Evidence map›Paper›PMID 41361169›Full record

ArticleNature communications2025

Near-infrared organic photoelectrochemical synaptic transistors by wafer-scale photolithography for neuromorphic visual system.

Xu Liu, Shilei Dai, Yiyang Jin, Junyao Zhang, Ziyi Guo, Tongrui Sun, Li Li, Pu Guo, Huaiyu Gao, Haixia Liang and 4 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Bioinspired Photodetectors: From Nature to Advanced Applications.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
  4. Article
  5. Electrochemical in-biosensing computing.National science review · 2026
    Article
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

14 authors.

Xu Liu *School of Materials Science and Engineering, Tongji University, Shanghai, P.R. China.
Shilei Dai *School of Materials Science and Engineering, Tongji University, Shanghai, P.R. China.
Yiyang Jin *School of Electronic and Information Engineering, State Key Laboratory of Autonomous. Intelligent Unmanned Systems, Frontiers Science Center for Intelligent Autonomous Systems, and Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai, P.R. China.
Junyao ZhangSchool of Materials Science and Engineering, Tongji University, Shanghai, P.R. China.ORCID http://orcid.org/0000-0002-6300-5875
Ziyi GuoSchool of Materials Science and Engineering, Tongji University, Shanghai, P.R. China.
Tongrui SunSchool of Materials Science and Engineering, Tongji University, Shanghai, P.R. China.
Li LiSchool of Materials Science and Engineering, Tongji University, Shanghai, P.R. China.
Pu GuoSchool of Materials Science and Engineering, Tongji University, Shanghai, P.R. China.
Huaiyu GaoSchool of Materials Science and Engineering, Tongji University, Shanghai, P.R. China.
Haixia LiangSchool of Materials Science and Engineering, Tongji University, Shanghai, P.R. China.
Shiqi ZhangSchool of Mechanical Engineering, Nantong University, Nantong, P.R. China.
Lize XiongTranslational Research Institute of Brain and Brain-Like Intelligence, Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Shanghai Fourth People's Hospital Affiliated to Tongji University, Tongji University, Shanghai, P.R. China. lizexiong@tongji.edu.cn.
Yanmin ZhouSchool of Electronic and Information Engineering, State Key Laboratory of Autonomous. Intelligent Unmanned Systems, Frontiers Science Center for Intelligent Autonomous Systems, and Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai, P.R. China. yanmin.zhou@tongji.edu.cn.ORCID http://orcid.org/0000-0001-7824-1179
Jia HuangSchool of Materials Science and Engineering, Tongji University, Shanghai, P.R. China. huangjia@tongji.edu.cn.ORCID http://orcid.org/0000-0002-2873-7704

Funding

National Natural Science Foundation of China (National Science Foundation of China) 22405136National Natural Science Foundation of China (National Science Foundation of China) 62088101
6 · The paper itself

Abstract

Optoelectronic synapses can be crucial for advancing artificial intelligence and visual systems. Optoelectronic synapses based on organic field-effect transistors have been widely studied but still face significant challenges including obvious programming nonlinearity, restricted response wavelength, high operation voltage, and limited storage memory. Organic electrochemical transistors can be another candidate but lack intensive studies. Additionally, wafer-scale photolithographic fabrication on optoelectronic synapses responding to near-infrared (NIR) light is highly desirable but rarely reported. Here, we propose the NIR organic photoelectrochemical transistor (OPECT) array capable of low voltage multi-level memories fabricated by photolithography. Based on NIR photo-induced electrochemical doping mechanism, the OPECTs enable linear weight programming with ultra-low nonlinearity (-0.015) over a wide range (47.3). We further demonstrate OPECTs arrays for image sensing, memorization, and visualization. Eventually, a convolutional computing system is constructed, executing accurate recognition of noisy handwritten digits. This work offers a promising insight into neuromorphic sensory computing applications.

Identifiers

PMID41361169
PMCPMC12780254

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.