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Retention Secured Nonlinear and Self‐Rectifying Analog Charge Trap Memristor for Energy‐Efficient Neuromorphic Hardware
A memristive crossbar array (MCA) is an ideal platform for emerging memory and neuromorphic hardware due to its high bitwise density capability. A charge trap memristor (CTM) is an attractive candidate for the memristor cell of the MCA, because the embodied rectifying characteristic frees it from th...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9875615/ https://www.ncbi.nlm.nih.gov/pubmed/36437042 http://dx.doi.org/10.1002/advs.202205654 |
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author | Kim, Geunyoung Son, Seoil Song, Hanchan Jeon, Jae Bum Lee, Jiyun Cheong, Woon Hyung Choi, Shinhyun Kim, Kyung Min |
author_facet | Kim, Geunyoung Son, Seoil Song, Hanchan Jeon, Jae Bum Lee, Jiyun Cheong, Woon Hyung Choi, Shinhyun Kim, Kyung Min |
author_sort | Kim, Geunyoung |
collection | PubMed |
description | A memristive crossbar array (MCA) is an ideal platform for emerging memory and neuromorphic hardware due to its high bitwise density capability. A charge trap memristor (CTM) is an attractive candidate for the memristor cell of the MCA, because the embodied rectifying characteristic frees it from the sneak current issue. Although the potential of the CTM devices has been suggested, their practical viability needs to be further proved. Here, a Pt/Ta(2)O(5)/Nb(2)O(5‐) (x) /Al(2)O(3‐) (y) /Ti CTM stack exhibiting high retention and array‐level uniformity is proposed, allowing a highly reliable selector‐less MCA. It shows high self‐rectifying and nonlinear current‐voltage characteristics below 1 µA of programming current with a continuous analog switching behavior. Also, its retention is longer than 10(5) s at 150 °C, suggesting the device is highly stable for non‐volatile analog applications. A plausible band diagram model is proposed based on the electronic spectroscopy results and conduction mechanism analysis. The self‐rectifying and nonlinear characteristics allow reducing the on‐chip training energy consumption by 71% for the MNIST dataset training task with an optimized programming scheme. |
format | Online Article Text |
id | pubmed-9875615 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98756152023-01-25 Retention Secured Nonlinear and Self‐Rectifying Analog Charge Trap Memristor for Energy‐Efficient Neuromorphic Hardware Kim, Geunyoung Son, Seoil Song, Hanchan Jeon, Jae Bum Lee, Jiyun Cheong, Woon Hyung Choi, Shinhyun Kim, Kyung Min Adv Sci (Weinh) Research Articles A memristive crossbar array (MCA) is an ideal platform for emerging memory and neuromorphic hardware due to its high bitwise density capability. A charge trap memristor (CTM) is an attractive candidate for the memristor cell of the MCA, because the embodied rectifying characteristic frees it from the sneak current issue. Although the potential of the CTM devices has been suggested, their practical viability needs to be further proved. Here, a Pt/Ta(2)O(5)/Nb(2)O(5‐) (x) /Al(2)O(3‐) (y) /Ti CTM stack exhibiting high retention and array‐level uniformity is proposed, allowing a highly reliable selector‐less MCA. It shows high self‐rectifying and nonlinear current‐voltage characteristics below 1 µA of programming current with a continuous analog switching behavior. Also, its retention is longer than 10(5) s at 150 °C, suggesting the device is highly stable for non‐volatile analog applications. A plausible band diagram model is proposed based on the electronic spectroscopy results and conduction mechanism analysis. The self‐rectifying and nonlinear characteristics allow reducing the on‐chip training energy consumption by 71% for the MNIST dataset training task with an optimized programming scheme. John Wiley and Sons Inc. 2022-11-27 /pmc/articles/PMC9875615/ /pubmed/36437042 http://dx.doi.org/10.1002/advs.202205654 Text en © 2022 The Authors. Advanced Science published by Wiley‐VCH GmbH https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Kim, Geunyoung Son, Seoil Song, Hanchan Jeon, Jae Bum Lee, Jiyun Cheong, Woon Hyung Choi, Shinhyun Kim, Kyung Min Retention Secured Nonlinear and Self‐Rectifying Analog Charge Trap Memristor for Energy‐Efficient Neuromorphic Hardware |
title | Retention Secured Nonlinear and Self‐Rectifying Analog Charge Trap Memristor for Energy‐Efficient Neuromorphic Hardware |
title_full | Retention Secured Nonlinear and Self‐Rectifying Analog Charge Trap Memristor for Energy‐Efficient Neuromorphic Hardware |
title_fullStr | Retention Secured Nonlinear and Self‐Rectifying Analog Charge Trap Memristor for Energy‐Efficient Neuromorphic Hardware |
title_full_unstemmed | Retention Secured Nonlinear and Self‐Rectifying Analog Charge Trap Memristor for Energy‐Efficient Neuromorphic Hardware |
title_short | Retention Secured Nonlinear and Self‐Rectifying Analog Charge Trap Memristor for Energy‐Efficient Neuromorphic Hardware |
title_sort | retention secured nonlinear and self‐rectifying analog charge trap memristor for energy‐efficient neuromorphic hardware |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9875615/ https://www.ncbi.nlm.nih.gov/pubmed/36437042 http://dx.doi.org/10.1002/advs.202205654 |
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