Work-Function Fluctuation of Gate-All-Around Silicon Nanowire n-MOSFETs: A Unified Comparison Between Cuboid and Voronoi Methods
In this article, the work-function fluctuation (WKF) of nanosized metal grains is estimated and compared with the cuboid and Voronoi methods for 10-nm-gate gate-all-around silicon nanowire n-MOSFETs. For the methods having different metal grain numbers (MGNs) and 1000 randomly generated samples, we...
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description | In this article, the work-function fluctuation (WKF) of nanosized metal grains is estimated and compared with the cuboid and Voronoi methods for 10-nm-gate gate-all-around silicon nanowire n-MOSFETs. For the methods having different metal grain numbers (MGNs) and 1000 randomly generated samples, we evaluate the variability of the threshold voltage, off-current and on-current. The estimated errors of figures-of-merit (FOM) above are within 1% between the cuboid and Voronoi methods when the sample increases (e.g., larger than 500) for all MGNs. If a small number of samples are with few metal grains (e.g., MGN = 16), they affect the normal distribution of FOM and cause large error due to the significant random location effect of metal grains. If the Voronoi method generates grains are with acute angles, abrupt changes of electric fields occur among grain boundaries. For large samples, errors of FOM are all within 1% because distributions of FOM follow the Gauss distribution. Thus, the results of this work suggest that the WKF-induced variability calculated by the cuboid method can well approximate to the results of Voronoi method for sufficient large samples. |
doi_str_mv | 10.1109/JEDS.2020.3046608 |
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For the methods having different metal grain numbers (MGNs) and 1000 randomly generated samples, we evaluate the variability of the threshold voltage, off-current and on-current. The estimated errors of figures-of-merit (FOM) above are within 1% between the cuboid and Voronoi methods when the sample increases (e.g., larger than 500) for all MGNs. If a small number of samples are with few metal grains (e.g., MGN = 16), they affect the normal distribution of FOM and cause large error due to the significant random location effect of metal grains. If the Voronoi method generates grains are with acute angles, abrupt changes of electric fields occur among grain boundaries. For large samples, errors of FOM are all within 1% because distributions of FOM follow the Gauss distribution. Thus, the results of this work suggest that the WKF-induced variability calculated by the cuboid method can well approximate to the results of Voronoi method for sufficient large samples.</description><identifier>ISSN: 2168-6734</identifier><identifier>EISSN: 2168-6734</identifier><identifier>DOI: 10.1109/JEDS.2020.3046608</identifier><identifier>CODEN: IJEDAC</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Approximation ; cuboid ; Electric fields ; Fluctuations ; Gallium arsenide ; gate-all-around ; Gaussian distribution ; Grain boundaries ; grain number ; Logic gates ; MOSFETs ; Nanowires ; Normal distribution ; sample size ; Silicon ; Solid modeling ; Three-dimensional displays ; Threshold voltage ; Tin ; Variability ; Voronoi ; Work-function fluctuation</subject><ispartof>IEEE journal of the Electron Devices Society, 2021, Vol.9, p.151-159</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c402t-605c7f49afc4fd8f7ff9e019d93e933464f4d54943c0977575f613b57bf80c493</citedby><cites>FETCH-LOGICAL-c402t-605c7f49afc4fd8f7ff9e019d93e933464f4d54943c0977575f613b57bf80c493</cites><orcidid>0000-0001-7374-0964</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9305254$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,860,2096,4010,27610,27900,27901,27902,54908</link.rule.ids></links><search><creatorcontrib>Sung, Wen-Li</creatorcontrib><creatorcontrib>Yang, Ya-Shu</creatorcontrib><creatorcontrib>Li, Yiming</creatorcontrib><title>Work-Function Fluctuation of Gate-All-Around Silicon Nanowire n-MOSFETs: A Unified Comparison Between Cuboid and Voronoi Methods</title><title>IEEE journal of the Electron Devices Society</title><addtitle>JEDS</addtitle><description>In this article, the work-function fluctuation (WKF) of nanosized metal grains is estimated and compared with the cuboid and Voronoi methods for 10-nm-gate gate-all-around silicon nanowire n-MOSFETs. For the methods having different metal grain numbers (MGNs) and 1000 randomly generated samples, we evaluate the variability of the threshold voltage, off-current and on-current. The estimated errors of figures-of-merit (FOM) above are within 1% between the cuboid and Voronoi methods when the sample increases (e.g., larger than 500) for all MGNs. If a small number of samples are with few metal grains (e.g., MGN = 16), they affect the normal distribution of FOM and cause large error due to the significant random location effect of metal grains. If the Voronoi method generates grains are with acute angles, abrupt changes of electric fields occur among grain boundaries. For large samples, errors of FOM are all within 1% because distributions of FOM follow the Gauss distribution. Thus, the results of this work suggest that the WKF-induced variability calculated by the cuboid method can well approximate to the results of Voronoi method for sufficient large samples.