Cargando…
Distinguishing artificial spin ice states using magnetoresistance effect for neuromorphic computing
Artificial spin ice (ASI) consisting patterned array of nano-magnets with frustrated dipolar interactions offers an excellent platform to study frustrated physics using direct imaging methods. Moreover, ASI often hosts a large number of nearly degenerated and non-volatile spin states that can be use...
Autores principales: | , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10160026/ https://www.ncbi.nlm.nih.gov/pubmed/37142614 http://dx.doi.org/10.1038/s41467-023-38286-y |
_version_ | 1785037197218414592 |
---|---|
author | Hu, Wenjie Zhang, Zefeng Liao, Yanghui Li, Qiang Shi, Yang Zhang, Huanyu Zhang, Xumeng Niu, Chang Wu, Yu Yu, Weichao Zhou, Xiaodong Guo, Hangwen Wang, Wenbin Xiao, Jiang Yin, Lifeng Liu, Qi Shen, Jian |
author_facet | Hu, Wenjie Zhang, Zefeng Liao, Yanghui Li, Qiang Shi, Yang Zhang, Huanyu Zhang, Xumeng Niu, Chang Wu, Yu Yu, Weichao Zhou, Xiaodong Guo, Hangwen Wang, Wenbin Xiao, Jiang Yin, Lifeng Liu, Qi Shen, Jian |
author_sort | Hu, Wenjie |
collection | PubMed |
description | Artificial spin ice (ASI) consisting patterned array of nano-magnets with frustrated dipolar interactions offers an excellent platform to study frustrated physics using direct imaging methods. Moreover, ASI often hosts a large number of nearly degenerated and non-volatile spin states that can be used for multi-bit data storage and neuromorphic computing. The realization of the device potential of ASI, however, critically relies on the capability of transport characterization of ASI, which has not been demonstrated so far. Using a tri-axial ASI system as the model system, we demonstrate that transport measurements can be used to distinguish the different spin states of the ASI system. Specifically, by fabricating a tri-layer structure consisting a permalloy base layer, a Cu spacer layer and the tri-axial ASI layer, we clearly resolve different spin states in the tri-axial ASI system using lateral transport measurements. We have further demonstrated that the tri-axial ASI system has all necessary required properties for reservoir computing, including rich spin configurations to store input signals, nonlinear response to input signals, and fading memory effect. The successful transport characterization of ASI opens up the prospect for novel device applications of ASI in multi-bit data storage and neuromorphic computing. |
format | Online Article Text |
id | pubmed-10160026 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-101600262023-05-06 Distinguishing artificial spin ice states using magnetoresistance effect for neuromorphic computing Hu, Wenjie Zhang, Zefeng Liao, Yanghui Li, Qiang Shi, Yang Zhang, Huanyu Zhang, Xumeng Niu, Chang Wu, Yu Yu, Weichao Zhou, Xiaodong Guo, Hangwen Wang, Wenbin Xiao, Jiang Yin, Lifeng Liu, Qi Shen, Jian Nat Commun Article Artificial spin ice (ASI) consisting patterned array of nano-magnets with frustrated dipolar interactions offers an excellent platform to study frustrated physics using direct imaging methods. Moreover, ASI often hosts a large number of nearly degenerated and non-volatile spin states that can be used for multi-bit data storage and neuromorphic computing. The realization of the device potential of ASI, however, critically relies on the capability of transport characterization of ASI, which has not been demonstrated so far. Using a tri-axial ASI system as the model system, we demonstrate that transport measurements can be used to distinguish the different spin states of the ASI system. Specifically, by fabricating a tri-layer structure consisting a permalloy base layer, a Cu spacer layer and the tri-axial ASI layer, we clearly resolve different spin states in the tri-axial ASI system using lateral transport measurements. We have further demonstrated that the tri-axial ASI system has all necessary required properties for reservoir computing, including rich spin configurations to store input signals, nonlinear response to input signals, and fading memory effect. The successful transport characterization of ASI opens up the prospect for novel device applications of ASI in multi-bit data storage and neuromorphic computing. Nature Publishing Group UK 2023-05-04 /pmc/articles/PMC10160026/ /pubmed/37142614 http://dx.doi.org/10.1038/s41467-023-38286-y Text en © The Author(s) 2023 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Hu, Wenjie Zhang, Zefeng Liao, Yanghui Li, Qiang Shi, Yang Zhang, Huanyu Zhang, Xumeng Niu, Chang Wu, Yu Yu, Weichao Zhou, Xiaodong Guo, Hangwen Wang, Wenbin Xiao, Jiang Yin, Lifeng Liu, Qi Shen, Jian Distinguishing artificial spin ice states using magnetoresistance effect for neuromorphic computing |
title | Distinguishing artificial spin ice states using magnetoresistance effect for neuromorphic computing |
title_full | Distinguishing artificial spin ice states using magnetoresistance effect for neuromorphic computing |
title_fullStr | Distinguishing artificial spin ice states using magnetoresistance effect for neuromorphic computing |
title_full_unstemmed | Distinguishing artificial spin ice states using magnetoresistance effect for neuromorphic computing |
title_short | Distinguishing artificial spin ice states using magnetoresistance effect for neuromorphic computing |
title_sort | distinguishing artificial spin ice states using magnetoresistance effect for neuromorphic computing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10160026/ https://www.ncbi.nlm.nih.gov/pubmed/37142614 http://dx.doi.org/10.1038/s41467-023-38286-y |
work_keys_str_mv | AT huwenjie distinguishingartificialspinicestatesusingmagnetoresistanceeffectforneuromorphiccomputing AT zhangzefeng distinguishingartificialspinicestatesusingmagnetoresistanceeffectforneuromorphiccomputing AT liaoyanghui distinguishingartificialspinicestatesusingmagnetoresistanceeffectforneuromorphiccomputing AT liqiang distinguishingartificialspinicestatesusingmagnetoresistanceeffectforneuromorphiccomputing AT shiyang distinguishingartificialspinicestatesusingmagnetoresistanceeffectforneuromorphiccomputing AT zhanghuanyu distinguishingartificialspinicestatesusingmagnetoresistanceeffectforneuromorphiccomputing AT zhangxumeng distinguishingartificialspinicestatesusingmagnetoresistanceeffectforneuromorphiccomputing AT niuchang distinguishingartificialspinicestatesusingmagnetoresistanceeffectforneuromorphiccomputing AT wuyu distinguishingartificialspinicestatesusingmagnetoresistanceeffectforneuromorphiccomputing AT yuweichao distinguishingartificialspinicestatesusingmagnetoresistanceeffectforneuromorphiccomputing AT zhouxiaodong distinguishingartificialspinicestatesusingmagnetoresistanceeffectforneuromorphiccomputing AT guohangwen distinguishingartificialspinicestatesusingmagnetoresistanceeffectforneuromorphiccomputing AT wangwenbin distinguishingartificialspinicestatesusingmagnetoresistanceeffectforneuromorphiccomputing AT xiaojiang distinguishingartificialspinicestatesusingmagnetoresistanceeffectforneuromorphiccomputing AT yinlifeng distinguishingartificialspinicestatesusingmagnetoresistanceeffectforneuromorphiccomputing AT liuqi distinguishingartificialspinicestatesusingmagnetoresistanceeffectforneuromorphiccomputing AT shenjian distinguishingartificialspinicestatesusingmagnetoresistanceeffectforneuromorphiccomputing |