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Chromatic forecasting hydrogels for anti-icing applications

Author

Listed:
  • Wenxuan Hou

    (Beijing Institute of Technology)

  • Xiaofei Chen

    (Beijing Institute of Technology)

  • Dan Wang

    (Beijing Institute of Technology
    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
    Beijing Institute of Technology)

  • Ye Xu

    (Beihang University)

  • Zhiyuan He

    (Beijing Institute of Technology
    Beijing Institute of Technology)

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.

Suggested Citation

  • Wenxuan Hou & Xiaofei Chen & Dan Wang & Yanyan Cao & Hongzhong Du & Gengchen Li & Zhuoheng Gan & Yifei Yan & Chong Gao & Fang Hu & Zhengxu Cai & Ye Xu & Zhiyuan He, 2025. "Chromatic forecasting hydrogels for anti-icing applications," Nature Communications, Nature, vol. 16(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-58806-2
    DOI: 10.1038/s41467-025-58806-2
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    References listed on IDEAS

    as
    1. Stoyanov, D.B. & Nixon, J.D. & Sarlak, H., 2021. "Analysis of derating and anti-icing strategies for wind turbines in cold climates," Applied Energy, Elsevier, vol. 288(C).
    2. Mohamed S. Abdalzaher & Hussein A. Elsayed & Mostafa M. Fouda & Mahmoud M. Salim, 2023. "Employing Machine Learning and IoT for Earthquake Early Warning System in Smart Cities," Energies, MDPI, vol. 16(1), pages 1-22, January.
    3. Steven J. Roeters & Thaddeus W. Golbek & Mikkel Bregnhøj & Taner Drace & Sarah Alamdari & Winfried Roseboom & Gertjan Kramer & Tina Šantl-Temkiv & Kai Finster & Jim Pfaendtner & Sander Woutersen & Tho, 2021. "Ice-nucleating proteins are activated by low temperatures to control the structure of interfacial water," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    4. Tom R. Andersson & J. Scott Hosking & María Pérez-Ortiz & Brooks Paige & Andrew Elliott & Chris Russell & Stephen Law & Daniel C. Jones & Jeremy Wilkinson & Tony Phillips & James Byrne & Steffen Tiets, 2021. "Seasonal Arctic sea ice forecasting with probabilistic deep learning," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    5. Owusu, Kwadwo Poku & Kuhn, David C.S. & Bibeau, Eric L., 2013. "Capacitive probe for ice detection and accretion rate measurement: Proof of concept," Renewable Energy, Elsevier, vol. 50(C), pages 196-205.
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