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With advancements in radar detection and electromagnetic (EM) communication technologies, intelligentizing EM functional materials (EFMs) and endowing them with dynamic responsiveness across multi-spectral ranges, along with the ability to perceive and adapt to complex operation environments, is of significant importance. This article provides a comprehensive review of the recent progress in intelligent EFMs. It begins with the fundamentals of intelligent EFMs, with an emphasis on their EM response mechanisms and basic functions. The motivation and necessity of developing intelligent EFMs are then discussed. Thereafter, new advances, particularly in the design of intelligent EFMs for various applications, including EM communication systems, EM protection platforms, sensors, robots, energy harvesting devices, wearable electronics, healthcare, and environmental management, are highlighted. Lastly, this review concludes with an outlook on future directions, critical challenges to address, and possible solutions for intelligent EFMs.
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http://dx.doi.org/10.1002/adma.202510212 | DOI Listing |
Adv Mater
August 2025
College of Smart Materials and Future Energy, State Key Laboratory of Coatings for Advanced Equipment, Fudan University, Shanghai, 200438, P. R. China.
With advancements in radar detection and electromagnetic (EM) communication technologies, intelligentizing EM functional materials (EFMs) and endowing them with dynamic responsiveness across multi-spectral ranges, along with the ability to perceive and adapt to complex operation environments, is of significant importance. This article provides a comprehensive review of the recent progress in intelligent EFMs. It begins with the fundamentals of intelligent EFMs, with an emphasis on their EM response mechanisms and basic functions.
View Article and Find Full Text PDFIEEE Trans Syst Man Cybern B Cybern
April 2010
Intelligent Systems Research Laboratory, Infolab21, Lancaster University, Lancaster, UK.
A new technique to the design and use of inferential sensors in the process industry is proposed in this paper, which is based on the recently introduced concept of evolving fuzzy models (EFMs). They address the challenge that the modern process industry faces today, namely, to develop such adaptive and self-calibrating online inferential sensors that reduce the maintenance costs while keeping the high precision and interpretability/transparency. The proposed new methodology makes possible inferential sensors to recalibrate automatically, which reduces significantly the life-cycle efforts for their maintenance.
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