Nonvolatile High-Contrast Whole Long-Wave Infrared Emissivity Switching Based on In₃SbTe₂

Switchable thermal emission in the long-wave infrared (LWIR, 8–14 μm) range is of great significance in applications like thermal detection, radiative cooling, and infrared camouflage. Existing methods for switchable LWIR emission apply photonic structures incorporating smart materials, which either require a continuous input power or produce limited emissivity contrasts. In this study, two nonvolatile high-contrast switchable emitters over the whole LWIR range have been proposed utilizing the drastic permittivity change of In3SbTe2 (IST) upon crystallization. One switchable emitter exhibits negative differential emissivity (ΔεN,8–14 μm ≈ −0.75, emissivity decreases with temperature) and is experimentally applied to infrared camouflage; the other shows positive differential emissivity (ΔεP,8–14 μm ≈ 0.83, emissivity increases with temperature) and demonstrates its capability in thermal management. The demonstrated characteristics of IST provide a new route for realizing differential emissivity and make the IST-based emitters highly promising for applications such as infrared camouflage and thermal management

Histograms and Gaussian distribution characteristics of the crop canopy reflectance data at different spatial scales before and after data analysis and correction with the new method in Labudalin farm of Hailaer Farming Cultivate Bureau in Inner Mongolia, China.

<p>Histograms and Gaussian distribution characteristics of the crop canopy reflectance data at different spatial scales before and after data analysis and correction with the new method in Labudalin farm of Hailaer Farming Cultivate Bureau in Inner Mongolia, China.</p

Location of the experimental fields.

<p>(A): Location of the experimental field in Labudalin farm of Hailaer Farming Cultivate Bureau in Inner Mongolia, China. (B): Location of the experimental field in Shunyi District and Changping District of Beijing, China.</p

Histograms and Gaussian distribution characteristics of the crop canopy reflectance data at different spatial scales before and after data analysis and correction with the new method in Shunyi District and Changping District of Beijing, China.

<p>Histograms and Gaussian distribution characteristics of the crop canopy reflectance data at different spatial scales before and after data analysis and correction with the new method in Shunyi District and Changping District of Beijing, China.</p

Statistical characteristics of the crop canopy reflectance data at different spatial scales before and after data analysis and correction with the new method in Shunyi District and Changping District of Beijing, China.

<p>Statistical characteristics of the crop canopy reflectance data at different spatial scales before and after data analysis and correction with the new method in Shunyi District and Changping District of Beijing, China.</p

Statistical characteristics of the crop canopy reflectance datasets at different spatial scales before and after data analysis and correction with the new method in Labudalin farm of Hailaer Farming Cultivate Bureau in Inner Mongolia, China.

<p>Statistical characteristics of the crop canopy reflectance datasets at different spatial scales before and after data analysis and correction with the new method in Labudalin farm of Hailaer Farming Cultivate Bureau in Inner Mongolia, China.</p