TY - JOUR
T1 - Adaptive infrared thermal camouflage of multi-layer PCMs devices via laser-electric co-modulation driven by neural network
AU - Zhao, Kailin
AU - Guo, Qin
AU - Jiang, Lan
AU - Zhang, Yansong
AU - Jiao, Shuhui
AU - Hu, Jie
AU - Cheng, Qian
AU - Cao, Xun
AU - Han, Weina
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/12
Y1 - 2025/12
N2 - 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.
AB - 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.
KW - Adaptive thermal camouflage system
KW - Emissivity
KW - Laser-electric
KW - Neural network
KW - Phase-change materials
UR - http://www.scopus.com/pages/publications/105019105997
U2 - 10.1186/s43074-025-00199-y
DO - 10.1186/s43074-025-00199-y
M3 - Article
AN - SCOPUS:105019105997
SN - 2662-1991
VL - 6
JO - PhotoniX
JF - PhotoniX
IS - 1
M1 - 42
ER -