Evidence map›Paper›PMID 41486840›Full record

ReviewAdvanced materials (Deerfield Beach, Fla.)2026

Organic Electrochemical Transistors for Neuromorphic Devices and Applications.

Kexin Xiang, Jiajun Song, Hong Liu, Junxin Chen, Feng Yan

Abstract readReview
In one paragraph

Review in Advanced materials (Deerfield Beach, Fla.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Review
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  3. Article
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  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Kexin XiangDepartment of Applied Physics, Research Center for Organic Electronics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, 999077, P. R. China.ORCID https://orcid.org/0009-0006-9623-7871
Jiajun SongDepartment of Applied Physics, Research Center for Organic Electronics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, 999077, P. R. China.
Hong LiuDepartment of Applied Physics, Research Center for Organic Electronics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, 999077, P. R. China.
Junxin ChenDepartment of Applied Physics, Research Center for Organic Electronics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, 999077, P. R. China.
Feng YanDepartment of Applied Physics, Research Center for Organic Electronics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, 999077, P. R. China.ORCID https://orcid.org/0000-0001-7385-6334

Funding

Research Center for Organic Electronics of the Hong Kong Polytechnic University 1-CE0P
6 · The paper itself

Abstract

Neuromorphic engineering, an interdisciplinary field bridging bioelectronics and neuroscience, endeavors to address the bottleneck of the von Neumann architecture by constructing hardware-level artificial neural networks (ANNs) and replicate the complicated architecture and functionality of the human brain, heralding a new era of intelligent sensing, processing, and computing systems. Organic electrochemical transistors (OECTs), which operate via the bulk doping of organic mixed ionic-electronic conductors, are emerging as promising platforms for neuromorphic devices that emulate neuronal and synaptic activities while seamlessly integrating with biological systems. OECTs offer several advantages, including compatibility with flexible and stretchable substrates, tunable ionic and electronic conductivity, multimodal sensing capability, and operation at low voltages. This review aims to provide a comprehensive and state-of-the-art vista of the rapidly advancing field of OECT-based neuromorphic devices, including organic electrochemical neurons, organic electrochemical synapses, and their integrated devices. Particular emphasis is placed on their ability to perform neuromorphic functions and diverse applications in neuromorphic computing and flexible biointerfaces. Conclusions, remaining challenges, and future prospects for the development of OECT-based neuromorphic devices are finally outlined.

Indexed as

artificial neural networkartificial neuronartificial synapsemixed ionic–electronic conductorneuromorphic engineeringorganic electrochemical transistor

Identifiers

PMID41486840
PMCPMC12902651

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.