Scalable Patterning of Organic Electrochemical Transistors for Logic Gates and Neuromorphic Computing

ABSTRACT Organic electrochemical transistors (OECTs) are promising building blocks for bioelectronics owing to their efficient ion–electron coupling, soft‐material compatibility and high transconductance. However, their large off‐state currents and poor scalability have so far limited high‐density integration and circuit‐level functionality. Here we introduce a patterning strategy suitable for solution‑processable organic semiconductors, enabling high‑fidelity OECT arrays with suppressed leakage and off‑state currents, on/off ratios up to 10 7 , and good device‑to‑device uniformity. Leveraging these patterned OECTs, we demonstrate the integration of logic circuits, including complementary inverters as well as NAND and NOR gates, exhibiting high voltage gain (up to 203 V/V), large noise margins (92.17%) and stable operation at low supply voltages. Benefiting from the patterning approach and the AlO x ‐induced suppression of off‐state current, the static power consumption of the inverter is reduced by approximately 90%. Beyond digital logic, we further show that these devices emulate key synaptic functions such as short‐term plasticity and enable reservoir computing tasks, defining a manufacturable platform for integrated bioelectronic circuitry and neuromorphic architectures. This patterning strategy therefore provides a general route toward high‐density biointerfaces and next‐generation brain–computer interfaces.

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Publication Details

Journal
Small
Published
2026-10-15
DOI
https://doi.org/10.1002/smll.76279
Primary Topic
Conducting polymers and applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Scalable Patterning of Organic Electrochemical Transistors for Logic Gates and Neuromorphic Computing

Junyang Deng, Liuyuan Lan, Wan Yue, Mengmeng Li et al.
Small
Conducting polymers and applications
article

Scalable Patterning of Organic Electrochemical Transistors for Logic Gates and Neuromorphic Computing

Junyang Deng, Liuyuan Lan, Wan Yue, Mengmeng Li, Jian Liu, Hanlin Wang, Miao Cheng, Zhenjie Ni, Yue Tian, Yazhuo Kuang, Jiahao Zhao, Yifan Xie, Zhongrui Wang, Chengqi Wei, Changrui Liu
article en

Abstract

ABSTRACT Organic electrochemical transistors (OECTs) are promising building blocks for bioelectronics owing to their efficient ion–electron coupling, soft‐material compatibility and high transconductance. However, their large off‐state currents and poor scalability have so far limited high‐density integration and circuit‐level functionality. Here we introduce a patterning strategy suitable for solution‑processable organic semiconductors, enabling high‑fidelity OECT arrays with suppressed leakage and off‑state currents, on/off ratios up to 10 7 , and good device‑to‑device uniformity. Leveraging these patterned OECTs, we demonstrate the integration of logic circuits, including complementary inverters as well as NAND and NOR gates, exhibiting high voltage gain (up to 203 V/V), large noise margins (92.17%) and stable operation at low supply voltages. Benefiting from the patterning approach and the AlO x ‐induced suppression of off‐state current, the static power consumption of the inverter is reduced by approximately 90%. Beyond digital logic, we further show that these devices emulate key synaptic functions such as short‐term plasticity and enable reservoir computing tasks, defining a manufacturable platform for integrated bioelectronic circuitry and neuromorphic architectures. This patterning strategy therefore provides a general route toward high‐density biointerfaces and next‐generation brain–computer interfaces.

Small
Sun Yat-sen University (CN), Chinese Academy of Sciences (CN), Southern University of Science and Technology (CN), Institute of Microelectronics (SG), State Key Laboratory on Integrated Optoelectronics (CN), Changchun Institute of Applied Chemistry (CN), Beijing National Laboratory for Molecular Sciences (CN), Institute of Microelectronics (CN), Institute of Chemistry (CN), University of Chinese Academy of Sciences (CN)
Natural Science Foundation of Beijing Municipality, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 26%
Conducting polymers and applications
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