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Trap-state mapping to model GaN transistors dynamic performance
Trapping phenomena degrade the dynamic performance of wide-bandgap transistors. However, the identification of the related traps is challenging, especially in presence of non-ideal defects. In this paper, we propose a novel methodology (trap-state mapping) to extract trap parameters, based on the ma...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8810804/ https://www.ncbi.nlm.nih.gov/pubmed/35110655 http://dx.doi.org/10.1038/s41598-022-05830-7 |
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author | Modolo, Nicola De Santi, Carlo Minetto, Andrea Sayadi, Luca Prechtl, Gerhard Meneghesso, Gaudenzio Zanoni, Enrico Meneghini, Matteo |
author_facet | Modolo, Nicola De Santi, Carlo Minetto, Andrea Sayadi, Luca Prechtl, Gerhard Meneghesso, Gaudenzio Zanoni, Enrico Meneghini, Matteo |
author_sort | Modolo, Nicola |
collection | PubMed |
description | Trapping phenomena degrade the dynamic performance of wide-bandgap transistors. However, the identification of the related traps is challenging, especially in presence of non-ideal defects. In this paper, we propose a novel methodology (trap-state mapping) to extract trap parameters, based on the mathematical study of stretched exponential recovery kinetics. To demonstrate the effectiveness of the approach, we use it to identify the properties of traps in AlGaN/GaN transistors, submitted to hot-electron stress. After describing the mathematical framework, we demonstrate that the proposed methodology can univocally describe the properties of the distribution of trap states. In addition, to prove the validity and the usefulness of the model, the trap properties extracted mathematically are used as input for TCAD simulations. The results obtained by TCAD closely match the experimental transient curves, thus confirming the accuracy of the trap-state mapping procedure. This methodology can be adopted also on other technologies, thus constituting a universal approach for the analysis of multiexponential trapping kinetics. |
format | Online Article Text |
id | pubmed-8810804 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-88108042022-02-03 Trap-state mapping to model GaN transistors dynamic performance Modolo, Nicola De Santi, Carlo Minetto, Andrea Sayadi, Luca Prechtl, Gerhard Meneghesso, Gaudenzio Zanoni, Enrico Meneghini, Matteo Sci Rep Article Trapping phenomena degrade the dynamic performance of wide-bandgap transistors. However, the identification of the related traps is challenging, especially in presence of non-ideal defects. In this paper, we propose a novel methodology (trap-state mapping) to extract trap parameters, based on the mathematical study of stretched exponential recovery kinetics. To demonstrate the effectiveness of the approach, we use it to identify the properties of traps in AlGaN/GaN transistors, submitted to hot-electron stress. After describing the mathematical framework, we demonstrate that the proposed methodology can univocally describe the properties of the distribution of trap states. In addition, to prove the validity and the usefulness of the model, the trap properties extracted mathematically are used as input for TCAD simulations. The results obtained by TCAD closely match the experimental transient curves, thus confirming the accuracy of the trap-state mapping procedure. This methodology can be adopted also on other technologies, thus constituting a universal approach for the analysis of multiexponential trapping kinetics. Nature Publishing Group UK 2022-02-02 /pmc/articles/PMC8810804/ /pubmed/35110655 http://dx.doi.org/10.1038/s41598-022-05830-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Modolo, Nicola De Santi, Carlo Minetto, Andrea Sayadi, Luca Prechtl, Gerhard Meneghesso, Gaudenzio Zanoni, Enrico Meneghini, Matteo Trap-state mapping to model GaN transistors dynamic performance |
title | Trap-state mapping to model GaN transistors dynamic performance |
title_full | Trap-state mapping to model GaN transistors dynamic performance |
title_fullStr | Trap-state mapping to model GaN transistors dynamic performance |
title_full_unstemmed | Trap-state mapping to model GaN transistors dynamic performance |
title_short | Trap-state mapping to model GaN transistors dynamic performance |
title_sort | trap-state mapping to model gan transistors dynamic performance |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8810804/ https://www.ncbi.nlm.nih.gov/pubmed/35110655 http://dx.doi.org/10.1038/s41598-022-05830-7 |
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