Quantum plexcitonic biosensing and methods thereof

Abstract

A molecular sensing device and molecular sensing method that are based on quantum plexcitonic states on strongly coupled nanophotonic systems are disclosed. The molecular sensing device includes a metasurface, a layer of a semiconducting and / or dielectric material disposed onto a layer of electrically conducting material, a metal nanohole array disposed onto the metasurface, a biological recognition element disposed onto a surface of the metal nanohole array, and where the surface of the metal nanohole array is configured to receive a bioanalyte and a plurality of quantum emitters. The molecular sensing device can be a mixture of quantum emitters, comprising gold, having more than one aspect ratio. The molecular sensing device may include a spectroscopic instrument, including a portable detector. The one or more biological recognition elements are configured to recognize a communicable disease in response to the presence of a specific biological recognition element.

Description

Client Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT QUANTUM PLEXCITONIC BIOSENSING AND METHODS THEREOF CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application is an International Application which claims the benefit of U.S. Provisional Application No.63 / 504,516 filed on May 26, 2023, the disclosure of which is incorporated by reference herein in its entirety. TECHNICAL FIELD

[0002] The present teachings relate generally to biosensors and biosensing methods and, more particularly, to biosensors and biosensing methods based on quantum plexcitonic molecular sensing. BACKGROUND

[0001] Quantum sensing marks the next frontier in developing advanced analytical and metrology tools poised to be unparalleled with respect to their classical counterparts. Fundamental to quantum sensing are the formation, modulation, and readout of quantum states for a coherently coupled atom field system in response to a given input physical variable, such as electromagnetic (EM) field strength and analyte concentration. Traditionally, quantum state control has been limited to a high vacuum or an ultrastable mechanical and thermal environment. Such conditions are essential to maintaining quantum states by insulating them from environmental perturbations, but incompatible with practical implementation for a broad range of physical measurements.

[0002] One of the prevailing designs for optical biosensing is based on surface plasmon resonance (SPR) peak shifts. The mechanism for SPR sensors is based on an instant SPR peak shift caused by an analyte-induced perturbation to the local dielectric environment. The amount of shift scales linearly with the perturbation size, or equivalently the analyte concentration. Such a scaling law implies that the sensitivity is limited by the quality factor (or Q factor) of the plasmonic resonator, which is a measure of the strength of the damping of oscillations associated with the plasmonic resonator. This Q factor can influence or set a lower limit on the minimally resolvable peak shift.

[0003] Unfortunately, most plasmonic resonators inherently possess low Q factors owing to strong metal losses. The intrinsic shot noise, or fluctuations of classic light owing to its discreet particle nature further constrains the achievable sensitivity of such resonators. Moreover, SPRClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT sensors can be vulnerable to interference, particularly if the peak passively shifted by the local dielectric perturbation is blind to what causes the shift.

[0004] Therefore, it is desirable to provide biosensors and biosensing methods that overcome these deficiencies and provide sensitive, efficient, and accurate results in biosensing applications. SUMMARY

[0005] The following presents a simplified summary in order to provide a basic understanding of some aspects of one or more embodiments of the present teachings. This summary is not an extensive overview, nor is it intended to identify key or critical elements of the present teachings, nor to delineate the scope of the disclosure. Rather, its primary purpose is merely to present one or more concepts in simplified form as a prelude to the detailed description presented later.

[0006] A molecular sensing device is disclosed. The molecular sensing device also includes a metasurface, may include a layer of a semiconducting and / or dielectric material disposed onto a layer of electrically conducting material. The device also includes a metal nanohole array disposed onto the metasurface. The device also includes a biological recognition element disposed onto a surface of the metal nanohole array, and where the surface of the metal nanohole array is configured to receive a bioanalyte and a plurality of quantum emitters. Implementations of the molecular sensing device may include where the semiconducting and / or dielectric material includes silicon dioxide. The electrically conducting material may include silver. The metal nanohole array may include gold. The plurality of quantum emitters may include gold. The plurality of quantum emitters may include a mixture of gold nanorods. The plurality of quantum emitters may include more than one aspect ratio, such as from about 1.1 to about 10. The metasurface may include from about 2 to about 50 alternating layers of the semiconducting material and electrically conducting material. The metasurface may include more than one alternating layer of the semiconducting and / or dielectric material and electrically conducting material. The molecular sensing device may include a spectroscopic instrument. The molecular sensing device may include a portable detector. The biological recognition element is configured to recognize a communicable disease. The bioanalyte corresponds to a specific biological recognition element. The bioanalyte may include a biological medium.

[0007] A molecular sensing method is also disclosed. The molecular sensing method includes exposing a molecular sensing device to a sample. The molecular sensing method also includes subjecting the molecular sensing device to light, generating an electromagnetic signal from a reaction between the sample and a surface of the molecular sensing device. The molecular sensing method also includes analyzing the electromagnetic signal to determine the presence of aClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT target analyte in the sample. The molecular sensing method also includes analyzing the electromagnetic signal to determine a quantity of the target analyte in the sample. The molecular sensing method also includes transmitting presence of the target analyte and the quantity of the target analyte, and where the molecular sensing device may include a metasurface, may include a layer of a semiconducting and / or dielectric material disposed onto a layer of electrically conducting material, and a metal nanohole array disposed onto the metasurface. Implementations of the molecular sensing method may include introducing a biological recognition element disposed onto a surface of the metal nanohole array, where the biological recognition element reacts with the sample. The sample may include biological media. Transmitting the presence of the target analyte and the quantity of the target analyte may include a colorimetric and / or spectroscopical transmission. Transmitting presence of the target analyte and the quantity of the target analyte may include a digital transmission to a portable computer medium such as an electronic display, cell phone, tablet, mobile computer, or combination thereof.

[0008] The features, functions, and advantages that have been discussed can be achieved independently in various implementations or can be combined in yet other implementations further details of which can be seen with reference to the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the present teachings and together with the description, serve to explain the principles of the disclosure. In the figures:

[0010] FIG.1A depicts an energy diagram describing energy levels for newly formed plexcitonic states separated by Rabi splitting ΩR under strong coupling.

[0011] FIG.1B depicts a diagram describing spectral splitting under strong coupling.

[0012] FIG.1C depicts anticrossing of the two plexcitonic levels by tuning the transition frequency of the exciton.

[0013] FIGS.1D- 1F are schematic diagrams representing different scenarios of light−matter interactions in a plasmonic nanocavity. FIG.1D represents a single exciton strongly coupled with a plasmonic nanocavity with an ultrasmall mode volume Vm, FIG.1E represents an ensemble of N excitons strongly coupled with a plasmonic nanocavity, and FIG.1F represents N excitonic particles strongly coupled with a plasmonic nanocavity with an ultrasmall mode volume Vm.

[0014] FIG.1G-1I are plots representing analytical results for the following: FIG.1G is a plot representing coupling strength-dependent spectral splitting for a single exciton strongly coupledClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT with a plasmonic nanocavity as shown in FIG.1D; FIG.1H is a plot showing exciton population- dependent spectral splitting for an ensemble of N excitons strongly coupled with a plasmonic nanocavity as shown in FIG.1E. FIG.1I depicts plots of coupling strength g-dependent Rabi splitting ΩR (left) and exciton population N-dependent Rabi splitting (right), respectively.

[0015] FIG.2A is a Schematic of a plasmonic hyperbolic metamaterial platform consisting of a hexagonally patterned gold nanohole array sitting on alternatively stacked silica−silver thin films.

[0016] FIGS.2B and 2C are plots of calculated permittivity and isofrequency surface (IFS) at 681 nm, respectively, for the metasurface made of six cycles of alternatively stacked silica−silver thin films.

[0017] FIG.2D is a plot of angle-resolved reflection spectra for the metasurface as shown in FIG.2A.

[0018] FIG.2E is a plot of reflection spectrum under an incident angle of 45° extracted from the upper dashed line in FIG.2D.

[0019] FIG.2F is a cross-section and FIGS.2G-2I are different top views of the normalized electrical field distribution for the metasurface shown in FIG.2A at 681 nm, respectively.

[0020] FIG.3A is a schematic for a quantum plexcitonic sensing device featuring a microfluidic platform with the sensing area consisting of the plasmonic hyperbolic metamaterial platform as shown in FIG.2A.

[0021] FIG.3B shows a schematic process for functionalization of gold nanorods and the metamaterial platform with respective analyte-specific biological recognition elements, resulting in the gold nanorods being captured on the metamaterial platform in the presence of analytes.

[0022] FIG.4A is a heat map reconstructed from the calculated reflection spectra for quantum plexcitonic sensing using gold nanorods.

[0023] FIG.4B is a plot of Rabi splitting ΩRwith respect to the population of gold or silica nanorods NUC based on FIG. 4A.

[0024] FIG.4C is a plot representing evaluation of conventional sensitivity is based on the ratio of Rabi splitting ΩRrelative to the change in the population of gold or silica nanorods δNUC, where linear fitting is performed to obtain conventional sensitivity ΩR / δNUC for quantum sensing.

[0025] FIG.4D is a heat map reconstructed from the calculated reflection spectra for classical sensing based on a frequency shift using silica nanorods with the same dimension as gold nanorods.

[0026] FIG.4E is a plot of frequency shift δω with respect to the population of gold or silica nanorods NUC based on FIG. 4D.Client Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT

[0027] FIG.4F is a plot representing the evaluation of conventional sensitivity based on the ratio of frequency shift δω relative to the change in the population of gold or silica nanorods δNUC, where linear fitting is performed to obtain conventional sensitivity δω / δNUC for classical sensing.

