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Fluctuation Sensitivity Map: A Novel Technique to Characterise and Predict Device Behaviour Under Metal Grain Work-Function Variability Effects

Karol Kalna Orcid Logo

IEEE Transactions on Electron Devices, Volume: 64, Issue: 4, Pages: 1695 - 1701

Swansea University Author: Karol Kalna Orcid Logo

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DOI (Published version): 10.1109/TED.2017.267006

Abstract

A new technique developed for the analysis of intrinsic sources of variability affecting the performance of semiconductor devices is presented. It is based on the creation of a fluctuation sensitivity map (FSM), which supplies spatial information about the source of variability affecting the device...

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Published in: IEEE Transactions on Electron Devices
ISSN: 0018-9383
Published: 2017
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URI: https://cronfa.swan.ac.uk/Record/cronfa32121
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spelling 2017-04-05T14:40:55.6023093 v2 32121 2017-02-27 Fluctuation Sensitivity Map: A Novel Technique to Characterise and Predict Device Behaviour Under Metal Grain Work-Function Variability Effects 1329a42020e44fdd13de2f20d5143253 0000-0002-6333-9189 Karol Kalna Karol Kalna true false 2017-02-27 EEEG A new technique developed for the analysis of intrinsic sources of variability affecting the performance of semiconductor devices is presented. It is based on the creation of a fluctuation sensitivity map (FSM), which supplies spatial information about the source of variability affecting the device performance and reliability, providing useful advice in the development of fluctuation-resistant device architectures. We have applied the FSM to metal grain work-function variations (MGWVs), since they are one of the major contributors to device variability. This technique is computationally very efficient because, once the original FSM is created, it can be used to predict the MGWV for different metal gates or grain sizes (GSs). Two state-of-the-art devices were used as test-models: a 10.7-nm gate length Si FinFET and 10.4-nm gate length In0.53Ga0.47As FinFET. The cross-sectional shape (triangular, rectangular, or bullet), the metal used in the gate (TiN or WN), and the GS (10, 7, and 5 nm) have been used as test scenarios for this technique. Journal Article IEEE Transactions on Electron Devices 64 4 1695 1701 0018-9383 Voronoi, FinFETs, gate work-function variability, intrinsic parameter fluctuations, sensitivity map 30 4 2017 2017-04-30 10.1109/TED.2017.267006 COLLEGE NANME Electronic and Electrical Engineering COLLEGE CODE EEEG Swansea University 2017-04-05T14:40:55.6023093 2017-02-27T09:51:26.5352874 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering Karol Kalna 0000-0002-6333-9189 1 0032121-28022017120713.pdf indelecio2017.pdf 2017-02-28T12:07:13.5700000 Output 2346710 application/pdf Accepted Manuscript true 2017-02-28T00:00:00.0000000 false eng
title Fluctuation Sensitivity Map: A Novel Technique to Characterise and Predict Device Behaviour Under Metal Grain Work-Function Variability Effects
spellingShingle Fluctuation Sensitivity Map: A Novel Technique to Characterise and Predict Device Behaviour Under Metal Grain Work-Function Variability Effects
Karol Kalna
title_short Fluctuation Sensitivity Map: A Novel Technique to Characterise and Predict Device Behaviour Under Metal Grain Work-Function Variability Effects
title_full Fluctuation Sensitivity Map: A Novel Technique to Characterise and Predict Device Behaviour Under Metal Grain Work-Function Variability Effects
title_fullStr Fluctuation Sensitivity Map: A Novel Technique to Characterise and Predict Device Behaviour Under Metal Grain Work-Function Variability Effects
title_full_unstemmed Fluctuation Sensitivity Map: A Novel Technique to Characterise and Predict Device Behaviour Under Metal Grain Work-Function Variability Effects
title_sort Fluctuation Sensitivity Map: A Novel Technique to Characterise and Predict Device Behaviour Under Metal Grain Work-Function Variability Effects
author_id_str_mv 1329a42020e44fdd13de2f20d5143253
author_id_fullname_str_mv 1329a42020e44fdd13de2f20d5143253_***_Karol Kalna
author Karol Kalna
author2 Karol Kalna
format Journal article
container_title IEEE Transactions on Electron Devices
container_volume 64
container_issue 4
container_start_page 1695
publishDate 2017
institution Swansea University
issn 0018-9383
doi_str_mv 10.1109/TED.2017.267006
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering
document_store_str 1
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description A new technique developed for the analysis of intrinsic sources of variability affecting the performance of semiconductor devices is presented. It is based on the creation of a fluctuation sensitivity map (FSM), which supplies spatial information about the source of variability affecting the device performance and reliability, providing useful advice in the development of fluctuation-resistant device architectures. We have applied the FSM to metal grain work-function variations (MGWVs), since they are one of the major contributors to device variability. This technique is computationally very efficient because, once the original FSM is created, it can be used to predict the MGWV for different metal gates or grain sizes (GSs). Two state-of-the-art devices were used as test-models: a 10.7-nm gate length Si FinFET and 10.4-nm gate length In0.53Ga0.47As FinFET. The cross-sectional shape (triangular, rectangular, or bullet), the metal used in the gate (TiN or WN), and the GS (10, 7, and 5 nm) have been used as test scenarios for this technique.
published_date 2017-04-30T03:39:19Z
_version_ 1763751765624225792
score 11.035349

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