Implementing of infrared camouflage with thermal management based on inverse design and hierarchical metamaterial

Abstract

Infrared camouflage is an effective technique to avoid many kinds of target detection by detectors in the infrared band. For a high-temperature environment, thermal management of selective emission is crucial to dissipate heat in the mid-infrared non-atmospheric window (5–8 μm). However, it still remains challenges for balancing infrared camouflage and thermal management. Here, we experimentally demonstrate a multilayer film structure (MFS) for infrared camouflage with thermal management. Combining the ideal emission spectrum and genetic algorithm (GA), the inverse-design MFS containing 7 layers of five materials (SiO2, Ge, ZnS, Pt and Au) has been designed. Based on the hierarchical metamaterial, the optimized MFS has high performance of infrared camouflage to against the lidar detection in the near-infrared band. The experimental results reveal the high compatible efficiency among thermal camouflage (ε 3–5μm = 0.21, ε 8–14μm = 0.16), laser stealth (ε 1.06μm = 0.64, ε 1.55μm = 0.90, ε 10.6μm = 0.76) and thermal management (ε 5–8μm = 0.54). Therefore, the proposed MFSs are attractive as basic building block of selective emitter, for the application of advanced photonics such as radiative cooling, infrared camouflage, and thermal emission.

Bicolor Regulation of an Ultrathin Absorber in the Mid-Wave Infrared and Long-Wave Infrared Regimes

“…Most objects outwardly radiate electromagnetic waves in the MIR band like a blackbody. According to the Stefan–Boltzmann law, the temperature of an object can be measured by detecting the radiation power within a specific band , T r = P − 1 ( ε IR , T ) where T r represents the temperature obtained using the inverse function of the blackbody radiation spectrum, P represents the radiation power detected by an IR detector and corresponds to the radiation power radiated by a blackbody at temperature T , and ε IR represents the emissivity of the IR detector in the operating band; for an IR camera, ε IR = 1. The detection power of an IR imager is generally determined by the radiation emitted from the object and that reflected from the environment: P ( ε , T ) = P rad ( ε , T ) + P ref ( ε , ε normala , T normala ) = ε ( λ ) I BB ( T ) + [ 1 − ε false( λ false) ] ε a ( λ ) I BB ( T normala ) where ε and ε a represent the emissivities of the object and ambient environment, respectively; T and T a represent the temperatures of the object and ambient environment, respectively; and I BB represents the blackbody irradiance at the corresponding temperature.…”

“…Most objects outwardly radiate electromagnetic waves in the MIR band like a blackbody. According to the Stefan−Boltzmann law, the temperature of an object can be measured by detecting the radiation power within a specific band46,47…”

Machine Learning Aided Design and Optimization of Thermal Metamaterials

“…A thermal camouflage device possesses the capability to render a hot object visually indistinguishable from the background temperature, creating the illusion of being as cold as the surroundings. In the study conducted by Jiang et al, 244 a multilayer film structure was optimized for infrared camouflage by employing the Genetic Algorithm (see Figure 25a). The GA is initialized with 1000 individuals, each of them is encoded with eight materials (five transparent materials in the infrared band including SiO 2 , Ge, ZnS, Si, and Ge 2 Sb 2 Te 5 , and three metals Au, Pt, and Ag) the thicknesses of eight layers (see Figure 25b).…”

“…(e) IR image of the optimized device heated at 60 °C with the background temperature of 20 °C. Reproduced with permission from ref . Copyright 2023 De Gruyter.…”

Light-manipulated phase change materials for multi-functional thermal camouflage

“…There are two intuitive ways to realize thermal camouflage by tuning temperature and emissivity. Some thermal conductive metamaterials have achieved thermal camouflage for the object through modified thermal conduction methods 7 , including but not limited to transformation thermotics method 8,9 , the scattering cancellation method 10,11 , and temperature-dependent material 12 . However, the effective material parameters (thermal conductivity, mass density, heat capacity) of conductive thermal metamaterials are not easily adjustable that restricts the performance and applications.…”