Artificial intelligence assisted nanogenerator applications

被引:2
|
作者
Xu, Shumao [1 ]
Manshaii, Farid [1 ]
Xiao, Xiao [1 ]
Chen, Jun [1 ]
机构
[1] Univ Calif Los Angeles, Dept Bioengn, Los Angeles, CA 90095 USA
基金
美国国家科学基金会;
关键词
CONVOLUTIONAL NEURAL-NETWORKS; TRIBOELECTRIC NANOGENERATORS; CLASSIFICATION; FABRICATION; PROGRESS; SENSORS;
D O I
10.1039/d4ta07127a
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Piezoelectric and triboelectric nanogenerators are at the forefront of converting ambient mechanical energy into electricity. These devices have experienced significant advancements in functionality and autonomy through integration with artificial intelligence (AI). This integration not only enhances their performance in autonomous operations by improving mechanical-to-electrical energy conversion efficiency, but also forges new pathways in robotics and intelligent systems. By increasing responsiveness and adaptability, these innovations expand the potential applications of nanogenerators. Looking ahead, the combination of nanogenerators with AI is poised to play a crucial role in developing sustainable, eco-friendly energy solutions. Their dual impact in advancing intelligent systems and promoting environmental sustainability signifies a significant milestone in nanogenerator technology for robotics. This review highlights the essential role of AI in refining nanogenerators, charting a path toward energy autonomy and sustainability.
引用
收藏
页码:832 / 854
页数:23
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