Cargando…

Semi-Automated Extraction of the Distribution of Single Defects for nMOS Transistors

Miniaturization of metal-oxide-semiconductor field effect transistors (MOSFETs) is typically beneficial for their operating characteristics, such as switching speed and power consumption, but at the same time miniaturization also leads to increased variability among nominally identical devices. Adve...

Descripción completa

Detalles Bibliográficos
Autores principales: Stampfer, Bernhard, Schanovsky, Franz, Grasser, Tibor, Waltl, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7231322/
https://www.ncbi.nlm.nih.gov/pubmed/32340395
http://dx.doi.org/10.3390/mi11040446
_version_ 1783535164656189440
author Stampfer, Bernhard
Schanovsky, Franz
Grasser, Tibor
Waltl, Michael
author_facet Stampfer, Bernhard
Schanovsky, Franz
Grasser, Tibor
Waltl, Michael
author_sort Stampfer, Bernhard
collection PubMed
description Miniaturization of metal-oxide-semiconductor field effect transistors (MOSFETs) is typically beneficial for their operating characteristics, such as switching speed and power consumption, but at the same time miniaturization also leads to increased variability among nominally identical devices. Adverse effects due to oxide traps in particular become a serious issue for device performance and reliability. While the average number of defects per device is lower for scaled devices, the impact of the oxide defects is significantly more pronounced than in large area transistors. This combination enables the investigation of charge transitions of single defects. In this study, we perform random telegraph noise (RTN) measurements on about 300 devices to statistically characterize oxide defects in a Si/SiO [Formula: see text] technology. To extract the noise parameters from the measurements, we make use of the Canny edge detector. From the data, we obtain distributions of the step heights of defects, i.e., their impact on the threshold voltage of the devices. Detailed measurements of a subset of the defects further allow us to extract their vertical position in the oxide and their trap level using both analytical estimations and full numerical simulations. Contrary to published literature data, we observe a bimodal distribution of step heights, while the extracted distribution of trap levels agrees well with recent studies.
format Online
Article
Text
id pubmed-7231322
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-72313222020-05-22 Semi-Automated Extraction of the Distribution of Single Defects for nMOS Transistors Stampfer, Bernhard Schanovsky, Franz Grasser, Tibor Waltl, Michael Micromachines (Basel) Article Miniaturization of metal-oxide-semiconductor field effect transistors (MOSFETs) is typically beneficial for their operating characteristics, such as switching speed and power consumption, but at the same time miniaturization also leads to increased variability among nominally identical devices. Adverse effects due to oxide traps in particular become a serious issue for device performance and reliability. While the average number of defects per device is lower for scaled devices, the impact of the oxide defects is significantly more pronounced than in large area transistors. This combination enables the investigation of charge transitions of single defects. In this study, we perform random telegraph noise (RTN) measurements on about 300 devices to statistically characterize oxide defects in a Si/SiO [Formula: see text] technology. To extract the noise parameters from the measurements, we make use of the Canny edge detector. From the data, we obtain distributions of the step heights of defects, i.e., their impact on the threshold voltage of the devices. Detailed measurements of a subset of the defects further allow us to extract their vertical position in the oxide and their trap level using both analytical estimations and full numerical simulations. Contrary to published literature data, we observe a bimodal distribution of step heights, while the extracted distribution of trap levels agrees well with recent studies. MDPI 2020-04-23 /pmc/articles/PMC7231322/ /pubmed/32340395 http://dx.doi.org/10.3390/mi11040446 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Stampfer, Bernhard
Schanovsky, Franz
Grasser, Tibor
Waltl, Michael
Semi-Automated Extraction of the Distribution of Single Defects for nMOS Transistors
title Semi-Automated Extraction of the Distribution of Single Defects for nMOS Transistors
title_full Semi-Automated Extraction of the Distribution of Single Defects for nMOS Transistors
title_fullStr Semi-Automated Extraction of the Distribution of Single Defects for nMOS Transistors
title_full_unstemmed Semi-Automated Extraction of the Distribution of Single Defects for nMOS Transistors
title_short Semi-Automated Extraction of the Distribution of Single Defects for nMOS Transistors
title_sort semi-automated extraction of the distribution of single defects for nmos transistors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7231322/
https://www.ncbi.nlm.nih.gov/pubmed/32340395
http://dx.doi.org/10.3390/mi11040446
work_keys_str_mv AT stampferbernhard semiautomatedextractionofthedistributionofsingledefectsfornmostransistors
AT schanovskyfranz semiautomatedextractionofthedistributionofsingledefectsfornmostransistors
AT grassertibor semiautomatedextractionofthedistributionofsingledefectsfornmostransistors
AT waltlmichael semiautomatedextractionofthedistributionofsingledefectsfornmostransistors