Predictive modeling of the NBTI effect for reliable design

Sarvesh Bhardwaj; Wenping Wang; Rakesh Vattikonda; Yu Cao; Sarma Vrudhula

doi:10.1109/CICC.2006.320885

Predictive modeling of the NBTI effect for reliable design

Sarvesh Bhardwaj, Wenping Wang, Rakesh Vattikonda, Yu Cao, Sarma Vrudhula

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

375 Scopus citations

Abstract

This paper presents a predictive model for the Negative Bias Temperature Instability (NBTI) of PMOS under both short term and long term operation. Based on the reaction-diffusion (R-D) mechanism, this model accurately captures the dependence of NBTI on the oxide thickness (t_ox), the diffusing species (H or H₂) and other key transistor and design parameters. In addition, we derive a closed form expression for the threshold voltage change (ΔV_th) under multiple cycle dynamic operation. Model accuracy and efficiency were verified with 90-nm experimental and simulation data. We further investigated the impact of NBTI on representative digital circuits.

Original language	English (US)
Title of host publication	Proceedings of the IEEE 2006 Custom Integrated Circuits Conference, CICC 2006
Pages	189-192
Number of pages	4
DOIs	https://doi.org/10.1109/CICC.2006.320885
State	Published - 2006
Event	IEEE 2006 Custom Integrated Circuits Conference, CICC 2006 - San Jose, CA, United States Duration: Sep 10 2006 → Sep 13 2006

Publication series

Name	Proceedings of the Custom Integrated Circuits Conference
ISSN (Print)	0886-5930

Other

Other	IEEE 2006 Custom Integrated Circuits Conference, CICC 2006
Country/Territory	United States
City	San Jose, CA
Period	9/10/06 → 9/13/06

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1109/CICC.2006.320885

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Predictive modeling of the NBTI effect for reliable design. / Bhardwaj, Sarvesh; Wang, Wenping; Vattikonda, Rakesh et al.
Proceedings of the IEEE 2006 Custom Integrated Circuits Conference, CICC 2006. 2006. p. 189-192 4114936 (Proceedings of the Custom Integrated Circuits Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Bhardwaj, S, Wang, W, Vattikonda, R, Cao, Y & Vrudhula, S 2006, Predictive modeling of the NBTI effect for reliable design. in Proceedings of the IEEE 2006 Custom Integrated Circuits Conference, CICC 2006., 4114936, Proceedings of the Custom Integrated Circuits Conference, pp. 189-192, IEEE 2006 Custom Integrated Circuits Conference, CICC 2006, San Jose, CA, United States, 9/10/06. https://doi.org/10.1109/CICC.2006.320885

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abstract = "This paper presents a predictive model for the Negative Bias Temperature Instability (NBTI) of PMOS under both short term and long term operation. Based on the reaction-diffusion (R-D) mechanism, this model accurately captures the dependence of NBTI on the oxide thickness (tox), the diffusing species (H or H2) and other key transistor and design parameters. In addition, we derive a closed form expression for the threshold voltage change (ΔVth) under multiple cycle dynamic operation. Model accuracy and efficiency were verified with 90-nm experimental and simulation data. We further investigated the impact of NBTI on representative digital circuits.",

author = "Sarvesh Bhardwaj and Wenping Wang and Rakesh Vattikonda and Yu Cao and Sarma Vrudhula",

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doi = "10.1109/CICC.2006.320885",

language = "English (US)",

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PY - 2006

Y1 - 2006

N2 - This paper presents a predictive model for the Negative Bias Temperature Instability (NBTI) of PMOS under both short term and long term operation. Based on the reaction-diffusion (R-D) mechanism, this model accurately captures the dependence of NBTI on the oxide thickness (tox), the diffusing species (H or H2) and other key transistor and design parameters. In addition, we derive a closed form expression for the threshold voltage change (ΔVth) under multiple cycle dynamic operation. Model accuracy and efficiency were verified with 90-nm experimental and simulation data. We further investigated the impact of NBTI on representative digital circuits.

AB - This paper presents a predictive model for the Negative Bias Temperature Instability (NBTI) of PMOS under both short term and long term operation. Based on the reaction-diffusion (R-D) mechanism, this model accurately captures the dependence of NBTI on the oxide thickness (tox), the diffusing species (H or H2) and other key transistor and design parameters. In addition, we derive a closed form expression for the threshold voltage change (ΔVth) under multiple cycle dynamic operation. Model accuracy and efficiency were verified with 90-nm experimental and simulation data. We further investigated the impact of NBTI on representative digital circuits.

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Predictive modeling of the NBTI effect for reliable design

Abstract

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