Single-transistor organic electrochemical neurons

Neuromorphic devices that mimic the energy-efficient sensing and processing capabilities of biological neurons hold significant promise for developing bioelectronic systems capable of precise sensing and adaptive stimulus-response. However, current silicon-based technologies lack biocompatibility and rely on operational principles that differ from those of biological neurons. Organic electrochemical neurons (OECNs) address these shortcomings but typically require multiple components, limiting their integration density and scalability. Here, we report a single-transistor OECN (1T-OECN) that leverages the hysteretic switching of organic electrochemical memtransistors (OECmTs) based on poly(benzimidazobenzophenanthroline). By tuning the electrolyte and driving voltage, the OECmTs switch between high- and low-resistance states, enabling action potential generation, dynamic spiking, and logic operations within a single device with dimensions comparable to biological neurons. The compact 1T-OECN design (~180 µm<sup>2</sup> footprint) supports high-density integration, achieving over 62,500 neurons/cm<sup>2</sup> on flexible substrates. This advancement highlights the potential for scalable, bio-inspired neuromorphic computing and seamless integration with biological systems.

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Publication Details

Journal
Nature Communications
Published
2025-05-09
DOI
https://doi.org/10.1038/s41467-025-59587-4
Citations
30
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
21.91

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article

Single-transistor organic electrochemical neurons

Dace Gao, Deyu Tu, Nevena Stajković, Claudia Latte Bovio et al.
30 citations
Nature Communications
Advanced Memory and Neural Computing
21.91
article

Single-transistor organic electrochemical neurons

Dace Gao, Deyu Tu, Nevena Stajković, Claudia Latte Bovio, Junpeng Ji, Francesca Santoro, Simone Fabiano, Chi‐Yuan Yang, Miao Xiong, Hanyan Wu
article en
30 citations

Abstract

Neuromorphic devices that mimic the energy-efficient sensing and processing capabilities of biological neurons hold significant promise for developing bioelectronic systems capable of precise sensing and adaptive stimulus-response. However, current silicon-based technologies lack biocompatibility and rely on operational principles that differ from those of biological neurons. Organic electrochemical neurons (OECNs) address these shortcomings but typically require multiple components, limiting their integration density and scalability. Here, we report a single-transistor OECN (1T-OECN) that leverages the hysteretic switching of organic electrochemical memtransistors (OECmTs) based on poly(benzimidazobenzophenanthroline). By tuning the electrolyte and driving voltage, the OECmTs switch between high- and low-resistance states, enabling action potential generation, dynamic spiking, and logic operations within a single device with dimensions comparable to biological neurons. The compact 1T-OECN design (~180 µm<sup>2</sup> footprint) supports high-density integration, achieving over 62,500 neurons/cm<sup>2</sup> on flexible substrates. This advancement highlights the potential for scalable, bio-inspired neuromorphic computing and seamless integration with biological systems.

Nature CommunicationsVol. 16(1)
Linköping University (SE), Forschungszentrum Jülich (DE), Italian Institute of Technology (IT), Department of Science,Technology and Innovation (ZA), Center for Advanced Biomaterials for Healthcare (IT), Department of Science and Technology and Biotechnology (IN), University of Naples Federico II (IT), RWTH Aachen University (DE)
European Commission, Stiftelsen för Strategisk Forskning, Linköpings Universitet, Knut och Alice Wallenbergs Stiftelse, Vetenskapsrådet
Affordable and clean energy
Openalex Percentile: Top 0%
Advanced Memory and Neural Computing
21.91
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