Statistical characterization of time-dependent variability defects using the maximum current fluctuation
This article presents a new methodology to extract, at a given operation condition, the statistical distribution of the number of active defects that contribute to the observed device time-dependent variability, as well as their amplitude distribution. Unlike traditional approaches based on complex...
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creator | Saraza-Canflanca, Pablo Martin Martinez, Javier Castro-Lopez, Rafael Roca, Elisenda Rodríguez Martínez, Rosana Fernandez, Francisco V Nafría i Maqueda, Montserrat |
description | This article presents a new methodology to extract, at a given operation condition, the statistical distribution of the number of active defects that contribute to the observed device time-dependent variability, as well as their amplitude distribution. Unlike traditional approaches based on complex and time-consuming individual analysis of thousands of current traces, the proposed approach uses a simpler trace processing, since only the maximum and minimum values of the drain current during a given time interval are needed. Moreover, this extraction method can also estimate defects causing small current shifts, which can be very complex to identify by traditional means. Experimental data in a wide range of gate voltages, from near-threshold up to nominal operation conditions, are analyzed with the proposed methodology. |
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Unlike traditional approaches based on complex and time-consuming individual analysis of thousands of current traces, the proposed approach uses a simpler trace processing, since only the maximum and minimum values of the drain current during a given time interval are needed. Moreover, this extraction method can also estimate defects causing small current shifts, which can be very complex to identify by traditional means. 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Unlike traditional approaches based on complex and time-consuming individual analysis of thousands of current traces, the proposed approach uses a simpler trace processing, since only the maximum and minimum values of the drain current during a given time interval are needed. Moreover, this extraction method can also estimate defects causing small current shifts, which can be very complex to identify by traditional means. Experimental data in a wide range of gate voltages, from near-threshold up to nominal operation conditions, are analyzed with the proposed methodology.</description><subject>Bias temperature instability (BTI)</subject><subject>Maximum current fluctuation (MCF)</subject><subject>Random telegraph noise (RTN)</subject><subject>Time-dependent variability (TDV)</subject><subject>Transistor</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>XX2</sourceid><recordid>eNqdjMEKwjAQRHvxIOo_7A8U2hTxA0Txrvewbjd2IUkl2Yj69VoRvHsYhnnMzLwajooqWYXQAw2YkJSTPN9wjDA6UAlc93zl2HNUuGESPIsXfUDPjkkzlCzxAjowBLxLKAGopDS1nS-k5fO1rGYOfebV1xdVu9-dtoeaciGbmDgRqh1RfmGSaTbGrlvTmK77Z_MCcPxO6Q</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Saraza-Canflanca, Pablo</creator><creator>Martin Martinez, Javier</creator><creator>Castro-Lopez, Rafael</creator><creator>Roca, Elisenda</creator><creator>Rodríguez Martínez, Rosana</creator><creator>Fernandez, Francisco V</creator><creator>Nafría i Maqueda, Montserrat</creator><scope>XX2</scope></search><sort><creationdate>2021</creationdate><title>Statistical characterization of time-dependent variability defects using the maximum current fluctuation</title><author>Saraza-Canflanca, Pablo ; Martin Martinez, Javier ; Castro-Lopez, Rafael ; Roca, Elisenda ; Rodríguez Martínez, Rosana ; Fernandez, Francisco V ; Nafría i Maqueda, Montserrat</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-csuc_recercat_oai_recercat_cat_2072_5120233</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Bias temperature instability (BTI)</topic><topic>Maximum current fluctuation (MCF)</topic><topic>Random telegraph noise (RTN)</topic><topic>Time-dependent variability (TDV)</topic><topic>Transistor</topic><toplevel>online_resources</toplevel><creatorcontrib>Saraza-Canflanca, Pablo</creatorcontrib><creatorcontrib>Martin Martinez, Javier</creatorcontrib><creatorcontrib>Castro-Lopez, Rafael</creatorcontrib><creatorcontrib>Roca, Elisenda</creatorcontrib><creatorcontrib>Rodríguez Martínez, Rosana</creatorcontrib><creatorcontrib>Fernandez, Francisco V</creatorcontrib><creatorcontrib>Nafría i Maqueda, Montserrat</creatorcontrib><collection>Recercat</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Saraza-Canflanca, Pablo</au><au>Martin Martinez, Javier</au><au>Castro-Lopez, Rafael</au><au>Roca, Elisenda</au><au>Rodríguez Martínez, Rosana</au><au>Fernandez, Francisco V</au><au>Nafría i Maqueda, Montserrat</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Statistical characterization of time-dependent variability defects using the maximum current fluctuation</atitle><date>2021</date><risdate>2021</risdate><abstract>This article presents a new methodology to extract, at a given operation condition, the statistical distribution of the number of active defects that contribute to the observed device time-dependent variability, as well as their amplitude distribution. Unlike traditional approaches based on complex and time-consuming individual analysis of thousands of current traces, the proposed approach uses a simpler trace processing, since only the maximum and minimum values of the drain current during a given time interval are needed. Moreover, this extraction method can also estimate defects causing small current shifts, which can be very complex to identify by traditional means. Experimental data in a wide range of gate voltages, from near-threshold up to nominal operation conditions, are analyzed with the proposed methodology.</abstract><oa>free_for_read</oa></addata></record> |
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subjects | Bias temperature instability (BTI) Maximum current fluctuation (MCF) Random telegraph noise (RTN) Time-dependent variability (TDV) Transistor |
title | Statistical characterization of time-dependent variability defects using the maximum current fluctuation |
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