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© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

This study presents an innovative, low-cost, mass-manufacturable ion implantation technique for converting thin film normally on AlGaN/GaN devices into normally off ones. Through TCAD (Technology Computer-Aided Design) simulations, we converted a calibrated normally on transistor into a normally off AlGaN/GaN transistor grown on a silicon <111> substrate using a nitrogen ion implantation energy of 300 keV, which shifted the bandgap from below to above the Fermi level. In addition, the threshold voltage (Vth) was adjusted by altering the nitrogen ion implantation dose. The normally off AlGaN/GaN device exhibited a breakdown voltage of 127.4 V at room temperature because of impact ionization, which showed a positive temperature coefficient of 3 × 10−3 K−1. In this study, the normally off AlGaN/GaN device exhibited an average drain current gain of 45.3%, which was confirmed through an analysis of transfer characteristics by changing the gate-to-source ramping. Accordingly, the proposed technique enabled the successful simulation of a 100-µm-wide device that can generate a saturation drain current of 1.4 A/mm at a gate-to-source voltage of 4 V, with a mobility of 1487 cm2V−1s−1. The advantages of the proposed technique are summarized herein in terms of processing and performance.

Details

Title
A Novel Nitrogen Ion Implantation Technique for Turning Thin Film “Normally On” AlGaN/GaN Transistor into “Normally Off” Using TCAD Simulation
Author
Sheu, Gene 1 ; Yu-Lin, Song 2   VIAFID ORCID Logo  ; Dupati Susmitha 1 ; Kutagulla Issac 1   VIAFID ORCID Logo  ; Mogarala, Ramyasri 1 

 Department of Computer Science and Information Engineering, Asia University, Taichung 41354, Taiwan; [email protected] (G.S.); [email protected] (D.S.); [email protected] (K.I.); [email protected] (R.M.) 
 Department of Computer Science and Information Engineering, Asia University, Taichung 41354, Taiwan; [email protected] (G.S.); [email protected] (D.S.); [email protected] (K.I.); [email protected] (R.M.); Department of Bioinformatics and Medical Engineering, Asia University, Taichung 41354, Taiwan 
First page
899
Publication year
2021
Publication date
2021
Publisher
MDPI AG
e-ISSN
20770375
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2602126953
Copyright
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.