</description><subject>Approximation</subject><subject>cuboid</subject><subject>Electric fields</subject><subject>Fluctuations</subject><subject>Gallium arsenide</subject><subject>gate-all-around</subject><subject>Gaussian distribution</subject><subject>Grain boundaries</subject><subject>grain number</subject><subject>Logic gates</subject><subject>MOSFETs</subject><subject>Nanowires</subject><subject>Normal distribution</subject><subject>sample size</subject><subject>Silicon</subject><subject>Solid modeling</subject><subject>Three-dimensional displays</subject><subject>Threshold voltage</subject><subject>Tin</subject><subject>Variability</subject><subject>Voronoi</subject><subject>Work-function fluctuation</subject><issn>2168-6734</issn><issn>2168-6734</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNkcFOGzEQhldVKxVRHgD1YonzpuO117vmlqaEgqAcUujRcmwPOF3s1N4V6q2PjkMQqi8ejf_5xtJXVccUZpSC_HJ59m01a6CBGQMuBPTvqoOGir4WHePv_6s_Vkc5b6CcngopxEH171dMv-vlFMzoYyDLYTLjpF_qiORcj66eD0M9T3EKlqz84E15-qFDfPLJkVBf36yWZz_zKZmT2-DRO0sW8XGrk88l-NWNT84FspjW0VuiC-MuphiiJ9dufIg2f6o-oB6yO3q9D6vbwlt8r69uzi8W86vacGjGWkBrOuRSo-Foe-wQpQMqrWROMsYFR25bLjkzILuu7VoUlK3bbo09GC7ZYXWx59qoN2qb_KNOf1XUXr00YrpXOo3eDE4Z14NsOIJA5FR22qABazhnhU5bLKyTPWub4p_J5VFt4pRC-b5qyioBRUpTUnSfMinmnBy-baWgdt7UzpvaeVOv3srM5_2Md8695SWDtmk5ewae8ZLA</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Sung, Wen-Li</creator><creator>Yang, Ya-Shu</creator><creator>Li, Yiming</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-7374-0964</orcidid></search><sort><creationdate>2021</creationdate><title>Work-Function Fluctuation of Gate-All-Around Silicon Nanowire n-MOSFETs: A Unified Comparison Between Cuboid and Voronoi Methods</title><author>Sung, Wen-Li ; Yang, Ya-Shu ; Li, Yiming</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c402t-605c7f49afc4fd8f7ff9e019d93e933464f4d54943c0977575f613b57bf80c493</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Approximation</topic><topic>cuboid</topic><topic>Electric fields</topic><topic>Fluctuations</topic><topic>Gallium arsenide</topic><topic>gate-all-around</topic><topic>Gaussian distribution</topic><topic>Grain boundaries</topic><topic>grain number</topic><topic>Logic gates</topic><topic>MOSFETs</topic><topic>Nanowires</topic><topic>Normal distribution</topic><topic>sample size</topic><topic>Silicon</topic><topic>Solid modeling</topic><topic>Three-dimensional displays</topic><topic>Threshold voltage</topic><topic>Tin</topic><topic>Variability</topic><topic>Voronoi</topic><topic>Work-function fluctuation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sung, Wen-Li</creatorcontrib><creatorcontrib>Yang, Ya-Shu</creatorcontrib><creatorcontrib>Li, Yiming</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>IEEE journal of the Electron Devices Society</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sung, Wen-Li</au><au>Yang, Ya-Shu</au><au>Li, Yiming</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Work-Function Fluctuation of Gate-All-Around Silicon Nanowire n-MOSFETs: A Unified Comparison Between Cuboid and Voronoi Methods</atitle><jtitle>IEEE journal of the Electron Devices Society</jtitle><stitle>JEDS</stitle><date>2021</date><risdate>2021</risdate><volume>9</volume><spage>151</spage><epage>159</epage><pages>151-159</pages><issn>2168-6734</issn><eissn>2168-6734</eissn><coden>IJEDAC</coden><abstract>In this article, the work-function fluctuation (WKF) of nanosized metal grains is estimated and compared with the cuboid and Voronoi methods for 10-nm-gate gate-all-around silicon nanowire n-MOSFETs. For the methods having different metal grain numbers (MGNs) and 1000 randomly generated samples, we evaluate the variability of the threshold voltage, off-current and on-current. The estimated errors of figures-of-merit (FOM) above are within 1% between the cuboid and Voronoi methods when the sample increases (e.g., larger than 500) for all MGNs. If a small number of samples are with few metal grains (e.g., MGN = 16), they affect the normal distribution of FOM and cause large error due to the significant random location effect of metal grains. If the Voronoi method generates grains are with acute angles, abrupt changes of electric fields occur among grain boundaries. For large samples, errors of FOM are all within 1% because distributions of FOM follow the Gauss distribution. Thus, the results of this work suggest that the WKF-induced variability calculated by the cuboid method can well approximate to the results of Voronoi method for sufficient large samples.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/JEDS.2020.3046608</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0001-7374-0964</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Approximation cuboid Electric fields Fluctuations Gallium arsenide gate-all-around Gaussian distribution Grain boundaries grain number Logic gates MOSFETs Nanowires Normal distribution sample size Silicon Solid modeling Three-dimensional displays Threshold voltage Tin Variability Voronoi Work-function fluctuation |
title | Work-Function Fluctuation of Gate-All-Around Silicon Nanowire n-MOSFETs: A Unified Comparison Between Cuboid and Voronoi Methods |
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