Abstract

This paper describes a new approach for modeling bias-temperature instability (BTI) in nanoscale transistors. The model uses non-iterative surface potential solvers enhanced with dynamic defect potential equations to enable accurate, physics-based circuit level simulations that incorporate BTI effects. Defect maps constructed from experimental data reported on high-k-metal-gate bulk complementary metal-oxide-semiconductor devices are used to parameterize the defect potential equation. By implementing the enhanced surface potential model in Verilog-A, both DC and AC BTI aging effects in combinational circuits are simulated and the results compared conventional threshold voltage shift methods for BTI modeling.

Original languageEnglish (US)
Article number225701
JournalJournal of Applied Physics
Volume123
Issue number22
DOIs
StatePublished - Jun 14 2018

Fingerprint

dynamic models
CMOS
defects
temperature
semiconductor devices
threshold voltage
alternating current
transistors
direct current
physics
shift
metals
simulation

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Bias temperature instability model using dynamic defect potential for predicting CMOS aging. / Fang, Runchen; Livingston, Ian; Esqueda, Ivan Sanchez; Kozicki, Michael; Barnaby, Hugh.

In: Journal of Applied Physics, Vol. 123, No. 22, 225701, 14.06.2018.

Research output: Contribution to journalArticle

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AB - This paper describes a new approach for modeling bias-temperature instability (BTI) in nanoscale transistors. The model uses non-iterative surface potential solvers enhanced with dynamic defect potential equations to enable accurate, physics-based circuit level simulations that incorporate BTI effects. Defect maps constructed from experimental data reported on high-k-metal-gate bulk complementary metal-oxide-semiconductor devices are used to parameterize the defect potential equation. By implementing the enhanced surface potential model in Verilog-A, both DC and AC BTI aging effects in combinational circuits are simulated and the results compared conventional threshold voltage shift methods for BTI modeling.

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