Development of a Technique for Characterizing Bias Temperature Instability-Induced Device-to-Device Variation at SRAM-Relevant Conditions
- Submitting institution
-
Liverpool John Moores University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 1278
- Type
- D - Journal article
- DOI
-
10.1109/TED.2014.2335053
- Title of journal
- IEEE Transactions on Electron Devices
- Article number
- -
- First page
- 3081
- Volume
- 61
- Issue
- 9
- ISSN
- 0018-9383
- Open access status
- Out of scope for open access requirements
- Month of publication
- July
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
8
- Research group(s)
-
D - RCEEE
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work is the key output of the EPSRC-funded project (£463k, EP/I012966/1, PI: J.F. Zhang, 2011-2014) with Cambridge University and the world’s largest microelectronics research institute, IMEC (Belgium), as partners. It underpinned a subsequent EPSRC grant award (£517k, EP/L010607/1, PI: J.F. Zhang, 2014-2018) and led to a fully-funded invited keynote presentation at IEEE CSTIC 2015 (http://www.chinaexhibition.com/trade_events/6375-CSTIC_2015_-_China_Semiconductor_Technology_International_Conference_2015.html). The work has influenced the assessment of Bias Temperature Instability Induced Device to Device Variation at Qualcomm (D. Vigar, Senior Principal Engineer, dvigar@qti.qualcomm.com) and ARM (V. Chandra, Technical Lead, vikas.chandra@arm.com), who became the industrial partners of the latter EPSRC project (EP/L010607/1).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -