field-Weighted Citation Impact
1.26

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Thermal resistance optimization of GaN-on-Si materials for RF HEMTs based on structure function method and static-pulsed I–V measurements

Meixin Feng, Shiwei Feng, Xiaoning Zhan, Xin Chen et al.
1 citations
Applied Physics Letters
GaN-based semiconductor devices and materials
1.26
article

Thermal resistance optimization of GaN-on-Si materials for RF HEMTs based on structure function method and static-pulsed I–V measurements

Meixin Feng, Shiwei Feng, Xiaoning Zhan, Xin Chen, Yu Zhou, Qingru Wang, X.Y. Zhang, Qian Sun, Xiaozhuang Lu, Quan Dai, Zhihong Feng, Qian Li, Yamin Zhang, Jianxun Liu, Hui Yang
article en
1 citations

Abstract

A major obstacle in the commercialization of GaN-on-Si RF HEMTs lies in the elevated thermal resistance introduced by the AlN/AlGaN multi-layer buffer, employed for stress management. This issue adversely impacts device performance and reliability. In this study, the structure function method was utilized to precisely determine the intrinsic thermal resistance of GaN-on-Si materials. Results reveal that a single-layer AlN buffer demonstrates a significantly enhanced heat dissipation capability compared to conventional AlN/AlGaN multi-layer or superlattice buffer. Additionally, the thermal performance of device under operation was quantitatively assessed using static-pulsed I–V measurements. Through theoretical simulations, the influence of GaN buffer structures on heat distribution within GaN-on-Si RF devices was explored, indicating that optimizing GaN buffer thickness can further enhance thermal performance. This research offers a thorough understanding of the relationship between material structures and RF device thermal behavior, providing crucial insights for the thermal management design of GaN-on-Si RF HEMTs.

Applied Physics LettersVol. 126(14)
University of Science and Technology of China (CN), Chinese Academy of Sciences (CN), Beijing University of Technology (CN), Suzhou Institute of Nano-tech and Nano-bionics (CN), Hebei Semiconductor Research Institute (CN)
National Natural Science Foundation of China, Youth Innovation Promotion Association of the Chinese Academy of Sciences, Jiangsu Provincial Key Research and Development Program, Basic Research Program of Jiangsu Province, National Key Research and Development Program of China, Science and Technology Program of Suzhou, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 23%
GaN-based semiconductor devices and materials
1.26
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.