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Variability Predictions for the Next Technology Generations of n-type Si(x)Ge(1−x) Nanowire MOSFETs

Using a state-of-the-art quantum transport simulator based on the effective mass approximation, we have thoroughly studied the impact of variability on [Formula: see text] channel gate-all-around nanowire metal-oxide-semiconductor field-effect transistors (NWFETs) associated with random discrete dop...

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Autores principales: Lee, Jaehyun, Badami, Oves, Carrillo-Nuñez, Hamilton, Berrada, Salim, Medina-Bailon, Cristina, Dutta, Tapas, Adamu-Lema, Fikru, Georgiev, Vihar P., Asenov, Asen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6316762/
https://www.ncbi.nlm.nih.gov/pubmed/30563045
http://dx.doi.org/10.3390/mi9120643
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author Lee, Jaehyun
Badami, Oves
Carrillo-Nuñez, Hamilton
Berrada, Salim
Medina-Bailon, Cristina
Dutta, Tapas
Adamu-Lema, Fikru
Georgiev, Vihar P.
Asenov, Asen
author_facet Lee, Jaehyun
Badami, Oves
Carrillo-Nuñez, Hamilton
Berrada, Salim
Medina-Bailon, Cristina
Dutta, Tapas
Adamu-Lema, Fikru
Georgiev, Vihar P.
Asenov, Asen
author_sort Lee, Jaehyun
collection PubMed
description Using a state-of-the-art quantum transport simulator based on the effective mass approximation, we have thoroughly studied the impact of variability on [Formula: see text] channel gate-all-around nanowire metal-oxide-semiconductor field-effect transistors (NWFETs) associated with random discrete dopants, line edge roughness, and metal gate granularity. Performance predictions of NWFETs with different cross-sectional shapes such as square, circle, and ellipse are also investigated. For each NWFETs, the effective masses have carefully been extracted from [Formula: see text] tight-binding band structures. In total, we have generated 7200 transistor samples and performed approximately 10,000 quantum transport simulations. Our statistical analysis reveals that metal gate granularity is dominant among the variability sources considered in this work. Assuming the parameters of the variability sources are the same, we have found that there is no significant difference of variability between SiGe and Si channel NWFETs.
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spelling pubmed-63167622019-01-10 Variability Predictions for the Next Technology Generations of n-type Si(x)Ge(1−x) Nanowire MOSFETs Lee, Jaehyun Badami, Oves Carrillo-Nuñez, Hamilton Berrada, Salim Medina-Bailon, Cristina Dutta, Tapas Adamu-Lema, Fikru Georgiev, Vihar P. Asenov, Asen Micromachines (Basel) Article Using a state-of-the-art quantum transport simulator based on the effective mass approximation, we have thoroughly studied the impact of variability on [Formula: see text] channel gate-all-around nanowire metal-oxide-semiconductor field-effect transistors (NWFETs) associated with random discrete dopants, line edge roughness, and metal gate granularity. Performance predictions of NWFETs with different cross-sectional shapes such as square, circle, and ellipse are also investigated. For each NWFETs, the effective masses have carefully been extracted from [Formula: see text] tight-binding band structures. In total, we have generated 7200 transistor samples and performed approximately 10,000 quantum transport simulations. Our statistical analysis reveals that metal gate granularity is dominant among the variability sources considered in this work. Assuming the parameters of the variability sources are the same, we have found that there is no significant difference of variability between SiGe and Si channel NWFETs. MDPI 2018-12-05 /pmc/articles/PMC6316762/ /pubmed/30563045 http://dx.doi.org/10.3390/mi9120643 Text en © 2018 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
Lee, Jaehyun
Badami, Oves
Carrillo-Nuñez, Hamilton
Berrada, Salim
Medina-Bailon, Cristina
Dutta, Tapas
Adamu-Lema, Fikru
Georgiev, Vihar P.
Asenov, Asen
Variability Predictions for the Next Technology Generations of n-type Si(x)Ge(1−x) Nanowire MOSFETs
title Variability Predictions for the Next Technology Generations of n-type Si(x)Ge(1−x) Nanowire MOSFETs
title_full Variability Predictions for the Next Technology Generations of n-type Si(x)Ge(1−x) Nanowire MOSFETs
title_fullStr Variability Predictions for the Next Technology Generations of n-type Si(x)Ge(1−x) Nanowire MOSFETs
title_full_unstemmed Variability Predictions for the Next Technology Generations of n-type Si(x)Ge(1−x) Nanowire MOSFETs
title_short Variability Predictions for the Next Technology Generations of n-type Si(x)Ge(1−x) Nanowire MOSFETs
title_sort variability predictions for the next technology generations of n-type si(x)ge(1−x) nanowire mosfets
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6316762/
https://www.ncbi.nlm.nih.gov/pubmed/30563045
http://dx.doi.org/10.3390/mi9120643
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