[0028] FIGS.4G-4H are plots depicting an evaluation of quantum sensitivity by normalizing Rabi splitting ΩR and frequency shift δω with respect to the population of gold or silica nanorods NUC, where quantum sensitivity ΩR / NUC for quantum plexcitonic sensing is presented in FIG.4G and quantum sensitivity δω / NUC for classical sensing is shown in FIG. 4H.

[0029] FIG.4I is a plot of normalized quantum sensitivity ΓS by taking the ΩR / δω ratio, which quantifies the quantum sensitivity enhancement of quantum plexcitonic sensing compared to its classical counterpart.

[0030] FIG.5A is a power spectrum, normalized and converted from the reflection spectra in FIG.4A with a vertical offset for better visualization and having white noise (SNR = 5 dB) added to the quantum plexcitonic sensing power spectrum.

[0031] FIG.5B is a violin plot of quantum plexcitonic sensing, showing a significant difference in the NUC-dependent Rabi splittings.

[0032] FIG.5C is a plot depicting conventional sensitivity of 31.81 ± 0.33 meV obtained on the basis of linear regression analysis.

[0033] FIG.5D is a power spectra, normalized and converted from the reflection spectra in FIG. 4A with a vertical offset for better visualization and having white noise (SNR = 5 dB) added to the classical sensing power spectra.

[0034] FIG.5E, FIG.5F are violin plots depicting classical sensing of NUC-dependent frequency shifts for SNR=5 and SNR=8, respectively.

[0035] In contrast, in classical sensing, as shown in FIGS.5E and 5F the difference in the NUC- dependent frequency shifts is found to be not significant in the violin plot for SNR=5 for FIG.5E, only when SNR ≥ 8 dB, as shown in FIG.5F, does the difference in the NUC-dependent frequency shifts become gradually significant.

[0036] FIGS.5G and 5H are plots depicting comparisons of SNR-dependent conventional sensitivity data between quantum plexcitonic sensing and classical sensing, respectively, where the shaded areas represent the absolute uncertainty of conventional sensitivity.

[0037] FIG.5I is a comparison plot of the SNR-dependent relative uncertainty of conventional sensitivity between quantum plexcitonic sensing and classical sensing, where the relative uncertainty is defined as the percentage ratio of the absolute uncertainty to the mean sensitivity.Client Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT

[0038] FIG.5J and 5K are plots comparing SNR- and NUC-dependent quantum sensitivity between quantum plexcitonic sensing and classical sensing, respectively, where the shaded areas represent the absolute uncertainly of quantum sensitivity.

[0039] FIG.5L is a comparison plot of the SNR- and NUC-dependent relative uncertainty of quantum sensitivity between quantum plexcitonic sensing and classical sensing, where the relative uncertainty is defined as the percentage ratio of the absolute uncertainty to the mean sensitivity.

[0040] FIG.6 is a flowchart illustrating a measurement method using quantum plexcitonic principles, in accordance with the present disclosure.

[0041] It should be noted that some details of the figures have been simplified and are drawn to facilitate understanding of the present teachings rather than to maintain strict structural accuracy, detail, and scale. DETAILED DESCRIPTION

[0042] Reference will now be made in detail to exemplary embodiments of the present teachings, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same, similar, or like parts.

[0043] With an origin in strong light−matter interactions, quantum plexcitons can provide a promising path toward quantum state control under ambient conditions, which can be potentially harnessed for developing quantum sensing technologies. Plexcitons are hybrid plasmon−exciton quasi-particles, formed under the strong coupling between plasmon and two-level quantum emitters (QEs), where the confined EM energy can dramatically augment the coupling strength through near field interactions to overcome energy loss rates. The ensuing large coupling-to-loss ratio is characteristic of and essential for strong coupling, making plexcitons robust against environmental perturbations; this behavior is in sharp contrast to the fragile quantum states of ultracold atoms, trapped ions, and superconducting qubits.

[0044] As plexcitonic states result from strong plasmon−exciton coupling, they can be modulated by varying their energy detuning and separation. The nature of the coherence of strong coupling suggests that the population of QEs can also modulate the coupling strength and thus be utilized for quantum state control.

[0045] For the purposes of the present disclosure, surface plasmon resonance (SPR) can be defined as a sensing technique that detects changes in the refractive index of the localClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT environment in the close proximity to a thin metallic film or other form. When light is shone on the metal, surface plasmons are excited, which are collective oscillations of electrons at a metal- dielectric interface. These can also be referred to as localized surface plasmon resonance (LSPR). Changes in the refractive index of the dielectric material near the metal surface cause changes in the resonant frequency of the surface plasmons, which can be detected and used to measure a concentration or binding of molecules on the surface. When metal nanoparticles are used, physical attributes of the metal nanoparticles, such as shape, size, or composition can influence the magnitude and spectral position of the SPR. In examples, the SPR frequency can be tuned or tailored by modification of the size, shape, and aspect ratio of the metal nanoparticles. Moreover, the strength of the SPR can be altered by the metal, the dielectric properties of surrounding medium, the size and shape of the nanoparticle, and other factors.

[0046] The shape of a metal nanoparticle can alter the localized surface plasmon resonance through electron confinement. For example, spherical gold nanoparticles have a well-defined plasmon resonance in the visible region, while rod-shaped gold nanoparticles exhibit widely tunable resonances from visible to near-infrared regions. It should be noted that triangular nanoparticles can also be used for sensing applications as the SPRs are sensitive to size and shape of the triangular nanoparticles. As the size of a nanoparticle decreases, the SPR peak can shift to an increased wavelength, which infers that as size decreases the nanoparticles can absorb and / or scatter near-infrared light, which can be utilized in biomedical imaging or sensing.

[0047] Quantum plexcitonic molecular sensing is a technique that combines plasmonics and quantum mechanics to provide highly sensitive molecular sensors. In this technique, a metallic plasmonic nanostructure is placed near an excitonic particle (including but not limited to a quantum dot), which creates a quasi-particle possessing the attributes of both light and matter, known as a plexciton. The presence of a molecule near the surface of the nanoparticle can perturb the plexciton, causing changes in its optical properties that can be detected. The combined technique has the potential for extremely high sensitivity and specificity, making it useful for a wide range of applications, including, but not limited to, medical diagnostics and environmental monitoring.

[0048] As most plasmonic resonators inherently possess low Q factors because of strong metal losses, which when combined with shot noise of light, the achievable sensitivity of plasmonic resonators can be constrained. Furthermore, sensors based on surface plasmon resonance can be subject to interference, particularly if the peak passively shifted by the local dielectric perturbation is blind to what causes the shift. In quantum plexcitonic molecular biosensing, biological molecules can be attached to the surface of a semiconductor-based material coated orClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT covered with a metal. When light is directed towards the surface, the plexcitons are excited, causing them to emit a measurable and detectable signal. The strength of the signal generated can provide detection of and determination of the presence and concentration of one or more biological molecules.

[0049] The present disclosure provides a solution for ultrasensitive, accurate, and multiplexed detection of a panel of analytes of interest by leveraging quantum plexcitonic effects. Devices and methods of the present disclosure can provide the development and utilization of diagnostic test kits that can deliver efficient and accurate results to guide early diagnosis of diseases and help combat epidemic outbreaks. Resultant diagnostic kits can be combined with portable, hand-held light sources and spectrometers for de-centralized and point-of-care disease detection and virus surveillance, providing substantial improvements to existing technologies. Quantum plexcitons can be used to create broadly generalizable methods for molecular sensing. The performance of such methods and devices can be significantly boosted by a doublet spectral peak shifting in opposite directions along with the compatibility with quantum state of light.

[0050] The present disclosure presents the concept that facile quantum state control can be employed as a novel method for developing quantum plexcitonic sensing technologies. An enabling component of the disclosed method and devices is the utilization of plexcitons to transduce the presence of the analyte into a signal that is manifested as spectral splitting. Conventionally, the surface plasmon resonance peak shift-based optical sensing is limited in the achievable sensitivity, as it is constrained by the quality factor of the plasmonic resonator, and in specificity, because the peak passively shifted by the local dielectric perturbation is blind to what caused it. In contrast, quantum plexcitonic sensing is built on strong light−matter interactions and promises ultrasensitivity and high specificity. Previous demonstrations of strong coupling with a single QE offer important insight into the prospect of leveraging quantum plexcitonic sensing to study single-molecule events that are often masked in ensemble measurements. As achieving strong coupling requires analytes or QEs to be spatially confined to the plasmonic mode volume and simultaneously spectrally overlapped with it, such stringent conditions ensure a high specificity and make it robust against environmental interference. Nevertheless, routine realization of plexcitons at the single-QE level remains a major hurdle, as common QEs lack the needed transition dipole moment to achieve strong coupling. Additionally, as the majority of analytes that need to be measured may not qualify as QEs, as they do not possess optical or electronic attributes that are essential for plexciton formation, new strategies are required to expand the applicability of quantum plexcitonic sensing for the measurement of a wider range of analytes that may or may not be modeled as a two-level QE.Client Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT

[0051] Driven by the unfulfilled promise of plexcitons, herein, informed by mechanistic principles that underpin the formation of plexcitons the present disclosure provides and three potential strategies toward realizing quantum plexcitonic sensing, which come with distinct requirements as well as associated levels of performance. The three potential strategies include (1) coupling a single exciton with a plasmonic nanocavity, (2) coupling a large population of excitons with a plasmonic nanocavity, and (3) modal strong coupling between a plasmonic nanocavity and plasmonic nanoparticles that serve as generalized excitonic particles. Of particular interest among them is the modal strong coupling. By employing as a plasmonic nanocavity a plasmonic hyperbolic metasurface that supports highly confined metamaterial modes, and through noise-modulated sensitivity studies based on Monte Carlo simulations, it can be numerically demonstrated that modal strong coupling-enabled quantum plexcitonic sensing not only far outperforms classical sensing in terms of sensitivity but also displays strong resilience against optical noise.

