Electrostatically Self‐Powered Intelligent Force Sensor With Tunable Performance via Mechanically Guided 3D Morphing

Read full text
Authors: Dongik Kam, Dayeon Jang, Hee Jae Hwang, Sunmin Jang, Sumin Cho, Donghan Lee, Donghyeon Yoo, Jun-Sang Yoon, Seong Jin Lee, Jongwoo Kim, Kyoung Je, Dongwhi Choi
Cited by: 2
References: 46

Abstract

ABSTRACT Sensors that capture diverse environmental information are crucial in the elemental technology driving the Fourth Industrial Revolution. However, the trade‐off between sensitivity and working range exhibited by conventional sensors results in limitations when the target stimuli deviate from their predesigned specifications. Thus, single sensors with adjustable performance characteristics must be developed to satisfy functionality requirements in diverse environments. In this study, a Tunable Usability‐Nourished Electrostatic‐based self‐powered force sensor (TUNE sensor) is introduced to overcome the limitations of the fixed detection performance of a single sensor. The tunable sensing performance of the TUNE sensor is achieved via mechano‐guided geometrical adaptation of its three‐dimensional (3D) structure formed via mechanical buckling. Continuous and reversible shape changes in the 3D structure allow modulation of the stiffness of the TUNE sensor, resulting in tunable sensing performance (sensitivity of 0.53~1.08 nC/N and working range of 1.01~0.35 N). The effectiveness of the tunable sensing performance is demonstrated through its implementation in a reconfigurable electronic scale and robotic sensing. This mechano‐guided geometrical adaptation strategy offers the potential for extending the use of sensors in multivariate environments and providing new opportunities for intelligent sensing systems in various applications. image

Fields of Study & Subjects

Advanced Sensor and Energy Harvesting Materials Soft Robotics and Applications Shape Memory Alloy Transformations

Publication details

Journal / source
EcoMat
Publisher
Wiley
Volume
8
Issue
2
Publication date
1 February 2026
Language
EN