Abstract

There are great concerns for sensing using flexible acoustic wave sensors and lab-on-a-chip, as mechanical strains will dramatically change the sensing signals (e.g., frequency) when they are bent during measurements. These strain-induced signal changes cannot be easily separated from those of real sensing signals (e.g., humidity, ultraviolet, or gas/biological molecules). Herein, we proposed a new strategy to minimize/eliminate the effects of mechanical bending strains by optimizing off-axis angles between the direction of bending deformation and propagation of acoustic waves on curved surfaces of layered piezoelectric film/flexible glass structure. This strategy has theoretically been proved by optimization of bending designs of off-axis angles and acoustically elastic effect. Proof-of-concept for humidity and ultraviolet-light sensing using flexible SAW devices with negligible interferences are achieved within a wide range of bending strains. This work provides the best solution for achieving high-performance flexible acoustic wave sensors under deformed/bending conditions.

Details

Title
Strategy to minimize bending strain interference for flexible acoustic wave sensing platform
Author
Zhou, Jian 1   VIAFID ORCID Logo  ; Ji, Zhangbin 1   VIAFID ORCID Logo  ; Guo, Yihao 1 ; Liu, Yanghui 1 ; Zhuo, Fengling 1 ; Zheng, Yuanjin 2 ; Gu, Yuandong(Alex) 3 ; Fu, YongQing 4 ; Duan, Huigao 5   VIAFID ORCID Logo 

 Hunan University, College of Mechanical and Vehicle Engineering, Changsha, China (GRID:grid.67293.39) 
 Nanyang Technological University, School of Electrical and Electronical Engineering, Singapore, Singapore (GRID:grid.59025.3b) (ISNI:0000 0001 2224 0361) 
 Shanghai Industrial μTechnology Research Institute (SITRI), Shanghai, China (GRID:grid.59025.3b) 
 Northumbria University, Faculty of Engineering and Environment, Newcastle upon Tyne, United Kingdom (GRID:grid.42629.3b) (ISNI:0000000121965555) 
 Hunan University, College of Mechanical and Vehicle Engineering, Changsha, China (GRID:grid.67293.39); Hunan University, Greater Bay Area Institute for Innovation, Guangzhou, China (GRID:grid.67293.39) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
23974621
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2716791582
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.