[0052] FIG.1A depicts an energy diagram describing energy levels for newly formed plexcitonic states separated by Rabi splitting ΩR under strong coupling. FIG.1B depicts a diagram describing spectral splitting under strong coupling. FIG.1C depicts anticrossing of the two plexcitonic levels by tuning the transition frequency of the exciton. FIGS.1D- 1F are schematic diagrams representing different scenarios of light−matter interactions in a plasmonic nanocavity. FIG.1D represents a single exciton strongly coupled with a plasmonic nanocavity with an ultrasmall mode volume Vm, FIG.1E represents an ensemble of N excitons strongly coupled with a plasmonic nanocavity, and FIG.1F represents N excitonic particles strongly coupled with a plasmonic nanocavity with an ultrasmall mode volume Vm. FIG.1G-1I are plots representing analytical results for the following: FIG.1G is a plot representing coupling strength- dependent spectral splitting for a single exciton strongly coupled with a plasmonic nanocavity as shown in FIG.1D; FIG.1H is a plot showing exciton population-dependent spectral splitting for an ensemble of N excitons strongly coupled with a plasmonic nanocavity as shown in FIG.1E. FIG.1I depicts plots of coupling strength g-dependent Rabi splitting ΩR(left) and exciton population N-dependent Rabi splitting (right), respectively.

[0053] Strategy 1: A Single Exciton. Theoretically, quantum plexcitonic sensing can reach single-molecule sensitivity provided that strong coupling can be achieved between a single exciton 106 and the plasmonic cavity 100, as shown in FIG.1D. The calculated scattering spectra shown in FIG.1G for a single exciton coupling with a plasmon based on the coupled-oscillator model imply that generation of plexcitons depends on the coupling strength. However, under normal circumstances, the transition dipole moment is approximately 1 Debye for commonClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT atomic and molecular QEs, too small for strong coupling to be achieved. Given the coupling strength g0 ∝ |ε·μ0| / √Vm (eq S2), an ultrasmall plasmonic mode volume Vm can be used to compensate for the small transition dipole moment μ0. In parallel, a high-vacuum, ultrastable mechanical and thermal environment can be created to suppress spectral line width broadening, thus reducing γp and γe to meet the strong coupling condition g0 > |γ−| / 2 (eq S11b) for a single exciton. However, given the associated stringent conditions, implementing this strategy on a regular basis remains elusive, and thus, it may not offer a practical quantum plexcitonic sensing strategy under ambient conditions when under excitation 112.

[0054] Strategy 2: N Excitons (N ≫ 1). One approach to overcoming the limitations described above is to increase the population of excitons 108 that can coherently interact with the plasmonic cavity 102, which can result in a collectively significant coupling-to-loss ratio √Ng0 / |γ−| (eq S11a) required for strong coupling, an arrangement shown in FIG.1E. On the basis of the Tavis−Cummings Hamiltonian, the coupling strength for N excitons is modified as √N|ε·μ0| / √Vm. Therefore, it offers a viable route for achieving strong coupling even in a lossy plasmonic cavity by spatially and spectrally overlapping a large population of excitons with a single plasmonic mode. The calculated scattering spectra for N excitons coupling with the plasmonic nanocavity display unambiguous N-dependent Rabi splitting, as depicted in FIG.1H, which mimics the coupling strength-modulated Rabi splitting shown in FIG.1I, and highlights that strong coupling can be achieved via both orthogonal methods. However, coupling N excitons with the plasmonic nanocavity unavoidably compromises the achievable sensitivity, rendering this strategy less than ideal for developing a quantum plexicitonic sensing method.

[0055] Strategy 3: N Excitonic Particles (N ≥ 1). One promising approach 104 is to leverage the modal strong coupling between the localized surface plasmon resonance (LSPR) and the plasmonic metamaterial mode, as depicted in FIG.1F. Plasmonic nanoparticles 110 supporting spectrally tunable LSPR can be facilely synthesized using wet chemistry. Given that the LSPR can be modeled as a two-level QE, plasmonic nanoparticles 110 can thus be generically called excitonic particles. As compared to atomic and molecular QEs, they possess a much larger transition dipole moment owing to the collective oscillation of free electrons (as compared to the collective excitons described in regard to Strategy 2 and shown in FIG.1E). In the meantime, plasmonic hyperbolic metamaterials support metamaterial modes with an ultrasmall mode volume, facilitating strong coupling with excitonic particles. Plasmonic hyperbolic metamaterials can be fabricated using nanosphere lithography, e-beam lithography, and other techniques. In this strategy, the analytes to be detected are not directly involved in the strong coupling; instead, both excitonic particles and the hyperbolic metamaterial platform need to be functionalized withClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT analyte specific chemical or biological recognition elements. The spatial coupling between excitonic particles and the metamaterial platform is thus contingent upon the successful capturing of analytes, which necessitates a sandwich type assay as we demonstrated previously. Therefore, modal strong coupling of a few excitonic particles on a plasmonic hyperbolic metasurface presents a promising strategy and is thus adopted for demonstrating a quantum plexcitonic sensing method under ambient conditions. Additionally, while there are N − 1 dark states coexisting with plexcitonic states, they do not contribute to plexcitonic spectral features for sensing applications and are thus not further discussed.

[0056] In the above example strategies, in addition to providing analytes to interact with the plasmonic field in the strong-coupling regime, more importantly, the present disclosure provides a broadly generalizable quantum plexcitonic sensing method that utilizes excitonic particles to strongly couple with a plasmonic metasurface. In examples, the analytes are not directly involve din achieving strong coupling. Alternatively, after the analytes are captured by the biological recognition elements that are functionalized on both excitonic particles and the plasmonic metasurface, strong coupling can be achieved, giving rise to plexcitons as an additional feature of the present method.

[0057] The descriptions of the behavior of a metamaterial mode on a plasmonic surface within an optical nanocavity or microcavity is described in context of a situation where light is trapped on the surface near a plexcitonic material. The excitonic materials, for example, a metal particle combined with an excitonic particle could be a quantum dot, or a nanoparticle, or fluorophores. In examples, ωRrepresents how far the peaks are separated in terms of their energy. While the nanoparticle or fluorophore size can vary, the relevant factor is the suitability of the nanostructure to enable a high Q factor. Energy splitting and bending behaviors for the coupled plasmon-QEs system with dissipation can be shown or described by schematic representation of the QED system comprising of a two-level atomic system representing QEs with a transition frequency ω0 and decay rate γ0 coherently interacting with a single mode of the oscillating bosonic field in a plasmonic cavity with a resonant frequency ωb and dissipation rate γb. The effective coupling strength is λ.

[0058] To further describe the mechanism responsible for the observed radiative energy shifts under the plasmonic field, quantum electrodynamics (QED) can be used to phenomenologically incorporate the dissipation rates γ0for the two-level atomic system representing quantum emitters (QEs), i.e., dyes, and γb for the plasmonic cavity into the system, as described previously. The Hamiltonian matrix for the coupled plasmon-QEs system is created as:Client Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT

[0059] By diagonalizingenergy eigenvalues are obtained as .

[0060] energy diagrams representingthe a with the present disclosure. The energy diagram of the system features two plexcitonic states (UP and LP) with the energy eigenvalues of ^±^. A QE and plasmon each have their own energy levels, and through their interaction, their hybridized form is manifested as an upper plexciton (UP) and a lower plexciton (LP), which show as two new separate peaks.

[0061] Twice the last term in the previous equation is defined as the generalized Rabi frequency:

[0062] in its complex formrate defined as γ− = (γ0 − γb) / 4. At zero detuning, the threshold for energy splitting occurs at λ = 2γ−, which divides the energy space into two regions that we term as the energy-bending region and the energy-splitting region. In the energy-splitting region, the coupling strength is more than two times greater than the reduced energy dissipation rate (λ > 2γ−), and therefore, a full Rabi cycle can be completed.

[0063] Such coherent plasmon-QEs interactions are characterized by the rapid and reversible energy exchange, resulting in the formation of a pair of plexcitonic states called upper plexciton (UP) and lower plexciton (LP). In the energy-splitting threshold with zero detuning where the coupling strength is exactly offset by twice the reduced energy dissipation rate, the generalized Rabi frequency becomes zero. Such a singular state is protected against perturbation from the plasmon- QEs interaction and is manifested as the point of intersection for energy-bending and energy-splitting regions.

[0064] Of particular interest to an exploration of the radiative energy shifts is the energy-bending region, where the coupling strength is less than twice the reduced energy dissipation rate (λ < 2γ−). The generalized Rabi frequency, ωR, becomes purely imaginary and thereby merely opens an additional energy dissipation channel instead of splitting the plexcitonic states. Consequently, the plasmon-QEs interaction bends the energy levels for both QEs and SPs. This finding, echoingClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT the one made on the perturbation of the molecular energy levels through (optical Stark effect) OSE by laser pumping, highlights the analogous roles of SPs and laser in fine-tuning the hybrid states of a coupled system. This can be considered the first report of the energy-level perturbation by the plasmonic effect that is analogous to OSE, which can be referred to as the “plasmonic Stark effect”.

