Preparation of Flexible Wavelength-Selective Metasurface for Infrared Radiation Regulation

Semimetal-dielectric-metal metasurface for infrared camouflage with high-performance energy dissipation in non-atmospheric transparency window

The development of novel camouflage technologies is of great significance, exerting an impact on both fundamental science and diverse military and civilian applications. Effective camouflage aims to reduce the recognizability of an object, making it to effortlessly blend with the environment. For infrared camouflage, it necessitates precise control over surface emissivity and temperature to ensure that the target blends effectively with the surrounding infrared background. This study presents a semimetal-dielectric-metal metasurface emitter engineered for the application of infrared camouflage. The metasurface, with a total thickness of only 545 nm, consists of a Bi micro-disk array and a continuous ZnS and Ti film beneath it. Unlike conventional metal-based metasurface design, our approach leverages the unique optical properties of Bi, achieving an average emissivity of 0.91 in the 5-8 μm non-atmospheric transparency window. Experimental results indicate that the metasurface emitter achieves lower radiation and actual temperatures compared to those observed in comparative experiments, highlighting its superior energy dissipation and thermal stability. The metasurface offers advantages such as structural simplicity, cost-effectiveness, angular insensitivity, and deep-subwavelength features, rendering it suitable for a range of applications including military camouflage and anti-counterfeiting, with potential for broad deployment in infrared technologies.

PISC-Net: A Comprehensive Neural Network Framework for Predicting Metasurface Infrared Emission Spectra

Multifunctional metasurfaces have exhibited extensive potential in various fields, owing to their unparalleled capacity for controlling electromagnetic wave characteristics. The precise resolution is achieved through numerical simulation in conventional metasurface design methodologies. Nevertheless, the simulations using these approaches are inherently computationally costly. This paper proposes the Physical Insight Self-Correcting Convolutional Network (PISC-Net), which enables rapid prediction of infrared radiation spectra of metasurfaces with remarkable generalization capacity. In contrast to preceding prediction networks, we have enhanced the cognitive ability of the network to recognize physical mechanisms by designing parameter-communication modules and integrating a priori knowledge grounded in the parameter association mechanism. Additionally, we proposed an effective strategy for constructing data sets that facilitate precise tuning of absorption bands in the entire spectral range (3-14 μm) and serves to reduce the costs associated with data set development. Transfer learning is employed to obtain precise predictions for large-period metasurfaces from limited data sets. This approach demonstrates that a network trained exclusively on simulation data could predict experimental outcomes accurately, as proved by the comparative analysis between simulation, experimental testing, and prediction results. The average mean square error is less than 4%.

Controlling thermal emission with metasurfaces and its applications

Thermal emission caused by the thermal motion of the charged particles is commonly broadband, un-polarized, and incoherent, like a melting pot of electromagnetic waves, which makes it unsuitable for infrared applications in many cases requiring specific thermal emission properties. Metasurfaces, characterized by two-dimensional subwavelength artificial nanostructures, have been extensively investigated for their flexibility in tuning optical properties, which provide an ideal platform for shaping thermal emission. Recently, remarkable progress was achieved not only in tuning thermal emission in multiple degrees of freedom, such as wavelength, polarization, radiation angle, coherence, and so on but also in applications of compact and integrated optical devices. Here, we review the recent advances in the regulation of thermal emission through metasurfaces and corresponding infrared applications, such as infrared sensing, radiative cooling, and thermophotovoltaic devices.

An elliptical nanoantenna array plasmonic metasurface for efficient solar energy harvesting

Plasmonic metasurfaces with subwavelength nanoantenna arrays have attracted much attention for their ability to control and manage optical properties. Solar absorbers are potential candidates for effectively converting photons into heat and electricity. This study introduces a novel ultrathin metasurface solar absorber employing elliptical-shaped nanoantenna arrays. We theoretically and numerically demonstrate a near-perfect broadband absorber with over 90% absorption efficiency in a wide range of wavelengths of 300-2500 nm, using finite element (FEM) and finite-difference time-domain (FDTD) methods. The proposed nanostructure configuration enhances light absorption by exciting localized surface plasmon resonances (LSPRs) between elliptical-shaped nanoantenna gaps at many wavelengths, maintaining stability at wide incident angles and insensitivity to light polarization. Compared to other state-of-the-art absorbers with a thickness of less than 300 nm, the designed nanostructure with 260 nm thickness achieves over 90% optical absorption across a broad range of wavelengths of 300-1116 nm in air (or vacuum) environments and performs effectively under water conditions for solar energy harvesting in a range of wavelengths of 300-1436 nm, and therefore can serve as a solar evaporator. Combining refractory plasmonic titanium nitride (TiN) and semiconductor gallium nitride (GaN) nanostructures holds great potential for efficient optoelectronic and photocatalytic applications, especially in harsh and high-temperature environments like thermophotovoltaic systems. The TiN-based metasurface absorber, with its ultrathin nanostructure and suitable spectral absorption in ultraviolet-visible-infrared spectra, offers scalability and cost-effectiveness. The findings in this work will deepen our understanding of LSPRs and pave a novel path for efficient solar energy conversion.