Key Takeaways & Executive Findings
- •• Proposed a new paradigm for nanoantenna design using coupled-mode theory, enabling precise control of light–matter interactions. • Designed an OC-Hμ resonator with ultra-sensitive (7.25% nm−1) and ultra-broadband (3–10 μm) sensing performance, immune to asymmetric Fano lineshapes. • Demonstrated machine learning-assisted mixture classification, concentration prediction, and spectral reconstruction with up to 100% accuracy. • Showcased potential for SARS-CoV-2 detection, advancing SEIRA technology for biomolecule recognition and trace detection.
Abstract
Plasmonic nanoantennas provide unique opportunities for precise control of light–matter coupling in surface-enhanced infrared absorption (SEIRA) spectroscopy, but most of the resonant systems realized so far suffer from the obstacles of low sensitivity, narrow bandwidth, and asymmetric Fano resonance perturbations. Here, we demonstrated an overcoupled resonator with a high plasmon-molecule coupling coefficient (μ) (OC-Hμ resonator) by precisely controlling the radiation loss channel, the resonator-oscillator coupling channel, and the frequency detuning channel. We observed a strong dependence of the sensing performance on the coupling state, and demonstrated that OC-Hμ resonator has excellent sensing properties of ultra-sensitive (7.25% nm−1), ultra-broadband (3–10 μm), and immune asymmetric Fano lineshapes. These characteristics represent a breakthrough in SEIRA technology and lay the foundation for specific recognition of biomolecules, trace detection, and protein secondary structure analysis using a single array (array size is 100×100 µm2). In addition, with the assistance of machine learning, mixture classification, concentration prediction and spectral reconstruction were achieved with the highest accuracy of 100%. Finally, we demonstrated the potential of OC-Hμ resonator for SARS-CoV-2 detection. These findings will promote the wider application of SEIRA technology, while providing new ideas for other enhanced spectroscopy technologies, quantum photonics and studying light–matter interactions.
1. Introduction
Maximizing tailored light–matter interactions in nanoscale materials is a central goal of nanophotonics [1]. Resonant nanosystems have been demonstrated for the confinement and control of electromagnetic energy in subwavelength volumes, providing unique opportunities for enhanced light–matter interactions [2]. Based on this property of nanophotonics, many applications have been demonstrated, including enhanced spectroscopy [3–5], nonlinear optics [6], plasmon catalysis [7], quantum optics [8] and nanolasers [9]. Among them, surface-enhanced infrared absorption (SEIRA) spectroscopy is more attractive [10, 11]. This is because the mid-infrared spectrum contains infrared vibrational fingerprints of various biochemical molecules, which are related to molecular composition, chemical bonds, and inherent configurations. The emergence of nanophotonics has solved the limitation of low sensitivity of infrared in detecting trace molecules or ultra-thin film systems [12–15]. SEIRA spectroscopy has made significant progress recently and has achieved molecular dynamic monitoring [16–19], hyperspectral imaging [20–24], and biochemical molecule detection [25–27], showing a wide range of application potential. Despite significant progress in controlling the spectral composition of light–matter interactions, several thorny issues have hindered widespread application of this technology.
Low sensitivity, narrow bandwidth, and asymmetric Fano resonance are the three main obstacles restricting the wide application of SEIRA [28–31]. Among them, low sensitivity leads to unsound value of the limit of detection (LOD). Narrow bandwidth affects the versatility of individual devices [31]. The asymmetric Fano resonance hinders the direct acquisition of molecular fingerprint vibration information [30]. Huge efforts have been made to solve the above problems. First, a series of strategies, such as utilizing nanogaps [28, 32, 33], molecular enrichment [27, 34], and bound states in the continuum (BIC) [20], have been proposed to improve the sensitivity of SEIRA. Second, methods such as multiresonance [17, 35, 36], supercell [31], array [20], modulation [25, 37] and gradient metasurfaces [38, 39] were used to collect broadband spectral data. In terms of weakening asymmetric Fano resonance, methods such as broadband [31], envelope [20, 40–42] or secondary calibration [43] have been proposed to restore the natural absorption fingerprint of molecules. While the above approaches all address one or two of the obstacles to some extent, simultaneously addressing all three of the above obstacles using a single array device remains a huge challenge. Solving these three challenges simultaneously on a single array device facilitates smaller device size, higher integration, and broader applicability.
Recently, there has been widespread interest in exploring nanoantennas driven by physics to achieve exceptional sensing capabilities. This pursuit has led to the emergence of various novel resonance modes with high-performance sensing characteristics, such as Fano-resonant [26], BIC [20], exceptional points [44], a
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Dongxiao Li, Hong Zhou, Zhihao Ren, Cheng Xu, Chengkuo Lee (2024). Tailoring Light–Matter Interactions in Overcoupled Resonator for Biomolecule Recognition and Detection. Nano-Micro Letters. https://doi.org/10.1007/s40820-024-01520-3
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Frequently Asked Questions
What is the main innovation of this paper?
The paper proposes a new paradigm for nanoantenna design using coupled-mode theory, leading to an overcoupled resonator (OC-Hμ) that simultaneously achieves ultra-sensitivity, ultra-broadband operation, and immunity to asymmetric Fano resonance, addressing key limitations of SEIRA spectroscopy.
How does the OC-Hμ resonator improve sensing performance?
By precisely controlling radiation loss, resonator-oscillator coupling, and frequency detuning, the OC-Hμ resonator achieves a high plasmon-molecule coupling coefficient, resulting in ultra-sensitive (7.25% nm−1) and ultra-broadband (3–10 μm) detection with symmetric lineshapes.
What role does machine learning play in this study?
Machine learning is used to analyze spectral data from the OC-Hμ resonator, enabling mixture classification, concentration prediction, and spectral reconstruction with up to 100% accuracy, enhancing the practical utility of the sensor.
What are the potential applications of this technology?
The technology can be applied for specific biomolecule recognition, trace detection, protein secondary structure analysis, and even SARS-CoV-2 detection, with implications for enhanced spectroscopy, quantum photonics, and light-matter interaction studies.
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