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用于中红外高光谱成像的表面等离激元-声子

Surface plasmons-phonons for mid-infrared hyperspectral imaging.

作者信息

Zhou Hong, Li Dongxiao, Ren Zhihao, Xu Cheng, Wang Lin-Fa, Lee Chengkuo

机构信息

Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore.

Center for Intelligent Sensors and MEMS (CISM), National University of Singapore, Singapore 117583, Singapore.

出版信息

Sci Adv. 2024 May 31;10(22):eado3179. doi: 10.1126/sciadv.ado3179. Epub 2024 May 29.

Abstract

Surface plasmons have proven their ability to boost the sensitivity of mid-infrared hyperspectral imaging by enhancing light-matter interactions. Surface phonons, a counterpart technology to plasmons, present unclear contributions to hyperspectral imaging. Here, we investigate this by developing a plasmon-phonon hyperspectral imaging system that uses asymmetric cross-shaped nanoantennas composed of stacked plasmon-phonon materials. The phonon modes within this system, controlled by light polarization, capture molecular refractive index intensity and lineshape features, distinct from those observed with plasmons, enabling more precise and sensitive molecule identification. In a deep learning-assisted imaging demonstration of severe acute respiratory syndrome coronavirus (SARS-CoV), phonons exhibit enhanced identification capabilities (230,400 spectra/s), facilitating the de-overlapping and observation of the spatial distribution of two mixed SARS-CoV spike proteins. In addition, the plasmon-phonon system demonstrates increased identification accuracy (93%), heightened sensitivity, and enhanced detection limits (down to molecule monolayers). These findings extend phonon polaritonics to hyperspectral imaging, promising applications in imaging-guided molecule screening and pharmaceutical analysis.

摘要

表面等离子体激元已通过增强光与物质的相互作用,证明了其提高中红外高光谱成像灵敏度的能力。表面声子作为等离子体激元的一种对应技术,对高光谱成像的贡献尚不清楚。在此,我们通过开发一种等离子体激元-声子高光谱成像系统来对此进行研究,该系统使用由堆叠的等离子体激元-声子材料组成的不对称十字形纳米天线。该系统内的声子模式受光偏振控制,可捕获分子折射率强度和线形特征,这与等离子体激元所观察到的不同,从而能够更精确、灵敏地识别分子。在严重急性呼吸综合征冠状病毒(SARS-CoV)的深度学习辅助成像演示中,声子展现出增强的识别能力(230400光谱/秒),有助于对两种混合的SARS-CoV刺突蛋白的空间分布进行去重叠和观察。此外,等离子体激元-声子系统展示出更高的识别准确率(93%)、更高的灵敏度以及更低的检测限(低至分子单层)。这些发现将声子极化激元学扩展至高光谱成像领域,有望应用于成像引导的分子筛选和药物分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0675/11135386/7c997f7231e3/sciadv.ado3179-f1.jpg

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