Optimization of NoN-melt-back-etching and selectivity for selective area growth of GaN drain on Si (100) substrate

This work explores the dual-step epitaxial GaN (DSE-GaN) process for the selective area growth of GaN drains on Si (100) substrates, addressing critical challenges in melt-back etching and regrowth selectivity. The DSE-GaN process combines the superior material properties of GaN with the inherent ad...

Full description

Saved in:
Bibliographic Details
Main Authors: Cheng-Jun Huang, Shuo Hwai, Tsai-Fu Chung, Chien-Nan Hsiao, Bo-Cheng Lin, Hung-Ching Tsai, Chi Huang Lui, Edward. Yi Chang, Mau-Chung Frank Chang
Format: Article
Language:English
Published: AIP Publishing LLC 2025-05-01
Series:AIP Advances
Online Access:http://dx.doi.org/10.1063/5.0256900
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850249540458774528
author Cheng-Jun Huang
Shuo Hwai
Tsai-Fu Chung
Chien-Nan Hsiao
Bo-Cheng Lin
Hung-Ching Tsai
Chi Huang Lui
Edward. Yi Chang
Mau-Chung Frank Chang
author_facet Cheng-Jun Huang
Shuo Hwai
Tsai-Fu Chung
Chien-Nan Hsiao
Bo-Cheng Lin
Hung-Ching Tsai
Chi Huang Lui
Edward. Yi Chang
Mau-Chung Frank Chang
author_sort Cheng-Jun Huang
collection DOAJ
description This work explores the dual-step epitaxial GaN (DSE-GaN) process for the selective area growth of GaN drains on Si (100) substrates, addressing critical challenges in melt-back etching and regrowth selectivity. The DSE-GaN process combines the superior material properties of GaN with the inherent advantages of the Si (100) substrate by utilizing GaN as the drain in the Si n-MOSFET. On the Si (100) substrate, the wide-bandgap GaN drain can be designed to enhance the device’s breakdown voltage or enable the integration of GaN-based light-emitting diodes or laser diodes. In this work, based on the Hertz–Knudsen model and our experiment, we determined a process window that eliminates melt-back etching and achieves full selectivity growth. Experimental results reveal that optimizing the growth temperature and trimethylgallium flow rate effectively suppresses the formation of Ga droplet and the non-selective growth of GaN grains. Finally, we successfully demonstrated the significant potential of Si n-MOSFETs with GaN drains. The fabricated devices, featuring a GaN drain-first architecture and demonstrating ID–VG characteristics, highlight the seamless integration of GaN’s wide-bandgap properties with silicon’s CMOS technology. This approach shows significant potential for radar, radio frequency, and optoelectronic applications by combining GaN’s high breakdown electric field and direct bandgap with the scalability of Si. Our findings establish a robust pathway for heterogeneous integration, advancing the development of high-power and high-frequency systems-on-chip technologies.
format Article
id doaj-art-5ed6db76a611487ba08d43c33f5666fc
institution OA Journals
issn 2158-3226
language English
publishDate 2025-05-01
publisher AIP Publishing LLC
record_format Article
series AIP Advances
spelling doaj-art-5ed6db76a611487ba08d43c33f5666fc2025-08-20T01:58:28ZengAIP Publishing LLCAIP Advances2158-32262025-05-01155055119055119-610.1063/5.0256900Optimization of NoN-melt-back-etching and selectivity for selective area growth of GaN drain on Si (100) substrateCheng-Jun Huang0Shuo Hwai1Tsai-Fu Chung2Chien-Nan Hsiao3Bo-Cheng Lin4Hung-Ching Tsai5Chi Huang Lui6Edward. Yi Chang7Mau-Chung Frank Chang8International College of Semiconductor Technology, National Yang Ming Chiao Tung University, Hsinchu 30010, TaiwanDepartment of Electrical and Computer Engineering, University of California, Los Angeles (UCLA), Los Angeles, California 90095, USADepartment of Materials Science and Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, TaiwanTaiwan Instrument Research Institute, National Applied Research Laboratories, Hsinchu 30010, TaiwanDepartment of Materials Science and Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, TaiwanDepartment of Materials Science and Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, TaiwanDepartment of