[0065] In exemplary examples of the present disclosure, one or more analyte-induced peak shifts in the weak coupling regime can reveal that as analyte concentration (C) increases, an energy resonance peak of the plasmonic cavity increases as well, with a higher concentration exhibiting a peak shift. Rabi splitting, ωR, in the strong coupling regime can describe the split between the upper plexciton (UP) and the lower plexciton (LP), as previously shown and described herein.

[0066] FIG.2A is a Schematic of a plasmonic hyperbolic metamaterial platform consisting of a hexagonally patterned gold nanohole array sitting on alternatively stacked silica−silver thin films. The gold nanohole array has a periodicity of 500 nm, a hole diameter of 400 nm, and a thickness of 60 nm. The silica and silver layers have thicknesses of 32 and 16 nm, respectively. There are a total of six cycles of silica−silver layers. The top silver layer is separated from the gold nanohole array by a silica spacer of 12 nm. FIGS.2B and 2C are plots of calculated permittivity and isofrequency surface (IFS) at 681 nm, respectively, for the metasurface made of six cycles of alternatively stacked silica−silver thin films. FIG.2D is a plot of angle-resolved reflection spectra for the metasurface as shown in FIG.2A. FIG.2E is a plot of reflection spectrum under an incident angle of 45° extracted from the upper dashed line in FIG.2D. FIG.2F is a cross-section and FIGS.2G-2I are different top views of the normalized electrical field distribution for the metasurface shown in FIG.2A at 681 nm. The dashed lines in FIG.2F represent the top views in FIGS.2H and 2I, respectively, while the dashed lines in FIGS.2H and 2I represent the cross section in FIG.2F. For FIG.2D and 2I, the incident polarization is along the x-axis. The white scale bar in FIGS.2F-2I is 250 nm.

[0067] The studied metamaterial platform (FIG.2A) consists of a hexagonally patterned gold nanohole array sitting on a planar metasurface made of six cycles of alternately stacked silica− silver thin films. The gold nanohole array has a periodicity of 500 nm, a hole diameter of 400 nm, and a thickness of 60 nm. The underlying silica and silver layers have thicknesses of 32 and 16 nm, respectively. These parameters are chosen on the basis of the requirement of a hyperbolic dispersion (FIG.2B), which leads to the activation of high-k metamaterial modes (FIG.2C), featuring a high Q factor (and thus a small dissipation rate γp) and an ultrasmall mode volume (Vm). However, owing to momentum mismatch, such metamaterial modes cannot be directly excited. Instead, a diffraction grating, such as a gold nanohole array, which can diffract light andClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT produce a wide range of wavevectors entering the metasurface, can be utilized to excite high-k modes. These modes are manifested as spectral resonance peaks in the angle dependent reflection spectra (FIG.2D) calculated by finite difference time-domain (FDTD) simulations. Of particular interest is the 681 nm resonance mode observed under an incident angle of 45° (FIGS.2A and 2E). The electric field profile of this mode shows that its EM energy is primarily concentrated on the surface of the gold bridge, which connects two adjacent nanoholes along the x-axis direction (FIGS.2F-2I). Therefore, this mode can be readily accessed from the top surface of the gold nanohole array and can thus be harnessed to generate plexcitons by strongly coupling it with excitonic particles. Gold nanorods with a length of 99 nm, a radius of 15 nm, and an end radius of 8 nm have been selected as excitonic particles, as they support a longitudinal LSPR mode at 681 nm well matched with the metamaterial mode at the same wavelength. It is important to note that despite previous demonstrations of strong coupling, the mode volumes of the involved nanostructured systems cannot be easily accessed by analytes or excitonic particles as it is sterically (partially or fully) blocked by the nanostructure, thus making them not well suited for developing a practical quantum plexcitonic sensing method.

[0068] FIG.3A is a schematic for a quantum plexcitonic sensing device featuring a microfluidic platform with the sensing area consisting of the plasmonic hyperbolic metamaterial platform as shown in FIG.2A. FIG.3B shows a schematic process for functionalization of gold nanorods and the metamaterial platform with respective analyte-specific biological recognition elements, resulting in the gold nanorods being captured on the metamaterial platform in the presence of analytes. Gold nanorods are oriented in a direction in which the longitudinal axis forms an angle of β with respect to the horizontal direction. The gold nanorod orientation angle β is found to only minimally affect the strong coupling with the metamaterial mode.

[0069] FIG.3A shows a biosensing device and measurement method using quantum plexcitonic principles, in accordance with the present disclosure. Within the device, there is an optical shift based on surface plasmon resonance effects when an analyte is introduced into the biosensing device provides a perturbation or shift within the dielectric environment, based on the specific analyte and the concentration of the analyte detected. The biosensing device uses an interaction between the materials, which results in a peak splitting, as previously shown and described herein. This peak splitting is dependent on concentration and is at least doubled in magnitude as compared to typical SPR effects. In addition to peak splitting and peak shift, there is an intensity change that can be quantified as well. The molecular sensing device 300 includes an inlet port for nanorods 310 whereby a plurality of nanorods 302 is introduced into a sensing area 318 of the molecular sensing device 300 by one or more droplets of a plurality of nanorods in a suspensionClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT 306. The plurality of nanorods 302 can include gold, silver, copper, or alternative metals exhibiting SPR effects, such as graphene or doped semiconductor materials. In the example of gold or other nanorods, the capability of tuning the frequency can be provided by modulating the aspect ratio of the nanorods, as various metamaterial optical modes can be spectrally differentiated at different wavelengths. For example, at a fixed frequency, the aspect ratio of a nanorod can be used to tune and match to each metamaterial mode, providing a spectrally differentiated plasmonic resonance for each nanorod. In examples, a first nanorod can be utilized to interact with a first metamaterial mode, while a second nanorod can be utilized to interact with a second metamaterial mode. The use of gold nanoparticles or gold nanorods, as well as other materials including nanomaterials that exhibit similar interactions, such as silver, copper, and the like, must be metallic based or include quantum dots or fluorophores, or be aggregates, clusters, hybrids, or alloys of one or more of the materials described herein. In examples, the plurality of nanorods comprise a mixture of nanorods or more than one aspect ratio, wherein each type of nanorod can be functionalized differently to enable detection of a different analyte. Examples of mixtures of nanorods include where the aspect ratio of one or more of the plurality of nanorods is from about 1.1 to about 10. In examples, gold nanorods are one type of generalized quantum emitters which can provide a dipole transition that is essential to achieve strong coupling between quantum emitters and the plasmonic resonances on the metasurface. Illustrative examples of quantum emitters can include plasmonic nanoparticles, such as but not limited to gold nanorods, gold nanospheres, gold nanostars, and any other shaped gold nanoparticles, fluorescent dyes, quantum dots, and in some examples, the chemical and bioanalytes to be detected that possess intrinsic dipole transitions upon excitations, among others.

[0070] A bioanalyte 304 is introduced into the molecular sensing device 300 by one or more droplets of one or more bioanalytes in a suspension 308, such as, but not limited to protein biomarkers, circulating tumor biomarkers (including but not limited to DNA, RNA, exosomes), peptides, drugs, biologics, neurotransmitters, inorganic and organic pollutants, heavy metals, and the like, placed in an inlet port for bioanalytes 312 whereby the bioanalyte 304 can be introduced into the sensing area 318 of the molecular sensing device 300. The molecular sensing device 300 is shown mounted onto a substrate or platform 314, and a quartz slide support 316. The molecular sensing device 300 further includes an outlet port 320. Examples of exemplary suitable substrates 314 include PDMS, other transparent polymer materials, glass, quartz, combinations thereof, and the like. Illustrative examples of suitable support 316 materials can further include PDMS, other transparent polymer materials, glass, quartz, silicon, combinations thereof, and the like. A spectroscopic measurement device 322, or a spectroscopic instrument, which emits in a range ofClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT ultraviolet (UV) to infrared (IR) light towards the sensing area 318 is disposed onto or near the molecular sensing device 300. The spectroscopic measurement device 322, or a spectroscopic instrument, may be portable, and any associated detector display printer, output device, or combination thereof can also be portable and suited to rapid on-site detection of biological analytes, including, but not limited to biological analytes associated with communicable diseases. As shown in FIG.3B, the molecular sensing device 300 is further shown having a metasurface 340, comprising at least one alternating layer of a semiconducting material and a conducting material or at least one layer of a semiconducting material disposed onto at least one layer of conducting material. In examples, there are more than one alternating layers of a semiconducting material and a conducting material to form the metasurface 340, for example, from about 2 to about 10 alternating layers of the semiconducting material and conducting material. In other examples, the metasurface can include up to 100 layers, such as from about 10 to about 75, or from about 10 to about 20 layers, from about 2 to about 50 layers, from about 2 to about 25 layers, or from about 2 to about 10 alternating layers. The molecular sensing device 300 includes a metal nanocavity or nanohole 332 array 334 disposed onto the metasurface 340. Within the metasurface 340, the semiconducting material can include silicon dioxide, aluminum oxide, or any semiconducting metal oxides, or combinations thereof, while the conducting material can include silver, gold, copper, or alloys thereof. The layered metasurfaces can include one layer of a metallic material and a second layer that is dielectric. By structuring their respective parameters, they can support distinct metamaterial modes with a high Q. Some of these additional details are visible in the enlarged view of sensing area as shown in FIG.3B. The plurality of nanoholes 332 is arranged in an array 334, as shown, which is made of gold. A top view 344 is also shown. In other examples, the hole array could be arranged in a square, hexagonal, or other manner so long as they the array includes a periodic structure. In examples, detectors can include fiber optics and microscope lenses. Light sources can include UV, visible, Near-IR, or IR light emission sources. Accompanying devices can include a spectrometer, fibers, or optical elements to transmit light.

