Functionalized gold nanoparticle enhanced nanorod hyperbolic metamaterial biosensor for highly sensitive detection of carcinoembryonic antigen.

Hyperbolic metamaterial (HMM) biosensors based on metals have superior performance in comparison with conventional plasmonic biosensors in the detection of low concentrations of molecules. In this study, a nanorod HMM (NHMM) biosensor based on refractive index changes for carcinoembryonic antigen (CEA) detection is developed using secondary antibody modified gold nanoparticle (AuNP-Ab2) nanocomposites as signal amplification element for the first time. Numerical analysis based on finite element method is conducted to simulate the perturbation of the electric field of bulk plasmon polariton (BPP) supported by a NHMM in the presence of a AuNP. The simulation reveals an enhancement of the localized electric field, which arises from the resonant coupling of BPP to the localized surface plasmon resonance supported by AuNPs and is beneficial for the detection of changes of the refractive index. Furthermore, the AuNP-Ab2 nanocomposites-based NHMM (AuNP/Ab2-NHMM) biosensor enables CEA detection in the visible and near-infrared regions simultaneously. The highly sensitive detection of CEA with a wide linear range of 1-500 ng/mL is achieved in the near-infrared region. The detectable concentration of the AuNP/Ab2-NHMM biosensor has a 50-fold decrease in comparison with a NHMM biosensor. A low detection limit of 0.25 ng/mL (1.25 pM) is estimated when considering a noise level of 0.05 nm as the minimum detectable wavelength shift. The proposed method achieves high sensitivity and good reproducibility for CEA detection, which makes it a novel and viable approach for biomedical research and early clinical diagnostics.

Sensitivity investigation of a biosensor with resonant coupling of propagating surface plasmons to localized surface plasmons in the near infrared region.

Gold nanoparticles (AuNPs) can be used to improve the performance of propagating surface plasmon resonance (PSPR) refractive index sensors. The resonant coupling effect between PSPR and localized surface plasmon resonance (LSPR) supported by AuNPs on sensitivity remains to be elucidated in terms of evanescent field intensity and distribution. In this study, we directly compare the sensitivity of the PSPR sensor and the resonant coupling mode between the PSPR and LSPR sensors in the wavelength scanning mode. The sensitivity of PSPR can be significantly improved in the near-infrared region excitation wavelength. 1,6-Hexanedithiol was used to achieve a AuNP modified gold film (GF-AuNP). The PSPR excited by the prism coupling mechanism can effectively stimulate LSPR supported by AuNPs in the GF-AuNP, and then resonant coupling is generated. Compared with PSPR, the resonant coupling mode shows a decrease in penetration depth by 28 times and an increase in the surface electric field intensity by 4.6 times in the numerical simulations. The decrease in the penetration depth in the GF-AuNP is made at the expense of bulk sensitivity. The biosensing sensitivity of the GF-AuNP shows up to 7-fold improvement in the carcinoembryonic antigen immunoassay and the GF-AuNP is proven to be a better biosensor. The experimental measurements are in excellent agreement with the theoretical model. This study can be also considered as a guide for the design of plasmonic sensors for detecting multiple substances at different scales, such as cells and proteins.

Color Printing and Encryption with Polarization-Switchable Structural Colors on All-Dielectric Metasurfaces.

Metasurface-based structural color with high resolution is promising for color printing and encryption. However, achieving tunable structural colors in practical applications is challenging owing to the immutability after the fabrication of metasurfaces. Herein, we proposed the polarization-switchable dielectric metasurfaces with full colors. The colorful images can be switched on/off by controlling the polarization of incident light. For the nanorods metasurfaces, all colors turned to black in the "off" mode because of the near-zero reflection, and the uniform black was advantageous for designing encryption applications. For the nanocrosses metasurfaces, colors reversed in two different "on" modes and images hidden in the "off" mode. With the polarization-sensitive metasurfaces, a fish-bird image, an overlapped dual-channel image, and a green-red heart image were obtained, respectively. The demonstrations can be applied to dynamic displays, optical cryptography, multichannel imaging, and optical data storage.

Coupling plasmon-waveguide resonance and multiple plasma modes in hyperbolic metamaterials for high-performance sensing.

