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February 11, 2026EcoMat2 citationsOpen Access

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

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DKDongik KamDJDayeon JangHHHee Jae Hwang

Key Points

  • To develop a self-powered force sensor with tunable characteristics for diverse environmental conditions.
  • Introduced a Tunable Usability-Nourished Electrostatic (TUNE) sensor design.
  • Achieved tunable performance via mechano-guided geometrical adaptation of a 3D structure.
  • Utilized mechanical buckling for continuous and reversible shape changes.
  • Sensitivity of the sensor ranged from 0.53 to 1.08 nC/N.
  • Working range varied between 1.01 and 0.35 N.
  • Demonstrated effectiveness through applications in a reconfigurable electronic scale and robotic sensing.

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

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Cite This Study

Kam et al. (2026) studied this question.

synapsesocial.com/papers/698c1c33267fb587c655e721https://doi.org/10.1002/eom2.70048
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