基于微谐振器的集成微波光子传感器

Xiaoyi Tian, Liwei Li, Linh Nguyen, Xiaoke Yi
{"title":"基于微谐振器的集成微波光子传感器","authors":"Xiaoyi Tian,&nbsp;Liwei Li,&nbsp;Linh Nguyen,&nbsp;Xiaoke Yi","doi":"10.1002/adsr.202300145","DOIUrl":null,"url":null,"abstract":"<p>Sensors stand as pivotal cornerstones of technology, driving progress across a spectrum of industries through their ability to precisely capture and interpret an extensive array of physical phenomena. Among these advancements, microwave photonic (MWP) sensing has emerged as a new sensing technique, elevating sensing speed and resolution for practical applications. Integrated MWP sensors exhibit unparalleled capabilities in ultra-sensitive, label-free nanoscale detection, offering the potential to synergize with advanced integration techniques for a compact footprint and versatile designs. This paper reviews and summarizes the development and recent advances in integrated MWP sensing, focusing on the schemes based on microresonators. The diverse array of existing schemes is systematically categorized, elucidating their operational principles and performance demonstration. Furthermore, the assistance of machine learning and deep learning in integrated MWP sensors is explored, highlighting the potential of intelligent sensing paradigms. Finally, current challenges and opportunities aimed at further advancing MWP sensors are discussed.</p>","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":"3 8","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.202300145","citationCount":"0","resultStr":"{\"title\":\"Integrated Microwave Photonic Sensors Based on Microresonators\",\"authors\":\"Xiaoyi Tian,&nbsp;Liwei Li,&nbsp;Linh Nguyen,&nbsp;Xiaoke Yi\",\"doi\":\"10.1002/adsr.202300145\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Sensors stand as pivotal cornerstones of technology, driving progress across a spectrum of industries through their ability to precisely capture and interpret an extensive array of physical phenomena. Among these advancements, microwave photonic (MWP) sensing has emerged as a new sensing technique, elevating sensing speed and resolution for practical applications. Integrated MWP sensors exhibit unparalleled capabilities in ultra-sensitive, label-free nanoscale detection, offering the potential to synergize with advanced integration techniques for a compact footprint and versatile designs. This paper reviews and summarizes the development and recent advances in integrated MWP sensing, focusing on the schemes based on microresonators. The diverse array of existing schemes is systematically categorized, elucidating their operational principles and performance demonstration. Furthermore, the assistance of machine learning and deep learning in integrated MWP sensors is explored, highlighting the potential of intelligent sensing paradigms. Finally, current challenges and opportunities aimed at further advancing MWP sensors are discussed.</p>\",\"PeriodicalId\":100037,\"journal\":{\"name\":\"Advanced Sensor Research\",\"volume\":\"3 8\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.202300145\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Sensor Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/adsr.202300145\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Sensor Research","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/adsr.202300145","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

传感器是技术的重要基石,通过其精确捕捉和解释大量物理现象的能力,推动着各行各业的进步。在这些进步中,微波光子(MWP)传感已成为一种新的传感技术,提高了实际应用中的传感速度和分辨率。集成式 MWP 传感器在超灵敏、无标记纳米级检测方面具有无与伦比的能力,可与先进的集成技术协同作用,实现紧凑的占地面积和多功能设计。本文回顾并总结了集成式 MWP 传感技术的发展和最新进展,重点是基于微谐振器的方案。本文对现有的各种方案进行了系统分类,阐明了它们的工作原理和性能演示。此外,还探讨了机器学习和深度学习对集成式 MWP 传感器的帮助,突出了智能传感范例的潜力。最后,还讨论了当前的挑战和机遇,旨在进一步推动 MWP 传感器的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Integrated Microwave Photonic Sensors Based on Microresonators

Sensors stand as pivotal cornerstones of technology, driving progress across a spectrum of industries through their ability to precisely capture and interpret an extensive array of physical phenomena. Among these advancements, microwave photonic (MWP) sensing has emerged as a new sensing technique, elevating sensing speed and resolution for practical applications. Integrated MWP sensors exhibit unparalleled capabilities in ultra-sensitive, label-free nanoscale detection, offering the potential to synergize with advanced integration techniques for a compact footprint and versatile designs. This paper reviews and summarizes the development and recent advances in integrated MWP sensing, focusing on the schemes based on microresonators. The diverse array of existing schemes is systematically categorized, elucidating their operational principles and performance demonstration. Furthermore, the assistance of machine learning and deep learning in integrated MWP sensors is explored, highlighting the potential of intelligent sensing paradigms. Finally, current challenges and opportunities aimed at further advancing MWP sensors are discussed.

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
自引率
0.00%
发文量
0
期刊最新文献
Transforming Renal Diagnosis: Graphene-Enhanced Lab-On-a-Chip for Multiplexed Kidney Biomarker Detection in Capillary Blood (Adv. Sensor Res. 11/2024) Masthead (Adv. Sensor Res. 11/2024) All Solid Photonic Crystal Fiber Enabled by 3D Printing Fiber Technology for Sensing of Multiple Parameters (Adv. Sensor Res. 11/2024) Design Approaches and Electromechanical Modeling of Conformable Piezoelectric-Based Ultrasound Systems (Adv. Sensor Res. 10/2024) Masthead (Adv. Sensor Res. 10/2024)
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1