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<p>Infrared thermal camouflage technologies are vital for enhancing the survivability of objects by altering their infrared radiation properties. However, existing solutions often fall short in adaptability and rapid responsiveness to dynamic environmental conditions, limiting their practical applicability. To overcome these challenges, we present an innovative approach combining ultrafast laser-induced non-volatile phase-change Ge<sub>2</sub>Sb<sub>2</sub>Te<sub>5</sub> (GST) voxel-crystallized units with electrically tunable volatile VO<sub>2</sub> layers. This integration enables precise, continuous control of infrared emissivity across a wide range of 0.14 to 0.98, effectively encompassing the emissivity of most materials. A neural network-based closed-loop system is employed for sensing, intelligent decision-making, and execution, achieving real-time thermal radiation matching between the target and its environment with a response speed of 3&#xa0;°C/s and an accuracy of ± 1&#xa0;°C. This strategy significantly enhances the adaptability of thermal camouflage in complex environments, paving the way for practical, dynamic thermal stealth applications.</p>

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Adaptive infrared thermal camouflage of multi-layer PCMs devices via laser-electric co-modulation driven by neural network

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月16日

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  • Kailin Zhao,
  • Qin Guo,
  • Lan Jiang,
  • Yansong Zhang,
  • Shuhui Jiao,
  • Jie Hu,
  • Qian Cheng,
  • Xun Cao,
  • Weina Han

摘要

Infrared thermal camouflage technologies are vital for enhancing the survivability of objects by altering their infrared radiation properties. However, existing solutions often fall short in adaptability and rapid responsiveness to dynamic environmental conditions, limiting their practical applicability. To overcome these challenges, we present an innovative approach combining ultrafast laser-induced non-volatile phase-change Ge2Sb2Te5 (GST) voxel-crystallized units with electrically tunable volatile VO2 layers. This integration enables precise, continuous control of infrared emissivity across a wide range of 0.14 to 0.98, effectively encompassing the emissivity of most materials. A neural network-based closed-loop system is employed for sensing, intelligent decision-making, and execution, achieving real-time thermal radiation matching between the target and its environment with a response speed of 3 °C/s and an accuracy of ± 1 °C. This strategy significantly enhances the adaptability of thermal camouflage in complex environments, paving the way for practical, dynamic thermal stealth applications.