基于二维材料的忆阻器中的随机共振

IF 9.1 2区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
J. B. Roldán, A. Cantudo, J. J. Torres, D. Maldonado, Yaqing Shen, Wenwen Zheng, Yue Yuan, M. Lanza
{"title":"基于二维材料的忆阻器中的随机共振","authors":"J. B. Roldán, A. Cantudo, J. J. Torres, D. Maldonado, Yaqing Shen, Wenwen Zheng, Yue Yuan, M. Lanza","doi":"10.1038/s41699-024-00444-1","DOIUrl":null,"url":null,"abstract":"Stochastic resonance is an essential phenomenon in neurobiology, it is connected to the constructive role of noise in the signals that take place in neuronal tissues, facilitating information communication, memory, etc. Memristive devices are known to be the cornerstone of hardware neuromorphic applications since they correctly mimic biological synapses in many different facets, such as short/long-term plasticity, spike-timing-dependent plasticity, pair-pulse facilitation, etc. Different types of neural networks can be built with circuit architectures based on memristive devices (mostly spiking neural networks and artificial neural networks). In this context, stochastic resonance is a critical issue to analyze in the memristive devices that will allow the fabrication of neuromorphic circuits. We do so here with h-BN based memristive devices from different perspectives. It is found that the devices we have fabricated and measured clearly show stochastic resonance behaviour. Consequently, neuromorphic applications can be developed to account for this effect, that describes a key issue in neurobiology with strong computational implications.","PeriodicalId":19227,"journal":{"name":"npj 2D Materials and Applications","volume":" ","pages":"1-6"},"PeriodicalIF":9.1000,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41699-024-00444-1.pdf","citationCount":"0","resultStr":"{\"title\":\"Stochastic resonance in 2D materials based memristors\",\"authors\":\"J. B. Roldán, A. Cantudo, J. J. Torres, D. Maldonado, Yaqing Shen, Wenwen Zheng, Yue Yuan, M. Lanza\",\"doi\":\"10.1038/s41699-024-00444-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Stochastic resonance is an essential phenomenon in neurobiology, it is connected to the constructive role of noise in the signals that take place in neuronal tissues, facilitating information communication, memory, etc. Memristive devices are known to be the cornerstone of hardware neuromorphic applications since they correctly mimic biological synapses in many different facets, such as short/long-term plasticity, spike-timing-dependent plasticity, pair-pulse facilitation, etc. Different types of neural networks can be built with circuit architectures based on memristive devices (mostly spiking neural networks and artificial neural networks). In this context, stochastic resonance is a critical issue to analyze in the memristive devices that will allow the fabrication of neuromorphic circuits. We do so here with h-BN based memristive devices from different perspectives. It is found that the devices we have fabricated and measured clearly show stochastic resonance behaviour. Consequently, neuromorphic applications can be developed to account for this effect, that describes a key issue in neurobiology with strong computational implications.\",\"PeriodicalId\":19227,\"journal\":{\"name\":\"npj 2D Materials and Applications\",\"volume\":\" \",\"pages\":\"1-6\"},\"PeriodicalIF\":9.1000,\"publicationDate\":\"2024-01-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.nature.com/articles/s41699-024-00444-1.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"npj 2D Materials and Applications\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://www.nature.com/articles/s41699-024-00444-1\",\"RegionNum\":2,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj 2D Materials and Applications","FirstCategoryId":"88","ListUrlMain":"https://www.nature.com/articles/s41699-024-00444-1","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

随机共振是神经生物学中的一个重要现象,它与神经元组织中发生的信号中噪声的建设性作用有关,有利于信息交流和记忆等。众所周知,Memristive 设备是硬件神经形态应用的基石,因为它们能在许多不同方面正确模拟生物突触,如短期/长期可塑性、尖峰计时可塑性、成对脉冲促进等。基于记忆器件的电路架构可以构建不同类型的神经网络(主要是尖峰神经网络和人工神经网络)。在这种情况下,随机共振是分析可用于制造神经形态电路的忆阻器件的一个关键问题。在此,我们从不同角度对基于 h-BN 的忆阻器件进行了分析。结果发现,我们制造和测量的器件明显表现出随机共振行为。因此,我们可以开发神经形态应用来解释这种效应,它描述了神经生物学中的一个关键问题,具有很强的计算意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Stochastic resonance in 2D materials based memristors

Stochastic resonance in 2D materials based memristors
Stochastic resonance is an essential phenomenon in neurobiology, it is connected to the constructive role of noise in the signals that take place in neuronal tissues, facilitating information communication, memory, etc. Memristive devices are known to be the cornerstone of hardware neuromorphic applications since they correctly mimic biological synapses in many different facets, such as short/long-term plasticity, spike-timing-dependent plasticity, pair-pulse facilitation, etc. Different types of neural networks can be built with circuit architectures based on memristive devices (mostly spiking neural networks and artificial neural networks). In this context, stochastic resonance is a critical issue to analyze in the memristive devices that will allow the fabrication of neuromorphic circuits. We do so here with h-BN based memristive devices from different perspectives. It is found that the devices we have fabricated and measured clearly show stochastic resonance behaviour. Consequently, neuromorphic applications can be developed to account for this effect, that describes a key issue in neurobiology with strong computational implications.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
npj 2D Materials and Applications
npj 2D Materials and Applications Engineering-Mechanics of Materials
CiteScore
14.50
自引率
2.10%
发文量
80
审稿时长
15 weeks
期刊介绍: npj 2D Materials and Applications publishes papers on the fundamental behavior, synthesis, properties and applications of existing and emerging 2D materials. By selecting papers with the potential for impact, the journal aims to facilitate the transfer of the research of 2D materials into wide-ranging applications.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信