Resolving molecule-specific information in dynamic lipid membrane processes with multi-resonant infrared metasurfaces

A multitude of biological processes are enabled by complex interactions between lipid membranes and proteins. To understand such dynamic processes, it is crucial to differentiate the constituent biomolecular species and track their individual time evolution without invasive labels. Here, we present a label-free mid-infrared biosensor capable of distinguishing multiple analytes in heterogeneous biological samples with high sensitivity. Our technology leverages a multi-resonant metasurface to simultaneously enhance the different vibrational fingerprints of multiple biomolecules. By providing up to 1000-fold near-field intensity enhancement over both amide and methylene bands, our sensor resolves the interactions of lipid membranes with different polypeptides in real time. Significantly, we demonstrate that our label-free chemically specific sensor can analyze peptide-induced neurotransmitter cargo release from synaptic vesicle mimics. Our sensor opens up exciting possibilities for gaining new insights into biological processes such as signaling or transport in basic research as well as provides a valuable toolkit for bioanalytical and pharmaceutical applications

Quantifying the Limits of Detection of Surface-Enhanced Infrared Spectroscopy with Grating Order-Coupled Nanogap Antennas

Infrared spectroscopy is widely used for biomolecular studies, but struggles when investigating minute quantities of analytes due to the mismatch between vibrational cross sections and IR wavelengths. It is therefore beneficial to enhance absorption signals by confining the infrared light to deeply subwavelength volumes comparable in size to the biomolecules of interest. This can be achieved with surface-enhanced infrared absorption spectroscopy, for which plasmonic nanorod antennas represent the predominant implementation. However, unifying design guidelines for such systems are still lacking. Here, we introduce an experimentally verified framework for designing antenna-based molecular IR spectroscopy sensors. Specifically, we find that in order to maximize the sensing performance, it is essential to combine the signal enhancement originating from nanoscale gaps between the antenna elements with the enhancement obtained from coupling to the grating order modes of the unit cell. Using an optimized grating order-coupled nanogap design, our experiments and numerical simulations show a hotspot limit of detection of two proteins per nanogap. Furthermore, we introduce and analyze additional limit of detection parameters, specifically for deposited surface mass, in-solution concentration, and secondary structure determination. These limits of detection provide valuable reference points for performance metrics of surface-enhanced infrared absorption spectroscopy in practical applications, such as the characterization of biological samples in aqueous solution

Infrared Metasurface Augmented by Deep Learning for Monitoring Dynamics between All Major Classes of Biomolecules

Insights into the fascinating molecular world of biological processes are crucial for understanding diseases, developing diagnostics, and effective therapeutics. These processes are complex as they involve interactions between four major classes of biomolecules, i.e., proteins, nucleic acids, carbohydrates, and lipids, which makes it important to be able to discriminate between all these different biomolecular species. In this work, a deep learning-augmented, chemically-specific nanoplasmonic technique that enables such a feat in a label-free manner to not disrupt native processes is presented. The method uses a highly sensitive multiresonant plasmonic metasurface in a microfluidic device, which enhances infrared absorption across a broadband mid-IR spectrum and in water, despite its strongly overlapping absorption bands. The real-time format of the optofluidic method enables the collection of a vast amount of spectrotemporal data, which allows the construction of a deep neural network to discriminate accurately between all major classes of biomolecules. The capabilities of the new method are demonstrated by monitoring of a multistep bioassay containing sucrose- and nucleotides-loaded liposomes interacting with a small, lipid membrane-perforating peptide. It is envisioned that the presented technology will impact the fields of biology, bioanalytics, and pharmacology from fundamental research and disease diagnostics to drug development

Self-Similar Multiresonant Nanoantenna Arrays for Sensing from Near- to Mid-Infrared

Tailoring nanoscale light concentration and electromagnetic near-field enhancement over a broad spectral range is crucial for many photonics applications such as infrared spectroscopy, photodetection, and light harvesting. So far, broadband light enhancement has faced significant challenges due to the difficulty of efficiently exciting resonances at spectrally separated wavelengths and the inability of current devices to individually tune each specific resonance. Here, we introduce a multiresonant structure based on the non-overlapping combination of plasmonic nano antenna arrays with multiple periodicities. The self-similarity of the multiperiodic array, obtained by a fractal-like generation procedure, enables the excitation of a high number of resonances without compromising their excitation efficiency. We experimentally demonstrate devices with up to four independent resonances covering an unprecedentedly wide spectral range from 10 to 1.5 mu m. Significantly, the reflectance signal is uniformly strong for all the resonances, reaching more than 70% amplitude and near-field intensity enhancements above 1000. We further show that each individual resonance wavelength can be independently controlled over a 50% spectral range by modifying a single geometrical antenna parameter, providing superior flexibility in tailoring the overall spectral response. Due to the self-similar layout and independent resonances, our design is well described by temporal coupled-mode theory, allowing for a straightforward extension for other nanophotonic applications. Finally, we demonstrate that the wide spectral coverage of our design enables a unique sensing method by simultaneously performing chemically specific mid-infrared detection and near infrared refractometry

