Temperature-dependent behavior of VO2-based artificial neurons

IF 3.5 2区物理与天体物理 Q2 PHYSICS, APPLIED Applied Physics Letters Pub Date : 2024-11-22 DOI:10.1063/5.0231840

Tiancheng Zhao, Yuan Xu, Jiacheng Liu, Xiang Bao, Liu Yuan, Deen Gu

{"title":"Temperature-dependent behavior of VO2-based artificial neurons","authors":"Tiancheng Zhao, Yuan Xu, Jiacheng Liu, Xiang Bao, Liu Yuan, Deen Gu","doi":"10.1063/5.0231840","DOIUrl":null,"url":null,"abstract":"Temperature serves as a pivotal factor influencing information transmission and computational capacity in neurons, significantly affecting the function and efficiency of neural networks. However, the temperature dependence of VO2-based artificial neuron, which is one of the highly promising artificial neurons, has been hardly reported to date. Here, high-performance VO2 devices with NDR features are prepared by rapid annealing and electroforming processes. We constructed VO2-based artificial neurons with output properties similar to those of biological neurons on the basis of the Pearson–Anson oscillation circuit. The temperature-dependent behavior of VO2 neurons was fully investigated. Increasing temperature leads to a decrease in the peak-to-peak value of the output spikes of VO2 neurons. The spike period of VO2 neurons remains relatively stable near room temperature, but it decreases as the temperature reaches above 26 °C. These temperature-dependent features of VO2 neurons are similar to the ones of biological neurons, suggesting a natural advantage of VO2-based artificial neurons in mimicking biological neural activity. These findings contribute toward comprehending and regulating the temperature-dependent behavior of artificial neurons based on Mott memristor.","PeriodicalId":8094,"journal":{"name":"Applied Physics Letters","volume":"34 1","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Physics Letters","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1063/5.0231840","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHYSICS, APPLIED","Score":null,"Total":0}

引用次数: 0

Abstract

Temperature serves as a pivotal factor influencing information transmission and computational capacity in neurons, significantly affecting the function and efficiency of neural networks. However, the temperature dependence of VO2-based artificial neuron, which is one of the highly promising artificial neurons, has been hardly reported to date. Here, high-performance VO2 devices with NDR features are prepared by rapid annealing and electroforming processes. We constructed VO2-based artificial neurons with output properties similar to those of biological neurons on the basis of the Pearson–Anson oscillation circuit. The temperature-dependent behavior of VO2 neurons was fully investigated. Increasing temperature leads to a decrease in the peak-to-peak value of the output spikes of VO2 neurons. The spike period of VO2 neurons remains relatively stable near room temperature, but it decreases as the temperature reaches above 26 °C. These temperature-dependent features of VO2 neurons are similar to the ones of biological neurons, suggesting a natural advantage of VO2-based artificial neurons in mimicking biological neural activity. These findings contribute toward comprehending and regulating the temperature-dependent behavior of artificial neurons based on Mott memristor.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

基于 VO2 的人工神经元随温度变化的行为

温度是影响神经元信息传输和计算能力的关键因素，对神经网络的功能和效率有着重要影响。然而，作为极具发展前景的人工神经元之一，基于 VO2 的人工神经元的温度依赖性迄今鲜有报道。本文通过快速退火和电铸工艺制备了具有 NDR 特性的高性能 VO2 器件。我们以 Pearson-Anson 振荡电路为基础，构建了具有与生物神经元相似输出特性的基于 VO2 的人工神经元。我们充分研究了 VO2 神经元随温度变化的行为。温度升高导致 VO2 神经元输出尖峰的峰峰值降低。VO2 神经元的尖峰周期在室温附近保持相对稳定，但当温度超过 26 °C 时，尖峰周期会缩短。VO2神经元的这些随温度变化而变化的特征与生物神经元相似，表明基于VO2的人工神经元在模拟生物神经活动方面具有天然优势。这些发现有助于理解和调节基于莫特忆阻器的人工神经元的温度依赖行为。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Applied Physics Letters 物理-物理：应用

CiteScore

6.40

自引率

10.00%

发文量

1821

审稿时长

1.6 months

期刊介绍： Applied Physics Letters (APL) features concise, up-to-date reports on significant new findings in applied physics. Emphasizing rapid dissemination of key data and new physical insights, APL offers prompt publication of new experimental and theoretical papers reporting applications of physics phenomena to all branches of science, engineering, and modern technology. In addition to regular articles, the journal also publishes invited Fast Track, Perspectives, and in-depth Editorials which report on cutting-edge areas in applied physics. APL Perspectives are forward-looking invited letters which highlight recent developments or discoveries. Emphasis is placed on very recent developments, potentially disruptive technologies, open questions and possible solutions. They also include a mini-roadmap detailing where the community should direct efforts in order for the phenomena to be viable for application and the challenges associated with meeting that performance threshold. Perspectives are characterized by personal viewpoints and opinions of recognized experts in the field. Fast Track articles are invited original research articles that report results that are particularly novel and important or provide a significant advancement in an emerging field. Because of the urgency and scientific importance of the work, the peer review process is accelerated. If, during the review process, it becomes apparent that the paper does not meet the Fast Track criterion, it is returned to a normal track.