[0071] Also shown in the enlarged view of sensing area depicted in FIG.3B is a first nanorod 326, a second nanorod 328, and a third nanorod 330, each having a specific aspect ratio, and disposed upon the plurality of nanoholes 332 arranged in the nanohole array 334. While not necessarily shown to scale, nanorods 326, 328, 330 having different aspect ratios can show differential selectivity towards different analytes or biological markers. A surface of the metal nanohole array 334 can be configured to receive one or more bioanalyte, or biological analyte, as well as a plurality of nanorods 326, 328, 330. Also shown disposed within the molecular sensing device 300 is a biological analyte 342A associated with the nanorods 326, 328, 330. While notClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT shown in detail herein, the various nanorods 326, 328, 330 can be functionalized with aptamers, ligands, antibodies, antigens, peptides, and the like, for the purpose of interacting with a particular target analyte. Further disposed upon a surface of the nanohole array 334 is a biological recognition element 342B associated with a biological analyte 326A. Biological recognition elements can include but are not limited to aptamers, ligands, antibodies, antigens, peptides, and the like. In the metasurface 340, combined with the array 334 of nanoholes 332 a metamaterial platform is provided, where the underlayers form a metalayer surface.

[0072] The metamaterial platform can be integrated into a microfluidic platform (FIG.3A). To perform quantum plexcitonic sensing, gold nanorods and the gold surface of the metamaterial platform can be functionalized with analyte specific chemical or biological recognition elements (FIG.3B) using thiol-based surface chemistry. The involved biological recognition elements 342A, 342B for gold nanorods and the metamaterial platform can be similar, such as antibodies that bind the analyte 326A, or different, such as two different single stranded DNA sequences with each specific to a binding site of an analyte326A, which may be a protein biomarker. Such flexibility expands the applicability of quantum plexcitonic sensing for measuring a broad range of analytes. The functionalized gold nanorods 326, 328, 330 are then introduced along with the analytes from the two inlets of the microfluidic platform. During incubation, an increasing number of analytes are captured by the recognition elements, which bring gold nanorods 326, 328, 330 into the proximity of (and covalent connection to) the gold nanohole array surface. The resulting spatial coupling between gold nanorods 326, 328, 330 and the platform, combined with their spectral overlap, enables strong plasmon−exciton coupling for analyte sensing. To effectively realize the spectral features of quantum plexcitonic sensing, a varying number of gold nanorods per unit cell of the gold nanohole array, or NUC, are made to couple with the metamaterial mode at 681 nm. Gold nanorods are placed at the center and right on top of the gold bridge connecting two adjacent nanoholes. With an increasing NUCfor gold nanorods, spectral splitting is observed (FIG.4A). Analysis of the Rabi splitting and coupling strength confirms that the condition for strong coupling as outlined in eq S11 is met. The observed spectral splitting provides further evidence for strong coupling. While reflection spectra in FIG.4A represents for gold nanorods oriented horizontally (β = 0°), the nanorod orientation is found to only minimally affect strong coupling. This can be attributed to the significant contribution of the longitudinal LSPR mode of the gold nanorods, which can be easily excited even under a less than ideal incident polarization direction.

[0073] In examples of the molecular sensing device 300, one or more biological recognition elements can be configured to recognize a communicable disease, alternatively in a rapid, on-siteClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT detection application. Examples of communicable diseases and specific aptamers such as covid- 19, tuberculosis, hepatitis B / C can be detected. While specific antibodies can be used to target them, antipathogenic aptamers specific to each type of communicable diseases can also be used with similar functions. In such examples the bioanalyte corresponds to a specific biological recognition element utilized in detection of one or more diseases or analytes representative of a specific health condition corresponding to the biological recognition element and biological analyte in a biological medium. In examples of the present disclosure, the bioanalyte can include a biological medium, or a sample comprising a biological medium can include a bioanalyte. Examples of applicable biological medium are further described herein. In examples, the molecular sensing device 300 can be present on a chip-based platform, where a chip including the molecular sensing device 300 is integrated into one or more other microfluidic platforms, paper- based test kits, or a combination thereof. In examples of the present disclosure, the molecular sensing device 300 includes one or more transducers to measure or use quantum nanosources to perform the measurement. Sensing devices of the present disclosure provide a molecular sensing device with measurements having advantageous signal to noise ratio, due to decreases photon fluctuation with the molecular sensing device 300.

[0074] In related energy diagrams representing such a sensing device 300, it can be demonstrated that a characteristic energy diagram exhibits three separate peak splits, or Rabi frequencies, ωR1, ωR2, and ωR3, associated with three different analytes. The intensity of each of the dual peaks increases as the concentrations, C1, C2, and C3 of each respective analyte detected by the molecular sensing device 300 increases.

[0075] FIG.4A is a heat map reconstructed from the calculated reflection spectra for quantum plexcitonic sensing using gold nanorods. FIG.4B is a plot of Rabi splitting ΩR with respect to the population of gold or silica nanorods NUCbased on FIG.4A. NUCis the number of gold or silica nanorods per unit cell of the gold nanohole array. Gold nanorods are oriented horizontally with β = 0°. FIG.4C is a plot representing evaluation of conventional sensitivity is based on the ratio of Rabi splitting ΩRrelative to the change in the population of gold or silica nanorods δNUC, where linear fitting is performed to obtain conventional sensitivity ΩR / δNUCfor quantum sensing. FIG. 4D is a heat map reconstructed from the calculated reflection spectra for classical sensing based on a frequency shift using silica nanorods with the same dimension as gold nanorods. FIG.4E is a plot of frequency shift δω with respect to the population of gold or silica nanorods NUCbased on FIG.4D. FIG.4F is a plot representing the evaluation of conventional sensitivity based on the ratio of frequency shift δω relative to the change in the population of gold or silica nanorods δNUC, where linear fitting is performed to obtain conventional sensitivity δω / δNUCfor classicalClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT sensing. FIGS.4G-4H are plots depicting an evaluation of quantum sensitivity by normalizing Rabi splitting ΩR and frequency shift δω with respect to the population of gold or silica nanorods NUC, where quantum sensitivity ΩR / NUC for quantum plexcitonic sensing is presented in FIG.4G and quantum sensitivity δω / NUC for classical sensing is shown in FIG.4H. FIG.4I is a plot of normalized quantum sensitivity ΓS by taking the ΩR / δω ratio, which quantifies the quantum sensitivity enhancement of quantum plexcitonic sensing compared to its classical counterpart.

[0076] The obtained Rabi splitting ΩR relative to NUC indicates its sensitive dependence on the population of gold nanorods (FIGS.4B and 4C). As a control, silica nanorods with the same dimensions have been used to study the performance of classical sensing based on the frequency shift δω on the same metamaterial platform. In sharp contrast to the dramatic spectral splitting in quantum plexcitonic sensing, an increase in NUCfor silica nanorods barely induces a frequency shift (FIG.4D). Only through close examination can the weakly NUC-dependent frequency shift be observed (FIGS.4E and 4F), underscoring the substantial advantages associated with quantum plexcitonic sensing.

[0077] With a decreasing NUC, Rabi splitting does not trend toward zero (FIGS.4B and 4C), albeit with a diminishing LP resonance mode, which suggests that gold nanorods strongly couple to the metamaterial platform at the single-nanoparticle level. As the population of gold nanorods is quantized, for the smallest studied NUCof 0.125 in FIG.4B, on average, there is one gold nanorod on the metamaterial platform with lateral dimensions of 4 μm × 4 μm. While this gold nanorod contributes to Rabi splitting, its spectral contribution is convoluted by the bare reflection spectrum from the uncoupled metamaterial area. Consequently, the resulting reflection spectrum displays a diminishing LP resonance mode while maintaining a finite and considerable level of Rabi splitting.

[0078] The significantly larger frequency variation associated with Rabi splitting implies a sensitivity for quantum plexcitonic sensing much higher than that for classical sensing. Herein, two types of quantitative methods, i.e., conventional sensitivity and quantum sensitivity have been adopted to assess the quantum plexcitonic sensing performance. Conventional sensitivity applies to a large population of excitonic particles (NUC≫ 1) and can be obtained through linear regression analysis of the frequency variation relative to the population change. Quantum plexcitonic sensing is found to display a conventional sensitivity Sq cof 31.92 meV, compared to an Sc cof 0.66 meV for classical sensing (FIGS.4C and 4F). In other words, quantum plexcitonic sensing is ∼48 times more sensitive than its classical counterpart.

[0079] In the meantime, quantum sensitivity is utilized to capture the essence of quantum sensing, which may possess a sensitivity down to a few analytes or a single analyte (NUC ≥ 1).Client Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT Quantum sensitivity can be obtained by taking the ratio of the induced frequency variation relative to the population of excitonic particles NUC. Quantum sensitivity is found to be dependent of NUC (FIGS.4G and 4H). Again, quantum plexcitonic sensing displays a significantly higher quantum sensitivity Sq q ranging from 67 to 116 meV, while that for classical sensing Sc q is much smaller, varying from 0.8 to 2.9 meV. To directly compare quantum plexcitonic sensing versus classical sensing, a normalized quantum sensitivity ΓS is used, where ΓS = ΩR / δω. Normalized quantum sensitivity ΓS suggests that quantum plexcitonic sensing outcompetes its classical counterpart by a factor of at least 40 (FIG.4I).