Metasurface-Based Molecular Biosensing Aided by Artificial Intelligence

Molecular spectroscopy provides unique information on the internal structure of biological materials by detecting the characteristic vibrational signatures of their constituent chemical bonds at infrared frequencies. Nanophotonic antennas and metasurfaces have driven this concept towards few-molecule sensitivity by confining incident light into intense hot spots of the electromagnetic fields, providing strongly enhanced light-matter interaction. In this Minireview, recently developed molecular biosensing approaches based on the combination of dielectric metasurfaces and imaging detection are highlighted in comparison to traditional plasmonic geometries, and the unique potential of artificial intelligence techniques for nanophotonic sensor design and data analysis is emphasized. Because of their spectrometer-less operation principle, such imaging-based approaches hold great promise for miniaturized biosensors in practical point-of-care or field-deployable applications

Metasurface-Enhanced Infrared Spectroscopy: An Abundance of Materials and Functionalities

Infrared spectroscopy provides unique information on the composition and dynamics of biochemical systems by resolving the characteristic absorption fingerprints of their constituent molecules. Based on this inherent chemical specificity and the capability for label-free, noninvasive, and real-time detection, infrared spectroscopy approaches have unlocked a plethora of breakthrough applications for fields ranging from environmental monitoring and defense to chemical analysis and medical diagnostics. Nanophotonics has played a crucial role for pushing the sensitivity limits of traditional far-field spectroscopy by using resonant nanostructures to focus the incident light into nanoscale hot-spots of the electromagnetic field, greatly enhancing light-matter interaction. Metasurfaces composed of regular arrangements of such resonators further increase the design space for tailoring this nanoscale light control both spectrally and spatially, which has established them as an invaluable toolkit for surface-enhanced spectroscopy. Starting from the fundamental concepts of metasurface-enhanced infrared spectroscopy, a broad palette of resonator geometries, materials, and arrangements for realizing highly sensitive metadevices is showcased, with a special focus on emerging systems such as phononic and 2D van der Waals materials, and integration with waveguides for lab-on-a-chip devices. Furthermore, advanced sensor functionalities of metasurface-based infrared spectroscopy, including multiresonance, tunability, dielectrophoresis, live cell sensing, and machine-learning-aided analysis are highlighted

Antenna-coupled infrared nanospectroscopy of intramolecular vibrational interaction

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Highly-Selective Optoelectronic Nose Based on Surface Plasmon Resonance Imaging for Sensing Volatile Organic Compounds

International audienceMonitoring volatile organic compounds (VOCs) is an important issue, but difficult to achieve on a large scale and on the field using conventional analytical methods. Electronic noses (eNs), as promising alternatives, are still compromised by their performances due to the fact that most of them rely on a very limited number of sensors and use databases devoid of kinetic information. To narrow the performance gap between human and electronic noses, we developed a novel optoelectronic nose, which features a large sensor microarray that enables multiplexed monitoring of binding events in real-time with a temporal response. For the first time, surface plasmon resonance imaging is demonstrated as a promising novel analytical tool for VOC detection in the gas phase. By combining it with cross-reactive sensor microarrays, the obtained optoelectronic nose shows a remarkably high selectivity, capable of discriminating between homologous VOCs differing by only a single carbon atom. In addition, the optoelectronic nose has good repeatability and stability. Finally, the preliminary assays using VOC binary and ternary mixtures show that it is also very efficient for the analysis of more complex samples, opening up the exciting perspective of applying it to “real-world” samples in diverse domains

High-contrast infrared absorption spectroscopy via mass-produced coaxial zero-mode resonators with sub-10 nm gaps

We present a wafer-scale array of resonant coaxial nanoapertures as a practical platform for surface-enhanced infrared absorption spectroscopy (SEIRA). Coaxial nanoapertures with sub-10 nm gaps are fabricated via photolithography, atomic layer deposition of a sacrificial Al2O3 layer to define the nanogaps, and planarization via glancing-angle ion milling. At the zeroth-order Fabry-Pérot resonance condition, our coaxial apertures act as a "zero-mode resonator (ZMR)", efficiently funneling as much as 34% of incident infrared (IR) light along 10 nm annular gaps. After removing Al2O3 in the gaps and inserting silk protein, we can couple the intense optical fields of the annular nanogap into the vibrational modes of protein molecules. From 7 nm gap ZMR devices coated with a 5 nm thick silk protein film, we observe high-contrast IR absorbance signals drastically suppressing 58% of the transmitted light and infer a strong IR absorption enhancement factor of 104∼105. These single nanometer gap ZMR devices can be mass-produced via batch processing and offer promising routes for broad applications of SEIRA.This research was supported primarily by the U.S. National Science Foundation (ECCS 1610333 to D.Y. and S.-H.O.) and Seagate Technology (D.A.M. and S.-H.O.). D.A.M. acknowledges the National Institutes of Health Biotechnology Training Grant (NIH T32 GM008347). L.M.-M. acknowledge financial support by the Spanish MINECO under contract No. MAT2014-53432-C5. F.V.-C., N.C.N., and J.P. acknowledge support from the AFOSR Grant (FA9550-11-1-0141 and FA9550-12-0357). A.J-H. and H.A. acknowledge European Research Council Consolidator Grant (ERC-2015-CoG682167).Peer reviewe