A sensor based on plasmon-waveguide resonance (PWR) exhibits an impressive narrow linewidth and has attracted extensive attention in plasmon label-free sensing. However, the low surface electric field intensity limits the detection ability of biomolecules, where the refractive index changes are restricted at the sensor surface. In this study, we study the coupling of PWR and multiple plasma modes in a hyperbolic metamaterial (HMM), combining narrow linewidth and electric field enhancement advantages. The PWR-HMM sensor includes a gold film, lossless dielectric layer, and metal/dielectric multilayer HMM array composed of 2-layer Au/Al2O3stacks. The evanescent field of PWR is used to excite multiple plasma modes in the HMM. The figure of merit of the proposed structure reaches 5417/RIU owing to the existence of lossless dielectric layer, which is 11.7 times than the conventional gold film structure. The maximum bulk sensitivity of the PWR-HMM sensor was 43 000 nm/RIU. In comparison with PWR, the surface electric field intensity and the surface sensitivity of PWR-HMM increase by four and two times, respectively. Furthermore, comparing the sensing performance of the PWR-HMM sensor and PWR-nanoparticle (NP) sensor (coupling PWR and localized surface plasmon resonance), it was found that PWR-HMM has 20% higher surface sensitivity than the PWR-NP. A sensing mechanism coupling PWR and multiple plasma modes in the HMMs opens a gate to significantly improve the PWR sensors performance, which is expected to be used to resolve urgent issues in biological, medical and clinical applications.

Tunable structural colors generated by hybrid Si3N4 and Al metasurfaces.

Metasurfaces with the capability of spectrum manipulation at subwavelength can generate structural colors. However, their practical applications in dynamic displays are limited because their optical performance is immutable after the fabrication of the metasurfaces. In this study, we demonstrate a color-tunable metasurface using numerical analysis. Moreover, we select a low-refractive-index dielectric material, Si3N4, which leaks the electric field to its surroundings. We investigate the potencial of these metasurfaces by simulations to achieve color-tuneable devices with encrypted watermarks. This modulation of colors can be applied to encrypted watermarks, anti-counterfeiting, and dynamic displays.

Efficient inverse design and spectrum prediction for nanophotonic devices based on deep recurrent neural networks.

The development of nanophotonic devices has presented a revolutionary means to manipulate light at nanoscale. How to efficiently design these devices is an active area of research. Recently, artificial neural networks (ANNs) have displayed powerful ability in the inverse design of nanophotonic devices. However, there is limited research on the inverse design for modeling and learning the sequence characteristics of a spectrum. In this work, we propose a deep learning method based on an improved recurrent neural network to extract the sequence characteristics of a spectrum and achieve inverse design and spectrum prediction. A key feature of the network is that the memory or feedback loops it comprises allow it to effectively recognize time series data. In the context of nanorods hyperbolic metamaterials, we demonstrated the high consistency between the target spectrum and the predicted spectrum, and the network learned the deep physical relationship concerning the structural parameter changes reflected on the spectrum. The effectiveness of our approach is also tested by user-drawn spectra. Moreover, the proposed model is capable of predicting an unknown spectrum based on a known spectrum with only 0.32% mean relative error. The prediction model may be helpful to predict data beyond the detection limit. We propose this versatile method as an effective and accurate alternative to the application of ANNs in nanophotonics, paving way for fast and accurate design of desired devices.

Ultra-narrowband near-infrared tunable two-dimensional perfect absorber for refractive index sensing.

An ultra-narrow-bandwidth near-infrared perfect plasmonic absorber with a periodic structure composed of metal-insulator-metal configuration is numerically designed and analyzed for a refractive index sensor. A perfect absorptivity of 99.99% and a rather narrow bandwidth of 2 nm are observed in the near-infrared wave band when the light is vertically incident in the structure. The ultra-high absorption and ultra-narrow bandwidth are explained as local surface plasmon resonance stimulated in the structure. The absorber is put into use as a plasmonic refractive index sensor with wavelength sensitivity as high as 1500 nm/RIU and figure of merit as high as 750, which significantly surpass those of many plasmonic sensors proposed in the past few decades. The designed absorber is tunable by changing geometry parameters. Because of the excellent sensing properties mentioned above, the proposed structure can be widely applied in fields such as photodetectors, biosensors, and chemical molecule detection.

