Bio‐Inspired Artificial Ionic Mechanoreceptor

ABSTRACT Recent advances in materials science and rehabilitation robotics have shown strong potential for active prosthetics capable of interacting with tools and objects. The key requirement for future active prosthetics is realistic tactile feedback. Despite significant progress, conventional tactile sensors cannot fully reproduce human‐like perception, likely due to their fundamentally different sensing mechanisms. This study presents a skin‐inspired artificial mechanoreceptor composed of microfluidic channels filled with NaCl electrolyte and embedded within soft elastomeric membranes. Intrinsic surface chemistry induces a non‐uniform ionic distribution inside the channels. Mechanical stimulation disturbs this distribution, leading to changes in electrical potential. Unlike traditional sensors based on purely electronic transduction, the proposed self‐powered mechanoreceptor operates through ionic interactions similar to those in biological mechanoreceptors. The generated signal exhibits temporal features such as overshoot and undershoot, analogous to neural depolarization and repolarization. Frequency analysis shows a dominant peak near 440 Hz, consistent with the operating range of Pacinian mechanoreceptors. The output potential depends strongly on ionic concentration, with an optimal value around 5 mM NaCl. The proposed mechanoreceptor offers strong potential for improved neural compatibility by ionically modulating the electrical potential in the medium and is expected to provide more realistic tactile perception in future prosthetic limbs.

Authors

Institutions

Publication Details

Journal
Advanced Functional Materials
Published
2026-09-14
DOI
https://doi.org/10.1002/adfm.77916
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Bio‐Inspired Artificial Ionic Mechanoreceptor

Mohammad Akbari, Rassoul Tabassian, John Noee, Jeppe Don et al.
Advanced Functional Materials
Advanced Sensor and Energy Harvesting Materials
article

Bio‐Inspired Artificial Ionic Mechanoreceptor

Mohammad Akbari, Rassoul Tabassian, John Noee, Jeppe Don, Lasse A. N. Pedersen
article en

Abstract

ABSTRACT Recent advances in materials science and rehabilitation robotics have shown strong potential for active prosthetics capable of interacting with tools and objects. The key requirement for future active prosthetics is realistic tactile feedback. Despite significant progress, conventional tactile sensors cannot fully reproduce human‐like perception, likely due to their fundamentally different sensing mechanisms. This study presents a skin‐inspired artificial mechanoreceptor composed of microfluidic channels filled with NaCl electrolyte and embedded within soft elastomeric membranes. Intrinsic surface chemistry induces a non‐uniform ionic distribution inside the channels. Mechanical stimulation disturbs this distribution, leading to changes in electrical potential. Unlike traditional sensors based on purely electronic transduction, the proposed self‐powered mechanoreceptor operates through ionic interactions similar to those in biological mechanoreceptors. The generated signal exhibits temporal features such as overshoot and undershoot, analogous to neural depolarization and repolarization. Frequency analysis shows a dominant peak near 440 Hz, consistent with the operating range of Pacinian mechanoreceptors. The output potential depends strongly on ionic concentration, with an optimal value around 5 mM NaCl. The proposed mechanoreceptor offers strong potential for improved neural compatibility by ionically modulating the electrical potential in the medium and is expected to provide more realistic tactile perception in future prosthetic limbs.

Advanced Functional Materials
Aarhus University (DK), Aarhus University Hospital (DK)
Openalex Percentile: Top 20%
Advanced Sensor and Energy Harvesting Materials
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.

Bio‐Inspired Artificial Ionic Mechanoreceptor — Mohammad Akbari, Rassoul Tabassian, et al. · Advanced Functional Materials (2026) | TGRS Research Map | TGRS