[0080] It is important to note that the sensitivities mentioned above for classical sensing may not be practically achievable owing to the weak correlation of the frequency shift relative to the excitonic particle population change, as such weak correlation can be easily masked by optical noise and other perturbations in physical systems.

[0081] Furthermore, it is imperative to evaluate how quantum plexcitonic sensing performs under the influence of optical noise. Herein, white noise, which was modeled using additive white Gaussian noise with various levels of the signal-to-noise ratio (SNR), was added to the reflection spectra in FIG.4A and FIG.4D to investigate noise-modulated sensitivity based on Monte Carlo simulations.

[0082] FIG.5A is a power spectrum, normalized and converted from the reflection spectra in FIG.4A with a vertical offset for better visualization and having white noise (SNR = 5 dB) added to the quantum plexcitonic sensing power spectrum. FIG.5B is a violin plot of quantum plexcitonic sensing, showing a significant difference in the NUC-dependent Rabi splittings. FIG. 5C is a plot depicting conventional sensitivity of 31.81 ± 0.33 meV obtained on the basis of linear regression analysis. FIG.5D is a power spectra, normalized and converted from the reflection spectra in FIG.4A with a vertical offset for better visualization and having white noise (SNR = 5 dB) added to the classical sensing power spectra. FIG.5E, FIG.5F are violin plots depicting classical sensing of NUC-dependent frequency shifts for SNR=5 and SNR=8, respectively. In contrast, in classical sensing, as shown in FIGS.5E and 5F the difference in the NUC-dependent frequency shifts is found to be not significant in the violin plot for SNR=5 for FIG.5E, only when SNR ≥ 8 dB, as shown in FIG.5F, does the difference in the NUC-dependent frequency shifts become gradually significant. FIGS.5G and 5H are plots depicting comparisons of SNR- dependent conventional sensitivity data between quantum plexcitonic sensing and classical sensing, respectively, where the shaded areas represent the absolute uncertainty of conventional sensitivity. FIG.5I is a comparison plot of the SNR-dependent relative uncertainty of conventional sensitivity between quantum plexcitonic sensing and classical sensing, where theClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT relative uncertainty is defined as the percentage ratio of the absolute uncertainty to the mean sensitivity. FIG.5J and 5K are plots comparing SNR- and NUC-dependent quantum sensitivity between quantum plexcitonic sensing and classical sensing, respectively, where the shaded areas represent the absolute uncertainly of quantum sensitivity. FIG.5L is a comparison plot of the SNR- and NUC-dependent relative uncertainty of quantum sensitivity between quantum plexcitonic sensing and classical sensing, where the relative uncertainty is defined as the percentage ratio of the absolute uncertainty to the mean sensitivity. The scale bar in FIG.5L is 50%. p values of <0.0001 (****), <0.001 (***), <0.01 (**), and <0.05 (*) were considered significant. p values of >0.05 were considered nonsignificant (ns).

[0083] Representative noisy spectra are presented in FIGS.5A and 5D. Through Lorentzian fitting, Rabi splittings in FIG.5A and frequency shifts in FIG.5D for a SNR of 5 dB are obtained; the distributions of these results are presented in violin plots in FIGS.5B and 5E, respectively. In quantum plexcitonic sensing, the difference in NUC-dependent Rabi splitting is found to be significant. Regression analysis returns a conventional sensitivity of 31.81 ± 0.33 meV for SNR = 5 dB (FIG.5C). Following a similar analysis, a series of SNR-dependent conventional sensitivities and uncertainties are obtained and are shown in FIG.5G. While the conventional sensitivity initially increases with an increasing SNR and then converges at 32.11 ± 0.01 meV, the accompanying absolute sensitivity uncertainty decreases monotonically, as expected, in response to the increase in SNR.

[0084] In classical sensing, the difference in NUC-dependent frequency shifts is not significant for SNR ≤ 8 dB; only when SNR ≥ 8 dB (FIG.5F) does the difference in NUCdependent frequency shifts become gradually significant. While SNR-dependent conventional sensitivity and uncertainty can be mathematically obtained on the basis of regression analysis of NUC- dependent frequency shifts, the uncertainty is significant for SNR ≤ 8 dB. Therefore, it can be concluded that the shaded area in FIG.5H with SNR ≤ 8 dB as a conventional sensitivity indeterminable area owing to a large margin of error. Additionally, a comparison of the relative uncertainty of conventional sensitivity in FIG.5I suggests a much larger sensitivity uncertainty for classical sensing in comparison to that for quantum plexcitonic sensing.

[0085] In the meantime, SNR- and NUC-dependent quantum sensitivity and uncertainty are evaluated and presented in FIGS.5J-5L. Quantum plexcitonic sensing displays an overall much higher quantum sensitivity yet a considerably smaller relative uncertainty compared to those of its classical counterpart, consistent with observations made in FIGS.5G-5I. Importantly, quantum plexcitonic sensing is robust against an increasing level of optical noise, while classical sensingClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT suffers. Taken together, observations from the noise-modulated sensitivity studies reinforce the quantum advantage over classical sensing.

[0086] The three potential strategies for realizing quantum plexcitonic sensing under ambient conditions were conceptualized and used to demonstrate a modal strong-coupling-based quantum plexcitonic sensing method on a plasmonic metamaterial platform. A systematic performance study established that the sensitivity of quantum plexcitonic sensing is much improved as compared to that of its classical counterpart. Further noise-modulated sensitivity studies through Monte Carlo simulations can reinforce the advantage of quantum plexcitonic sensing over classical sensing. The presented quantum plexcitonic sensing represents an entirely new mechanism for developing quantum-enhanced optical devices based on the unique and readily accessible quantum states of plexcitons; it is expected to be adaptable to various strongly coupled plasmon−exciton systems and can be generalized for detecting a wide variety of chemical and biological analytes.

[0087] FIG.6 is a flowchart illustrating a measurement method using quantum plexcitonic principles, in accordance with the present disclosure. The molecular sensing method 600 includes the exposure of a molecular sensing device to a sample 602, followed by subjecting the molecular sensing device to light 604. The light can originate from one or more spectrophotometer devices and can direct one or more of the following types of radiation to the device and / or sample contained upon or deposited upon the molecular sensing device: ultraviolet, infrared, near infrared, gamma, x-ray, and the like. For the light sources, visible and near-infrared light can also be used. The type of spectrophotometer could be standard UV-Vis-NIR spectrophotometer or fiber probe-based, like the handheld devices available from Ocean Optics of Orlando, FL or Thorlabs of Newton, NJ. Next, an electrochemical signal is generated from a reaction between the sample and a surface of the molecular sensing device 606, and in particular, the reaction may involve a reaction between the analyte and a biological recognition element disposed upon one or more surfaces of the molecular sensing device, or an interaction between one or more types of plurality of nanorods deposited upon a surface of or contained within the molecular sensing device. Next, the molecular sensing method 600 includes analyzing the electromagnetic spectral signal to determine a presence of a target analyte in the sample 608, analyzing the electromagnetic spectral signal to determine a quantity of the of the target analyte in the sample 610, and finally transmitting presence of the target analyte and the quantity of the target analyte 612. The molecular sensing method 600 can be performed by a molecular sensing device having a metasurface including a layer of a semiconducting and / or dielectric material disposed onto a layer of conducting material, and a metal nanohole array disposed onto the metasurface, as describedClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT herein. The molecular sensing method 600 further includes introducing a biological recognition element disposed onto a surface of the metal nanohole array, wherein the biological recognition element reacts with the sample. In certain examples, the sample includes a biological media. The biological media may be an aerosol. The biological media may be a liquid, such as but not limited to blood or saliva. In certain examples, the method for molecular sensing may include calibrating one or more electromagnetic signals to a presence of an analyte included in the biological media. A target analyte may also be introduced in the absence of any biological media. The biological media introduced to the molecular sensing device may be in solid form, aerosol form, liquid form, or combinations thereof. The biological media introduced to the molecular sensing device may be phlegm, mucous, sneeze, blood, urine, sweat, vomit, saliva, aspirated saliva, stool, and other biopsy samples, or combinations thereof. The method for molecular sensing may include determining or detecting a presence of the analyte and a quantity of the analyte via a display, secondary device, or combination thereof. The method for molecular sensing may include transmitting the presence of the target analyte and the quantity of the target analyte includes a colorimetric or spectroscopical transmission. In alternate examples, transmitting a presence of the target analyte and the quantity of the target analyte can alternately include a digital transmission to a portable computer medium such as an electronic display, cell phone, tablet, mobile computer, or combination thereof.

