Enhanced Thermal Boundary Conductance across GaN/SiC Interfaces with AlN Transition Layers

材料科学 光电子学 图层(电子) 声子 宽禁带半导体 分子动力学 热导率 凝聚态物理 纳米技术 复合材料 物理 计算化学 化学
作者
Ruiyang Li,Kamal Hussain,Michael E. Liao,Kenny Huynh,Md Shafkat Bin Hoque,Spencer Wyant,Yee Rui Koh,Zhihao Xu,Yekan Wang,Dorian Luccioni,Zhe Cheng,Jingjing Shi,Eungkyu Lee,Samuel Graham,Asegun Henry,Patrick E. Hopkins,Mark S. Goorsky,Muhammad Asif Khan,Tengfei Luo
出处
期刊:ACS Applied Materials & Interfaces [American Chemical Society]
卷期号:16 (6): 8109-8118 被引量:31
标识
DOI:10.1021/acsami.3c16905
摘要

Heat dissipation plays a crucial role in the performance and reliability of high-power GaN-based electronics. While AlN transition layers are commonly employed in the heteroepitaxial growth of GaN-on-SiC substrates, concerns have been raised about their impact on thermal transport across GaN/SiC interfaces. In this study, we present experimental measurements of the thermal boundary conductance (TBC) across GaN/SiC interfaces with varying thicknesses of the AlN transition layer (ranging from 0 to 73 nm) at different temperatures. Our findings reveal that the addition of an AlN transition layer leads to a notable increase in the TBC of the GaN/SiC interface, particularly at elevated temperatures. Structural characterization techniques are employed to understand the influence of the AlN transition layer on the crystalline quality of the GaN layer and its potential effects on interfacial thermal transport. To gain further insights into the trend of TBC, we conduct molecular dynamics simulations using high-fidelity deep learning-based interatomic potentials, which reproduce the experimentally observed enhancement in TBC even for atomically perfect interfaces. These results suggest that the enhanced TBC facilitated by the AlN intermediate layer could result from a combination of improved crystalline quality at the interface and the "phonon bridge" effect provided by AlN that enhances the overlap between the vibrational spectra of GaN and SiC.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
东方千筹完成签到,获得积分20
3秒前
4秒前
5秒前
Zhenggg发布了新的文献求助30
5秒前
5秒前
喜懒100发布了新的文献求助10
5秒前
bkagyin应助zzzzzz采纳,获得10
5秒前
9秒前
卜卜发布了新的文献求助50
11秒前
我是老大应助懒惰馨采纳,获得20
13秒前
16秒前
17秒前
丘比特应助蓝天采纳,获得10
18秒前
阿讓发布了新的文献求助10
19秒前
frankyeah完成签到,获得积分10
20秒前
21秒前
不厌完成签到 ,获得积分10
21秒前
清风完成签到 ,获得积分10
21秒前
橘子完成签到,获得积分10
21秒前
hr完成签到 ,获得积分10
22秒前
隐形曼青应助zc采纳,获得10
22秒前
漂亮123完成签到,获得积分10
22秒前
rodion完成签到 ,获得积分10
24秒前
frankyeah发布了新的文献求助50
24秒前
24秒前
lqcolleen完成签到,获得积分10
25秒前
小江不饿完成签到,获得积分10
25秒前
25秒前
上官若男应助kitty采纳,获得10
26秒前
26秒前
26秒前
方舟应助Sisyphus采纳,获得10
27秒前
10086发布了新的文献求助10
29秒前
百宝发布了新的文献求助10
30秒前
30秒前
星辰大海应助阿讓采纳,获得10
31秒前
Jane发布了新的文献求助50
33秒前
清新的慕凝完成签到,获得积分10
34秒前
35秒前
晚随月完成签到 ,获得积分10
35秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Photodetectors: From Ultraviolet to Infrared 500
Cancer Targets: Novel Therapies and Emerging Research Directions (Part 1) 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6359503
求助须知:如何正确求助?哪些是违规求助? 8173510
关于积分的说明 17214610
捐赠科研通 5414555
什么是DOI,文献DOI怎么找? 2865497
邀请新用户注册赠送积分活动 1842839
关于科研通互助平台的介绍 1691052