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Wavelength-multiplexed hook nanoantennas for machine learning enabled mid-infrared spectroscopy

Author

Listed:
  • Zhihao Ren

    (National University of Singapore
    National University of Singapore
    NUS Suzhou Research Institute (NUSRI))

  • Zixuan Zhang

    (National University of Singapore
    National University of Singapore
    NUS Suzhou Research Institute (NUSRI))

  • Jingxuan Wei

    (National University of Singapore
    National University of Singapore
    NUS Suzhou Research Institute (NUSRI))

  • Bowei Dong

    (National University of Singapore
    National University of Singapore
    NUS Suzhou Research Institute (NUSRI))

  • Chengkuo Lee

    (National University of Singapore
    National University of Singapore
    NUS Suzhou Research Institute (NUSRI)
    National University of Singapore)

Abstract

Infrared (IR) plasmonic nanoantennas (PNAs) are powerful tools to identify molecules by the IR fingerprint absorption from plasmon-molecules interaction. However, the sensitivity and bandwidth of PNAs are limited by the small overlap between molecules and sensing hotspots and the sharp plasmonic resonance peaks. In addition to intuitive methods like enhancement of electric field of PNAs and enrichment of molecules on PNAs surfaces, we propose a loss engineering method to optimize damping rate by reducing radiative loss using hook nanoantennas (HNAs). Furthermore, with the spectral multiplexing of the HNAs from gradient dimension, the wavelength-multiplexed HNAs (WMHNAs) serve as ultrasensitive vibrational probes in a continuous ultra-broadband region (wavelengths from 6 μm to 9 μm). Leveraging the multi-dimensional features captured by WMHNA, we develop a machine learning method to extract complementary physical and chemical information from molecules. The proof-of-concept demonstration of molecular recognition from mixed alcohols (methanol, ethanol, and isopropanol) shows 100% identification accuracy from the microfluidic integrated WMHNAs. Our work brings another degree of freedom to optimize PNAs towards small-volume, real-time, label-free molecular recognition from various species in low concentrations for chemical and biological diagnostics.

Suggested Citation

  • Zhihao Ren & Zixuan Zhang & Jingxuan Wei & Bowei Dong & Chengkuo Lee, 2022. "Wavelength-multiplexed hook nanoantennas for machine learning enabled mid-infrared spectroscopy," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-31520-z
    DOI: 10.1038/s41467-022-31520-z
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    References listed on IDEAS

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    Cited by:

    1. Laura Paggi & Alice Fabas & Hasnaa El Ouazzani & Jean-Paul Hugonin & Nikos Fayard & Nathalie Bardou & Christophe Dupuis & Jean-Jacques Greffet & Patrick Bouchon, 2023. "Over-coupled resonator for broadband surface enhanced infrared absorption (SEIRA)," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    2. Hong Zhou & Zhihao Ren & Dongxiao Li & Cheng Xu & Xiaojing Mu & Chengkuo Lee, 2023. "Dynamic construction of refractive index-dependent vibrations using surface plasmon-phonon polaritons," Nature Communications, Nature, vol. 14(1), pages 1-12, December.

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