[0088] The present disclosure provides a broadly generalizable quantum plexcitonic method and device for molecular sensing by making analytes to interact with the plasmonic field in the strong-coupling regime. In this context, analytes serve directly as quantum emitters or can bind to quantum emitters through biorecognition elements which can rapidly and coherently exchange energy with the plasmonic field. Instead of a single peak shift in response to the dielectric perturbation, quantum plexcitonic biosensing displays dramatic Rabi splitting and are characterized by two new peaks called plexcitons, which are shifting in opposite directions in response to the analytes. Additional advantages of the oppositely shifted plexcitons is a new scaling law that increases as the square root of the perturbation, i.e., the analytes concentration, increases. As a result, quantum plexcitonic biosensors of the present disclosure are more sensitive than SPR immunoassays wherein the full strength is reached at very low concentrations. In examples, squeezed quantum states of light can be introduced. During the strong light-matter coupling, the quantum nature of light is preserved in the form of squeezed quantum plexcitonic state. Upon decoupling, the optical output conserves the quantum state of light and delivers an ultrasensitivity unbounded by the shot-noise limit. As achieving strong coupling requires the analytes to be spatially confined into the subwavelength mode volume of the plasmonic field andClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT simultaneously spectrally overlapped with it, such stringent conditions help effectively preclude false positives and make quantum plexcitonic biosensors comparatively robust against environmental interference. Such a quantum plasmonic biosensing design can thus deliver ultrasensitive solutions for accurate analytes detection. The quantum plexcitonic system can be realized on a judiciously designed plasmonic substrate. The platform of the present disclosure includes a gold nanohole array disposed upon on a metasurface, which is fabricated using alternatively stacked silica-silver thin films. As the gold nanohole array provides a diffraction grating, the supported metamaterial modes can be excited. Thus, the excited metamaterial modes exhibit high-Q spectral lines and therefore, they permit strong light-matter interaction with an excitonic particle through near-field coupling. Owing to the wide spectral tunability of gold nanorods, they can be selected as the desired excitonic particles and can be tuned to be spectrally in resonance with one of the metamaterial modes. Alternatively, any other types of metasurfaces can be similarly used to realize quantum plexcitonic sensing so long as they support similarly high Q metamaterials modes to strongly coupling with excitionic particles.

[0089] As a result, quantum plexcitons can be excited and are manifested as a pair of newly formed peaks separated by Rabi frequency. By functionalizing the plasmonic platform and the gold nanorods with biological recognition elements that are specific to given analytes of interest, the quantum plexcitonic system can thus function as a platform for quantum plexcitonic biosensing. Notably, multiplexed biosensing can be readily enabled by utilizing gold nanorods with multiple resonance frequencies that are spectrally aligned with the respective metamaterial modes.

[0090] Such a chip-based plasmonic platform can be integrated onto a paper test strip which can be used for rapid test of Covid-19 and other biomarkers. As excitation and detection of quantum plexcitons only require a handheld light source and portable spectrometer, this can eliminate the use of complicated and expensive instrumentation, such as polymerase chain reaction (PCR) machines, fluorescence and Raman microscopes, or mass spectrometry. Therefore, the quantum plexcitonic biosensing is field-deployable for rapid detection of a panel of analytes. Experimental Quantum Plexcitonic Sensing Hamiltonians for plasmon-exciton coupling

[0091] To understand how plexcitons can be harnessed for quantum plexcitonic sensing, it is essential to have a mechanistic understanding of the formation, modulation, and manifestation of plexcitons. To start with, the coupling between a single plasmonic mode and a two-level excitonClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT (i.e., quantum emitter) can be described by the Jaynes–Cummings (JC) Hamiltonian. The JC Hamiltonian under rotating frame approximation is given by: ^^^^ = ^^(^^^ 1^^ +2) +1 2^^^^^ + ^^(^^^^^ + ^^^^^) (S1)

[0092] In eq.resonance frequency ^^, where ^^^and ^^ are the creation and annihilation operators. The second term^^ ^^^^^is the Hamiltonian for the exciton with a transition frequency ^^. The third term ^^(^^^^^ + ^^^^^) represents the plasmon-exciton coupling with a coupling strength ^^, which isgiven by: ^^ ∝ |^ ∙ !|⁄ "#$ (S2)

[0093] where #$is the plasmonic mode volume,!is the excitonic transition dipole moment, and ^ is the unit vector for the electric field. ^^^, ^^^, and ^^ are Pauli matrices for inversion, raising and lowering. In the JC Model, a pair of quantized hybrid plasmon-exciton modes are expected to form (Fig.1a). The new eigenstates are given by: |±^' = 1(|^, * + 1^ ± |+, *^) (S3)

[0094] In eq. S3, the(UP) and lower plexciton (LP), as shown in FIG.1A. Essentially, the ground state |^^ with * + 1 excitations in the plasmonic cavity can hybridize with the excited state |+^ with * excitations in the plasmonic cavity, forming the UP and LP states | ± ^*. The corresponding eigenvalues can be obtained as: ^',± = ^,(* + 1 / 2) ± .4(* + 1)^^^ + ∆^ / 2 (S4)

[0095] where Δ = ^1 ― ^+ is the energy deun ng o e excitonic transition frequency ^+ from the plasmonic resonance ^1. Eq. S4 indicates that, as compared to the unhybridized states, the newly formed plexcitonic states are shifted away from the bare plasmonic and excitonic states, and are separated by an energy given by the Rabi frequency: =^^^Client Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT

[0096] For an exciton in resonance with the plasmonic cavity, i.e., Δ = 0, the Rabi frequency is reduced to: Ω3 = 2^^ (S5b)

[0097] where the factor √* + 1effective coupling strength ^0. The JC model can be extended to study the interaction between 4 excitons with a plasmonic cavity using the Tavis–Cummings (TC) Hamiltonian, where a large number of excitons are collectively coupled with a small number of excitons in the plasmonic cavity. Based on the Holstein–Primakoff transformation, the collective spin operator for 4 excitons 56 = ∑98:^ ^^8 can be replaced by a bosonic operator ;< for Pauli matrices, with the TCHamiltonian^^=^ = ^^^^^^^ + ^ 4^(− <^< ^< <^ (S6)2 + ; ;) + √4^^(^^ ; + ^^; )

[0098] In eq.are modeled as a giant quantum oscillator coupling with the plasmonic cavity. As compared to a single exciton, the collective coupling can significantly augment the plasmon-exciton coupling strength by a factor of√4. Accordingly, the Rabi frequency under both off-resonance and on- resonance conditions is revised by a factor of√4, and is given by: Ω3 = .4(* + 1)4^^^ + ∆^ (S7a)

[0099] The derived Rabithe essence of plexcitons and manifests itself as the plexcitonic energy level splitting shown in FIG. 1A. To unveil how the plasmonic energy loss rate ?1 and the excitonic decay rate ?+ can shape Rabi splitting, the Hamiltonian ^@^ for the coupled plasmon-exciton system with 4 excitons can be written as: ^= ^^ − D?^ √4^^ E

[0100] In eq. S8, the interaction of 4 excitons with the plasmonic mode. After diagonalizing the Hamiltonian, the complex eigenvalues are obtained as:Client Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT ^^ ^± = (^^ + ^^) / 2 − D(?^ + ?^) / 2 ± .44^^ − (?F + DG)^ / 2 (S9)

[0101] where the reduced energy dissipation rate + ― ?1. Accordingly, thecomplex Rabi frequency is given as: Ω^ ^3 = .44^^ − (?F + DG)^ (S10)

[0102] The formation of plexcitons requires H^3 > 0 , which results in the necessary conditionfor plasmon-exciton strong coupling under the on-resonance condition, as given by: √4^^ > |?F| / 2 (S11a)

[0103] For a single excitonic^^ > |?F| / 2 (S11b)

[0104] Eq. S11b suggests that the effective coupling strength needs to outcompete half the reduced energy dissipation rate of the coupled plasmon-exciton system in order to achieve strong coupling. Eq. S10, S11a and S11b lay out the theoretical foundation for quantum plexcitonic sensing, in which multiple tuning parameters are directly related to Rabi splitting. It is important to note that Rabi splitting can be directly measured as it is spectrally manifested as a pair of split peaks shifting in opposite directions away from the bare plasmonic and excitonic resonance peaks. The situation can be illustrated well by the scattering spectra for a coupled plasmon- exciton system calculated based on the coupled-oscillator model, as shown in FIG.1B. In an energy dispersion diagram, Rabi splitting is also evinced as the anti-crossing between UP and LP by sweeping the excitonic frequency (FIG.1C). Notably, both the UP and LP energy levels, and particularly Rabi splitting, are sensitive to a series of tuning parameters, including the energy detuning Δ and individual excitonic coupling strength ^0 of the coupled plasmon-exciton system, the mode volume #Kand spectral linewidth 2?1of the plasmonic nanocavity, the transition dipole moment !, spectrallinewidth 2?, and population 4 of the exciton. Modulation of any of these parameters can lead to a variation of the energetics of plexcitons, which can be measured using optical spectroscopy. This underscores the flexibility with which plexcitons can be leveraged as a novel transduction signal for developing innovative quantum plexcitonic sensing methods. FDTD simulationsClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT

[0105] Ansys Lumerical 2020 R2.2 (Anasys. Inc. Vancouver, BC, Canada) software was employed to conduct all the FDTD-based numerical studies. A plane wave with horizontal polarization was used as the excitation light source while periodic boundary conditions were used for calculating the optical properties of the plasmonic hyperbolic metamaterials, including the coupling with gold nanorods and silica nanorods. Separately, the Total-Field Scattered-Field (TFSF) was used as the input source to calculate the extinction spectral of gold nanorods with perfectly boundary conditions used. The background refractive index was set as 1.0. Definition of conventional and quantum sensitivity

[0106] Conventionally, for a large population of excitonic particles, i.e., 4LM≫1, sensitivity is defined as the ratio of the induced frequency shift relative to the molar concentration change which, in this case, is the population change of excitonic particles, or N4LM. This definition of sensitivity is called conventional sensitivity. The conventional sensitivity for quantum plexcitonic sensing (5OP) and Q frequency shift-based classic sensing (5^^) can be respectively given as: 5PΩ3O(4R^ ≫ 1) =(S12a)N4R^

[0107] which can be obtained through regression analysis of Rabi splitting ΩS, and frequency shift N^ with respect to the population change of the gold and silicaAs shown in FIGS.4C and 4F, based on linear fitting, quantum plexcitonic sensing displays a conventional sensitivity 5OPof 31.92 meV while the conventional sensitivity 5^^for frequency shift-based classical sensing is merely 0.66 meV. In other words, quantum plexcitonic sensing is about 48 times more sensitive than its classical counterpart.

