Bioinspired Mechanosensitive Organic Artificial Neuron With Programmable Excitatory and Inhibitory Responses via Nonlinear Mechano-Electrochemical Coupling.

Authors

Rassen Boukraa, Pietro Belleri, Zsolt M Kovács-Vajna, Paschalis Gkoupidenis, Fabrizio Torricelli

Published in

Advanced materials (Deerfield Beach, Fla.). Pages e75027. Sep 17, 2026. Epub Sep 17, 2026.

Abstract

Neuromorphic systems capable of directly interfacing with the physical world are essential for embodied intelligence, wearable bioelectronics, and adaptive human-machine interaction. However, most artificial neurons process mechanical and chemical stimuli through external sensors and peripheral circuitry, rather than encoding multimodal information at the neuron-level, limiting integration and functional coupling between stimuli and excitability. Here we report a flexible organic artificial neuron (OAN) that couples mechanical deformation and ionic environment to spiking dynamics through nonlinear mechano-electrochemical interactions. The OAN, fabricated by additive manufacturing on flexible substrates, integrates an organic electrochemical nonlinear element exhibiting S-shaped negative differential resistance (S-NDR) with a nonlinear active load to generate low-voltage oscillatory activity. Mechanical bending within the elastic regime and variations in electrolyte ion concentration reconfigure the relative position between the S-NDR characteristic and the active-load line in the current-voltage plane, enabling deterministic transitions between quiescent and oscillatory states. The proposed OAN shows mechanically triggered firing, mechanically induced silencing, and chemically controlled reactivation. Numerical simulations quantitatively reproduce the nonlinear OAN operation and spiking behavior, providing predictive design guidelines. These findings establish a device-level framework for multimodal organic neurons in which mechanical and ionic signals are directly encoded in device physics, opening avenues toward biointegrated neuromorphic systems.

PMID:
42753145
Bibliographic data and abstract were imported from PubMed on 18 Sep 2026.

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