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Ultrasensitive Molecular Fingerprint Retrieval Using Strongly Detuned Overcoupled Plasmonic Nanoantennas
Edit Time:2024-03-05     View:

Tailoring light-matter interactions via plasmonic nanoantennas (PNAs) has emerged as a breakthrough technology for spectroscopic applications. The detuning between molecular vibrations and plasmonic resonances, as a fundamental and inevitable optical phenomenon in light-matter interactions, reduces the interaction efficiency, resulting in a weak molecule sensing signal at the strong detuning state. Research from College of Optoelectronic Engineering, Chongqing University demonstrated that the low interaction efficiency from detuning can be tackled by overcoupled PNAs (OC-PNAs) with a high ratio of the radiative to intrinsic loss rates, which can be used for ultrasensitive spectroscopy at strong plasmonic-molecular detuning.

 

 

 

Prof. Xiaojing Mu report in Advanced Materials that they proposed a design strategy for single-pixel modulation-free OC-PNAs based on loss engineering. In OC-PNAs, the ultrasensitive molecule signals are achieved within a wavelength detuning range of 248 cm−1, which is 173 cm−1 wider than previous works. Meanwhile, the OC-PNAs are immune to the distortion of molecular signals and maintain a lineshape consistent with the molecular signature fingerprint. This strategy allows a single device to enhance and capture the full and complex fingerprint vibrations in the mid-infrared range. In the proof-of-concept demonstration, 13 kinds of molecules with some vibration fingerprints strongly detuning by the OC-PNAs are identified with 100% accuracy with the assistance of machine-learning algorithms. This work gains new insights into detuning-state nanophotonics for potential applications including spectroscopy and sensors.

 

For more information about this research, see’ Ultrasensitive Molecular Fingerprint Retrieval Using Strongly Detuned Overcoupled Plasmonic Nanoantennas’, Dongxiao Li, Hong Zhou, Ziwei Chen, Zhihao Ren, Cheng Xu, Xianming He, Tao Liu, Xin Chen, He Huang, Chengkuo Lee, Xiaojing Mu. Advanced Materials, 2023, 2301787.

https://onlinelibrary.wiley.com/doi/abs/10.1002/adma.202301787

 

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