Strain-Insensitive, Crosstalk-Suppressed, Ultrawide-Linearity Iontronic Tactile Skin from a Synergistic Segment-Embedded Strategy

Tactile sensing arrays play a crucial role in human-machine interaction, robotics, and artificial intelligence by enabling the perception of physical stimuli on robotic surfaces or human skin. However, skin-attachable sensor arrays still suffer from strain interference and signal crosstalk under stretching or bending, particularly on curved or deformable surfaces. Here, we present a stretchable tactile array that is both strain-insensitive and crosstalk-suppressed, achieved via a hierarchically segmented design that mitigates lateral and vertical deformations synergistically. By tessellating hard and compliant elements within encapsulation layers, stretch deformation in the sensing region is reduced by 79%, and the overall mean stress is decreased by over 90%. Multilevel segmented spacers are proposed to provide vertical support while maintaining stretchability. These synergistic designs achieve comprehensive strain insensitivity (75% stretching insensitivity and bending insensitivity) and ultralow crosstalk (31.82 dB). Furthermore, iontronic porous foams are introduced to endow sensing pixels with high linearity (<i>R</i><sup>2</sup> = 0.985) and sensitivity (2.812 kPa<sup>-1</sup>). We demonstrate accurate tactile information acquisition on soft, curved human fingers and showcase the array's potential for multi-attribute object recognition.

Authors

Institutions

Publication Details

Journal
ACS Sensors
Published
2025-09-05
DOI
https://doi.org/10.1021/acssensors.5c01517
Citations
2
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
1.35

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Strain-Insensitive, Crosstalk-Suppressed, Ultrawide-Linearity Iontronic Tactile Skin from a Synergistic Segment-Embedded Strategy

Weichao Guo, Xinjun Sheng, Yanchao Zhao, Wei Xu
2 citations
ACS Sensors
Advanced Sensor and Energy Harvesting Materials
1.35
article

Strain-Insensitive, Crosstalk-Suppressed, Ultrawide-Linearity Iontronic Tactile Skin from a Synergistic Segment-Embedded Strategy

Weichao Guo, Xinjun Sheng, Yanchao Zhao, Wei Xu
article en
2 citations

Abstract

Tactile sensing arrays play a crucial role in human-machine interaction, robotics, and artificial intelligence by enabling the perception of physical stimuli on robotic surfaces or human skin. However, skin-attachable sensor arrays still suffer from strain interference and signal crosstalk under stretching or bending, particularly on curved or deformable surfaces. Here, we present a stretchable tactile array that is both strain-insensitive and crosstalk-suppressed, achieved via a hierarchically segmented design that mitigates lateral and vertical deformations synergistically. By tessellating hard and compliant elements within encapsulation layers, stretch deformation in the sensing region is reduced by 79%, and the overall mean stress is decreased by over 90%. Multilevel segmented spacers are proposed to provide vertical support while maintaining stretchability. These synergistic designs achieve comprehensive strain insensitivity (75% stretching insensitivity and bending insensitivity) and ultralow crosstalk (31.82 dB). Furthermore, iontronic porous foams are introduced to endow sensing pixels with high linearity (<i>R</i><sup>2</sup> = 0.985) and sensitivity (2.812 kPa<sup>-1</sup>). We demonstrate accurate tactile information acquisition on soft, curved human fingers and showcase the array's potential for multi-attribute object recognition.

ACS SensorsVol. 10(9)
Shanghai Jiao Tong University (CN), Robotics Research (United States) (US), State Key Laboratory of Chemical Engineering (CN)
National Natural Science Foundation of China, Science and Technology Commission of Shanghai Municipality, State Key Laboratory of Robotics and System
Openalex Percentile: Top 18%
Advanced Sensor and Energy Harvesting Materials
1.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.