Resonant Metasurfaces for Spectroscopic Detection: Physics and Biomedical Applications

超材料 等离子体子 拉曼散射 小型化 散射 太赫兹辐射 纳米技术 材料科学 电介质 光电子学 光学 物理 拉曼光谱
作者
Cuiping Liang,Jiajie Lai,Shaozhen Lou,Huigao Duan,Yueqiang Hu
出处
期刊:Advanced devices & instrumentation [AAAS00]
卷期号:2022 被引量:12
标识
DOI:10.34133/2022/9874607
摘要

Metasurfaces are ultrathin metamaterials consisting of subwavelength scatterers (e.g., meta-atoms) arranged in a specific sequence that generates low radiation losses and fantastic optical resonances. According to the electromagnetic response properties, metasurfaces can be divided into two categories: metallic nanostructures based on the response of plasmonic excitations (e.g., noble metals and graphene) and all-dielectric nanostructures based on near-field scattering (e.g., Mie scattering). Metasurfaces supporting various optical modes possess optical localization and electromagnetic field enhancement capabilities on the subwavelength scale, making them a promising platform for label-free detection in biomedical sensing. Metasurface-based optical sensors offer several outstanding advantages over conventional spectroscopic detection solutions, such as planar structures, low loss, miniaturization, and integration. Recently, novel sensing and even imaging tools based on metasurfaces have widely loomed and been proposed. Given recent advances in the field of metasurface spectroscopic detection, this review briefly summarizes the main resonance mechanisms of metasurfaces and the notable achievements, including refractive index sensing, surface-enhanced Raman scattering, surface-enhanced infrared absorption, and chiral sensing in the ultraviolet to terahertz wavelengths. Ultimately, we draw a summary of the current challenges of metasurface spectroscopic detection and look forward to future directions for improving these techniques. As the subject is broad and growing, our review will not be comprehensive. Nevertheless, we will endeavor to describe the main research in this area and assess some of the relevant literature.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
愚者先生关注了科研通微信公众号
1秒前
渡边卯卯发布了新的文献求助10
1秒前
play6761发布了新的文献求助10
1秒前
小太阳发布了新的文献求助30
1秒前
3秒前
水泥完成签到,获得积分10
3秒前
雨晴发布了新的文献求助10
3秒前
4秒前
4秒前
5秒前
5秒前
5秒前
科研通AI2S应助韩靖仇采纳,获得10
5秒前
5秒前
黄辉冯完成签到,获得积分10
6秒前
虚心碧发布了新的文献求助10
6秒前
lxx完成签到,获得积分20
7秒前
hhhhhhl完成签到,获得积分20
7秒前
7秒前
7秒前
11点睡觉完成签到,获得积分20
8秒前
yangmanjuan完成签到,获得积分10
8秒前
9秒前
huk发布了新的文献求助10
9秒前
9秒前
彭dada完成签到,获得积分10
9秒前
dc发布了新的文献求助10
9秒前
Yihong发布了新的文献求助10
9秒前
蓝天发布了新的文献求助10
10秒前
10秒前
12秒前
852应助凤梨爱好者采纳,获得10
12秒前
senl完成签到 ,获得积分10
12秒前
psen3发布了新的文献求助10
13秒前
牧绯完成签到,获得积分10
13秒前
52hezi发布了新的文献求助10
13秒前
闲人小年发布了新的文献求助10
13秒前
13秒前
科研通AI6.3应助黑眼圈采纳,获得10
13秒前
三千完成签到,获得积分10
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Picture this! Including first nations fiction picture books in school library collections 2000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1500
Cowries - A Guide to the Gastropod Family Cypraeidae 1200
ON THE THEORY OF BIRATIONAL BLOWING-UP 666
Signals, Systems, and Signal Processing 610
“美军军官队伍建设研究”系列(全册) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6385775
求助须知:如何正确求助?哪些是违规求助? 8199400
关于积分的说明 17343740
捐赠科研通 5439340
什么是DOI,文献DOI怎么找? 2876662
邀请新用户注册赠送积分活动 1853035
关于科研通互助平台的介绍 1697253