压电
能量收集
材料科学
节点(物理)
物联网
能量(信号处理)
纳米技术
人工智能
计算机科学
声学
嵌入式系统
物理
复合材料
量子力学
作者
Manjuan Huang,Minglu Zhu,Xiaowei Feng,Zixuan Zhang,Tianyi Tang,Xinge Guo,Tao Chen,Huicong Liu,Lining Sun,Chengkuo Lee
出处
期刊:ACS Nano
[American Chemical Society]
日期:2023-03-20
卷期号:17 (7): 6435-6451
被引量:52
标识
DOI:10.1021/acsnano.2c11366
摘要
The evolution of artificial intelligence of things (AIoT) drastically facilitates the development of a smart city via comprehensive perception and seamless communication. As a foundation, various AIoT nodes are experiencing low integration and poor sustainability issues. Herein, a cubic-designed intelligent piezoelectric AIoT node iCUPE is presented, which integrates a high-performance energy harvesting and self-powered sensing module via a micromachined lead zirconate titanate (PZT) thick-film-based high-frequency (HF)-piezoelectric generator (PEG) and poly(vinylidene fluoride-co-trifluoroethylene) (P(VDF-TrFE)) nanofiber thin-film-based low-frequency (LF)-PEGs, respectively. The LF-PEG and HF-PEG with specific frequency up-conversion (FUC) mechanism ensures continuous power supply over a wide range of 10-46 Hz, with a record high power density of 17 mW/cm3 at 1 g acceleration. The cubic design allows for orthogonal placement of the three FUC-PEGs to ensure a wide range of response to vibrational energy sources from different directions. The self-powered triaxial piezoelectric sensor (TPS) combined with machine learning (ML) assisted three orthogonal piezoelectric sensing units by using three LF-PEGs to achieve high-precision multifunctional vibration recognition with resolutions of 0.01 g, 0.01 Hz, and 2° for acceleration, frequency, and tilting angle, respectively, providing a high recognition accuracy of 98%-100%. This work proves the feasibility of developing a ML-based intelligent sensor for accelerometer and gyroscope functions at resonant frequencies. The proposed sustainable iCUPE is highly scalable to explore multifunctional sensing and energy harvesting capabilities under diverse environments, which is essential for AIoT implementation.
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