Multilevel Printed Wearable Radio-Frequency Intelligent Identification Platform for Object Recognition

• Published in: ACS applied materials & interfaces Vol. 16; no. 37; pp. 49856 - 49867
• Main Authors: Ju, Lu, Yu, Buyun, Chen, Hao, Xiao, Zhida, Xiang, Wei, Zhan, Junlin, Zhang, Chao, Liu, Zhenguo, Tao, Li, Lu, Weibing
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 18-09-2024
• Subjects: Surfaces, Interfaces, and Applications; flexible electronics; additive manufacturing; RFID technology; object identification; reconfigurable antenna
• ISSN: 1944-8244; 1944-8252; 1944-8252
• DOI: 10.1021/acsami.4c06404

As a noncontact target recognition technique, radio-frequency identification (RFID) technology demonstrates attractive potential in constructing human–machine interaction (HMI) systems. However, the current development of RFID technologies in HMI systems is hampered by critical challenges in manufacturing high-performance RFID readers with superior flexibility and wearing comfort. Hence, we propose a multilevel printing strategy to overcome the difficulties in manufacturing high-performance large-scale microwave systems. Compared to traditional processes, the RFID system fabricated by the hybrid additive manufacturing technique exhibits equivalent electromagnetic performance and has obvious advantages in terms of manufacturing cost and environmental friendliness. A printed reconfigurable antenna with intelligent radiation mode is seamlessly integrated with the reader circuit via a “one-step” printing technology. Additionally, through chemical doping and artificial intelligence (AI) prediction, we have developed a modified polydimethylsiloxane (PDMS) encapsulation to miniaturize the system volume and enhance reliability. Electromagnetic and mechanical measurements demonstrated that our flexible RFID platform offers superior reliability and stability during long-term daily use. The RFID platform possesses exceptional capabilities in target positioning and accurate identification, demonstrating unique potential in noncontact sensing and recognition, which are highly demanded by flexible and wearable HMI systems.