Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/86839
Title: A vacancy-interstitial defect pair model for positive-bias temperature stress-induced electron trapping transformation in the high-κ gate n-MOSFET
Authors: Gu, Chenjie
Ang, Diing Shenp
Gao, Yuan
Gu, Renyuan
Zhao, Ziqi
Zhu, Chao
Keywords: CMOS Reliability
Dynamic Bias Temperature Instability (BTI)
Issue Date: 2017
Source: Gu, C., Ang, D. S., Gao, Y., Gu, R., Zhao, Z., & Zhu, C. (2017). A vacancy-interstitial defect pair model for positive-bias temperature stress-induced electron trapping transformation in the high-κ gate n-MOSFET. IEEE Transactions on Electron Devices, 64(6), 2505-2511.
Series/Report no.: IEEE Transactions on Electron Devices
Abstract: Recent device reliability studies have observed the shallow-to-deep transformation of electron-trap states under positive-bias temperature stressing. Being two typical types of defects in the high-κ oxide, the oxygen vacancy and oxygen interstitial have been investigated in many simulations, but results have indicated that the corresponding defect levels are either too shallow or too deep and fail to explain the experimental observation. Here, we propose a vacancy-interstitial (V o -O i ) model. By tuning the relative positions of V o and O i , we show that the charge trap level of the defect pair can be adjusted continuously within the HfO 2 bandgap. This allows us to depict a possible atomic picture for understanding the shallow-to-deep transformation of electron trapping.
URI: https://hdl.handle.net/10356/86839
http://hdl.handle.net/10220/45202
ISSN: 0018-9383
DOI: 10.1109/TED.2017.2694440
Rights: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/TED.2017.2694440].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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