Materials Science and Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, TaiwanInternational College of Semiconductor Technology, National Yang Ming Chiao Tung University, Hsinchu 30010, TaiwanDepartment of Electrical and Computer Engineering, University of California, Los Angeles (UCLA), Los Angeles, California 90095, USAThis work explores the dual-step epitaxial GaN (DSE-GaN) process for the selective area growth of GaN drains on Si (100) substrates, addressing critical challenges in melt-back etching and regrowth selectivity. The DSE-GaN process combines the superior material properties of GaN with the inherent advantages of the Si (100) substrate by utilizing GaN as the drain in the Si n-MOSFET. On the Si (100) substrate, the wide-bandgap GaN drain can be designed to enhance the device’s breakdown voltage or enable the integration of GaN-based light-emitting diodes or laser diodes. In this work, based on the Hertz–Knudsen model and our experiment, we determined a process window that eliminates melt-back etching and achieves full selectivity growth. Experimental results reveal that optimizing the growth temperature and trimethylgallium flow rate effectively suppresses the formation of Ga droplet and the non-selective growth of GaN grains. Finally, we successfully demonstrated the significant potential of Si n-MOSFETs with GaN drains. The fabricated devices, featuring a GaN drain-first architecture and demonstrating ID–VG characteristics, highlight the seamless integration of GaN’s wide-bandgap properties with silicon’s CMOS technology. This approach shows significant potential for radar, radio frequency, and optoelectronic applications by combining GaN’s high breakdown electric field and direct bandgap with the scalability of Si. Our findings establish a robust pathway for heterogeneous integration, advancing the development of high-power and high-frequency systems-on-chip technologies.http://dx.doi.org/10.1063/5.0256900
spellingShingle Cheng-Jun Huang
Shuo Hwai
Tsai-Fu Chung
Chien-Nan Hsiao
Bo-Cheng Lin
Hung-Ching Tsai
Chi Huang Lui
Edward. Yi Chang
Mau-Chung Frank Chang
Optimization of NoN-melt-back-etching and selectivity for selective area growth of GaN drain on Si (100) substrate
AIP Advances
title Optimization of NoN-melt-back-etching and selectivity for selective area growth of GaN drain on Si (100) substrate
title_full Optimization of NoN-melt-back-etching and selectivity for selective area growth of GaN drain on Si (100) substrate
title_fullStr Optimization of NoN-melt-back-etching and selectivity for selective area growth of GaN drain on Si (100) substrate
title_full_unstemmed Optimization of NoN-melt-back-etching and selectivity for selective area growth of GaN drain on Si (100) substrate
title_short Optimization of NoN-melt-back-etching and selectivity for selective area growth of GaN drain on Si (100) substrate
title_sort optimization of non melt back etching and selectivity for selective area growth of gan drain on si 100 substrate
url http://dx.doi.org/10.1063/5.0256900
work_keys_str_mv AT chengjunhuang optimizationofnonmeltbacketchingandselectivityforselectiveareagrowthofgandrainonsi100substrate
AT shuohwai optimizationofnonmeltbacketchingandselectivityforselectiveareagrowthofgandrainonsi100substrate
AT tsaifuchung optimizationofnonmeltbacketchingandselectivityforselectiveareagrowthofgandrainonsi100substrate
AT chiennanhsiao optimizationofnonmeltbacketchingandselectivityforselectiveareagrowthofgandrainonsi100substrate
AT bochenglin optimizationofnonmeltbacketchingandselectivityforselectiveareagrowthofgandrainonsi100substrate
AT hungchingtsai optimizationofnonmeltbacketchingandselectivityforselectiveareagrowthofgandrainonsi100substrate
AT chihuanglui optimizationofnonmeltbacketchingandselectivityforselectiveareagrowthofgandrainonsi100substrate
AT edwardyichang optimizationofnonmeltbacketchingandselectivityforselectiveareagrowthofgandrainonsi100substrate
AT mauchungfrankchang optimizationofnonmeltbacketchingandselectivityforselectiveareagrowthofgandrainonsi100substrate