Chromatic forecasting hydrogels for anti-icing applications

Wenxuan Hou, Xiaofei Chen, Dan Wang, Yanyan Cao, Hongzhong Du, Gengchen Li, Zhuoheng Gan, Yifei Yan, Chong Gao, Fang Hu, Zhengxu Cai, Ye Xu and Zhiyuan He ()
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Wenxuan Hou: Beijing Institute of Technology
Xiaofei Chen: Beijing Institute of Technology
Dan Wang: Beijing Institute of Technology
Yanyan Cao: Beijing Institute of Technology
Hongzhong Du: Beijing Institute of Technology
Gengchen Li: Beijing Institute of Technology
Zhuoheng Gan: Southern Medical University
Yifei Yan: Beihang University
Chong Gao: Beijing Institute of Technology
Fang Hu: Southern Medical University
Zhengxu Cai: Beijing Institute of Technology
Ye Xu: Beihang University
Zhiyuan He: Beijing Institute of Technology

Nature Communications, 2025, vol. 16, issue 1, 1-9

Abstract: Abstract Icing forecast provides advanced notification, enabling preemptive anti-icing treatments to prevent facility damage and minimize economic losses from unexpected icing events. However, in real-world environments and practical applications, current technologies struggle to accurately predict ice formation on solid surfaces. This difficulty arises from the random and unpredictable nature of ice nucleation, influenced by variable weather conditions, diverse ice-nucleating agents, complex surface properties, and uncertain material defects or contamination. Herein, inspired by the role of ice-nucleating proteins (INPs) in cellular responses to low-temperature stress, we develop an innovative icing forecast hydrogel (IFH) device that encapsulates INPs. By simply regulating the INP content, the advance forecast time for icing can be precisely controlled over a wide temperature range from −6 to −28 oC. To enhance forecasting accuracy, a color-coded grading system is implemented. The anti-icing application of this IFH device on wind turbines has proven its effectiveness, as it activated the de-icing system 70 min prior to real ice accretion on wind turbine blade, resulting in an additional 1898 kWh of electricity generated over two h. Our study presents a strategy for icing forecast, demonstrating its practical utility in wind power field and its potential for various anti-icing applications.

Date: 2025
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DOI: 10.1038/s41467-025-58806-2

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