Design of high-performance plasmonic nanosensors by particle swarm optimization algorithm combined with machine learning.

Metallic plasmonic nanosensors that are ultra-sensitive, label-free, and operate in real time hold great promise in the field of chemical and biological research. Conventionally, the design of these nanostructures has strongly relied on time-consuming electromagnetic simulations that iteratively solve Maxwell's equations to scan multi-dimensional parameter space until the desired sensing performance is attained. Here, we propose an algorithm based on particle swarm optimization (PSO), which in combination with a machine learning (ML) model, is used to design plasmonic sensors. The ML model is trained with the geometric structure and sensing performance of the plasmonic sensor to accurately capture the geometry-sensing performance relationships, and the well-trained ML model is then applied to the PSO algorithm to obtain the plasmonic structure with the desired sensing performance. Using the trained ML model to predict the sensing performance instead of using complex electromagnetic calculation methods allows the PSO algorithm to optimize the solutions fours orders of magnitude faster. Implementation of this composite algorithm enabled us to quickly and accurately realize a nanoridge plasmonic sensor with sensitivity as high as 142,500 nm/RIU. We expect this efficient and accurate approach to pave the way for the design of nanophotonic devices in future.

A near-ideal solar selective absorber with strong broadband optical absorption from UV to NIR.

A near-ideal solar absorber, which is composed of a metal nanowire array and a planar multilayer system, is proposed and investigated. Both numerical and analytical results show that the proposed nanostructure can achieve over 90% optical absorption throughout the wavelength range of 300-1909 nm due to the coupled effect of multiple resonance modes, and can maintain a good absorption stability over a wide incident angle regardless of the polarization states. Meanwhile, for practical applications, the total photothermal conversion efficiency can reach 95.57% at operating temperature of 373.15 K, which is particularly useful in solar energy harvesting. The absorption performance is also strongly dependent on the diameter and height of nanowire as well as the thicknesses of dielectric layers, enabling the further improvement of both the operating bandwidth and absorption efficiency. Moreover, by adjusting the period of the multilayer or nanowire materials, the selective absorption properties of this nanostructure can be flexibly controlled to satisfy more spectral requirements. These features make the presented designs hold promise for a series of solar-dependent optical applications, such as photothermal energy generation and thermal emitters.

Ultrabroadband light absorption based on photonic topological transitions in hyperbolic metamaterials.

Photonic topological transitions (PTTs) in metamaterials open up a novel approach to design a variety of high-performance optical devices and provide a flexible platform for manipulating light-matter interactions at nanoscale. Here, we present a wideband spectral-selective solar absorber based on multilayered hyperbolic metamaterial (HMM). Absorptivity of higher than 90% at normal incidence is supported over a wide wavelength range from 300 to 2215 nm, due to the topological change in the isofrequency surface (IFS). The operating bandwidth can be flexibly tailored by adjusting the thicknesses of the metal and dielectric layers. Moreover, the near-ideal absorption performance can be retained well at a wide angular range regardless of the incident light polarization. These features make the proposed design hold great promise for practical applications in energy harvesting.

Tunable optical angular selectivity in hyperbolic metamaterial via photonic topological transitions.

An ultra-narrow angular optical transparency window based on photonic topological transition (PTT) is theoretically and numerically investigated in a low-loss hyperbolic metamaterial (HMM) platform, which consists of aligned metallic nanowires embedded indielectric host matrices. Our results indicate that, near the transition point of PTT, the designed system exhibits high-efficiency optical angular selectivity close to normal incidence by tailoring the topology of metamaterial's equi-frequency surface (EFS). Moreover, the operating wavelength (λ0) is flexibly tunable by selecting appropriate material and geometrical parameters, which provides significant guidance for the later experimental design. Our method is further applied to super-resolution imaging, with a resolution of at least λ0/4 and over a significant distances (>12λ0). The HMM-supported angularly selective system could find promising applications for high-efficiency light manipulation and lensless on-chip imaging.