[0108] Note that it has been suggested that the conventional sensitivity may not accurately capture the essence of quantum sensing, owing to its potential sensitivity down to a few to single analytes. Following a previous treatment, the number of excitonic particles per unit cell of the gold nanohole array 4TU with 4LM ≥ 1, instead of the population change of excitonic particles N4LM, is adopted as the quantifying descriptor to re-define the sensitivity, which is called quantum sensitivity. The quantum sensitivity for quantum plexcitonic sensing and its classical counterpart are respectively given as:Client Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT 5O O(4R^ ≥ 1) =Ω3(S13a) 4R^

[0109] The obtainedcounterpart is found to be 4LM-dependent, as shown in FIGS.4G-4H. Again, the quantum plexcitonic sensing displays a significantly higher quantum sensitivity ranging from 67 meV to 116 meV, while the quantum sensitivity for classical sensing is much smaller, varying from 0.8 meV to 2.9 meV for the studied number of gold or silica nanoparticles 4LM. To directly compare the quantum plexcitonic sensing versus classical sensing, a normalized quantum sensitivity is used, which is defined as: 5O ΓO(4R^ ≥ 1)Ω3X= O = (S14) 5P (4R^ ≥ 1)N^

[0110] The obtained normalized quantum sensitivity is presented in FIG.4I, suggesting that quantum plexcitonic sensing outcompetes its classical counterpart by a factor of at least 40. It is important to note that, while the classical sensing displays a conventional sensitivity of 0.66 meV and a quantum sensitivity of 2.9 meV for 4LM=0.625, these sensitivities may not be practically achievable owing to the weak correlation between the frequency shift and the excitonic particle population change. Such weak correlation can be easily masked by optical noise and other perturbations in physical systems. White noise addition and Monte Carlo simulations

[0111] In addition to the shot noise because of the particle nature of photons, the most common optical noise can arise from ambient light sources, which is generically called white noise. Herein, additive white Gaussian noise (AWGN) with a particular level of signal-to-noise ratio (SNR) is used to model white noise effects following previously reported methods. AWGN generates a random noise with a frequency-independent uniform power spectral density. The probability of AWGN noise follows a Gaussian distribution with a mean value of zero. It is important to note that, despite the well-defined SNR, the added AWGN noise is random and cannot repeat itself each time, which results in different noisy spectra even with the same SNR. It is because of this that the obtained noisy spectra can give rise to a sensitivity with a certain level of uncertainty. To systematically study the noise-induced sensitivity uncertainty, herein, Monte Carlo simulations are implemented to generate a set of noisy spectra with a given level of SNRClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT for each calculated reflection spectrum in FIGS.4A and 4D. Following previously reported methods, the Lorentzian function is given by: ^(^) =^Y1 + 4(^ − ^^(S15) ∆^ )^^

[0112] In eq. S15, is ^Z thethe full width half maximum. Eq. S15 can be applied to obtain these parameters such as ^Z, ^0 and Δ^0by fitting the calculated spectra in FIG.4D for classical sensing. For the calculated spectra in FIG.5A in quantum plexcitonic sensing, eq. S15 can be modified to a double Lorentzian function to extract ^Z, ^0 and Δ^0 for the pair of plexcitonic peaks.

[0113] To obtain noisy spectra, the reflection spectra in FIGS.4A and 4D are first converted into normalized power spectra. Subsequently, AWGN with a certain level of signal-to-noise ratio (SNR) is added, where SNR is defined as: ^Y^ 54S =^ (S16) ^'

[0114] To comprehensively assesswhite noise, Monte Carlo simulations were employed to generate noisy spectra with different levels of SNR. Specifically, we utilized the built-in MATLAB* function awgn to add AWGN noise to the power spectra converted from FIGS.4A and 4D. For each spectrum, the noise addition process was repeated 20,000 times for a certain level of SNR until all the spectra in FIGS.4A and 4D and all the studied SNR (SNR=1, 2, 3, 5, 8, 10, 15, 20, 30, 40, 50 dB) have been accounted for. The number of noise additions (20,000 times) was determined based on the convergence study of the obtained sensitivity. With all the obtained noisy spectra for both quantum plexcitonic and classical sensing, systematic data analysis was performed to study the SNR-dependent sensitivity and uncertainty, as presented in FIGS.5A-5L.

[0115] While the present teachings have been illustrated with respect to one or more implementations, alterations and / or modifications may be made to the illustrated examples without departing from the spirit and scope of the appended claims. For example, it may be appreciated that while the process is described as a series of acts or events, the present teachings are not limited by the ordering of such acts or events. Some acts may occur in different orders and / or concurrently with other acts or events apart from those described herein. Also, not all process stages may be required to implement a methodology in accordance with one or more aspects or embodiments of the present teachings. It may be appreciated that structural objectsClient Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT and / or processing stages may be added, or existing structural objects and / or processing stages may be removed or modified. Further, one or more of the acts depicted herein may be carried out in one or more separate acts and / or phases. Furthermore, to the extent that the terms “including,” “includes,” “having,” “has,” “with,” or variants thereof are used in either the detailed description and the claims, such terms are intended to be inclusive in a manner similar to the term “comprising.” The term “at least one of” is used to mean one or more of the listed items may be selected. Further, in the discussion and claims herein, the term “on” used with respect to two materials, one “on” the other, means at least some contact between the materials, while “over” means the materials are in proximity, but possibly with one or more additional intervening materials such that contact is possible but not required. Neither “on” nor “over” implies any directionality as used herein. The term “conformal” describes a coating material in which angles of the underlying material are preserved by the conformal material. The term “about” indicates that the value listed may be somewhat altered, as long as the alteration does not result in nonconformance of the process or structure to the illustrated embodiment. The terms “couple,” “coupled,” “connect,” “connection,” “connected,” “in connection with,” and “connecting” refer to “in direct connection with” or “in connection with via one or more intermediate elements or members.” Finally, the terms “exemplary” or “illustrative” indicate the description is used as an example, rather than implying that it is an ideal. Other embodiments of the present teachings may be apparent to those skilled in the art from consideration of the specification and practice of the disclosure herein. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the present teachings being indicated by the following claims.

Claims

Client Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT WHAT IS CLAIMED IS:

1. A molecular sensing device, comprising: a metasurface, comprising a layer of a semiconducting and / or dielectric material disposed onto a layer of electrically conducting material; a metal nanohole array disposed onto the metasurface; and a biological recognition element disposed onto a surface of the metal nanohole array; and wherein: the surface of the metal nanohole array is configured to receive a bioanalyte and a plurality of quantum emitters.

2. The molecular sensing device of claim 1, wherein the semiconducting and / or dielectric material comprises silicon dioxide.

3. The molecular sensing device of claim 1, wherein the electrically conducting material comprises silver.

4. The molecular sensing device of claim 1, wherein the metal nanohole array comprises gold.

5. The molecular sensing device of claim 1, wherein the plurality of quantum emitters comprise gold.

6. The molecular sensing device of claim 5, wherein the plurality of quantum emitters comprise a plurality of nanorods.

7. The molecular sensing device of claim 1, wherein the plurality of quantum emitters comprise a plurality of plasmonic nanoparticles comprising more than one aspect ratio.

8. The molecular sensing device of claim 7, wherein the aspect ratio of the plurality of quantum emitters is from about 1.1 to about 10.

9. The molecular sensing device of claim 1, wherein the metasurface comprises more than one alternating layer of the semiconducting and / or dielectric material and electrically conducting material.Client Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT 10. The molecular sensing device of claim 8, wherein the metasurface comprises from about 2 to about 50 alternating layers of the semiconducting material and electrically conducting material.

11. The molecular sensing device of claim 1, further comprising a spectroscopic instrument.

12. The molecular sensing device of claim 1, further comprising a portable detector.

13. The molecular sensing device of claim 1, wherein the biological recognition element is configured to recognize a communicable disease.

14. The molecular sensing device of claim 1, wherein the bioanalyte corresponds to a specific biological recognition element.

15. The molecular sensing device of claim 1, wherein the bioanalyte comprises a biological medium.

16. A molecular sensing method, comprising: exposing a molecular sensing device to a sample; subjecting the molecular sensing device to light; generating an electromagnetic signal from a reaction between the sample and a surface of the molecular sensing device; analyzing the electromagnetic signal to determine a presence of a target analyte in the sample; analyzing the electromagnetic signal to determine a quantity of the of the target analyte in the sample; and transmitting presence of the target analyte and the quantity of the target analyte; and wherein the molecular sensing device comprises: a metasurface, comprising a layer of a semiconducting and / or dielectric material disposed onto a layer of electrically conducting material; and a metal nanohole array disposed onto the metasurface.

17. The molecular sensing method of claim 16, further comprising introducing a biological recognition element disposed onto a surface of the metal nanohole array, wherein the biological recognition element reacts with the sample.

18. The molecular sensing method of claim 16, wherein sample comprises a biological media.Client Ref: C17711_P17711-02 Attorney Ref: 0184.0263-PCT 19. The molecular sensing method of claim 16, wherein transmitting the presence of the target analyte and the quantity of the target analyte comprises a colorimetric and / or spectroscopical transmission.

20. The molecular sensing method of claim 16, wherein transmitting presence of the target analyte and the quantity of the target analyte comprises a digital transmission to a portable computer medium such as an electronic display, cell phone, tablet, mobile computer, or combination thereof.

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