Evidence map›Paper›PMID 41690917›Full record

ArticleNature communications2026

Intrinsically stretchable all-polymer neuromorphic visual adaptive transistors based on multidimensional-phase-separation-induced micromesh.

Chengyu Wang, Mingcong Qin, Jianzhe Sun, Yangshuang Bian, Mingliang Zhu, Wenkang Shi, Jiaxin Hong, Yanyan Cao, Yiran Liu, Zhiyuan Zhao and 2 more

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Chengyu WangBeijing National Laboratory for Molecular Sciences, Key Laboratory of Organic Solids, Institute of Chemistry Chinese Academy of Sciences, Beijing, China.
Mingcong QinBeijing National Laboratory for Molecular Sciences, Key Laboratory of Organic Solids, Institute of Chemistry Chinese Academy of Sciences, Beijing, China.
Jianzhe SunBeijing National Laboratory for Molecular Sciences, Key Laboratory of Organic Solids, Institute of Chemistry Chinese Academy of Sciences, Beijing, China.
Yangshuang BianBeijing National Laboratory for Molecular Sciences, Key Laboratory of Organic Solids, Institute of Chemistry Chinese Academy of Sciences, Beijing, China.
Mingliang ZhuBeijing National Laboratory for Molecular Sciences, Key Laboratory of Organic Solids, Institute of Chemistry Chinese Academy of Sciences, Beijing, China.
Wenkang ShiBeijing National Laboratory for Molecular Sciences, Key Laboratory of Organic Solids, Institute of Chemistry Chinese Academy of Sciences, Beijing, China.
Jiaxin HongBeijing National Laboratory for Molecular Sciences, Key Laboratory of Organic Solids, Institute of Chemistry Chinese Academy of Sciences, Beijing, China.
Yanyan CaoBeijing National Laboratory for Molecular Sciences, Key Laboratory of Organic Solids, Institute of Chemistry Chinese Academy of Sciences, Beijing, China.
Yiran LiuBeijing National Laboratory for Molecular Sciences, Key Laboratory of Organic Solids, Institute of Chemistry Chinese Academy of Sciences, Beijing, China.
Zhiyuan ZhaoBeijing National Laboratory for Molecular Sciences, Key Laboratory of Organic Solids, Institute of Chemistry Chinese Academy of Sciences, Beijing, China. zhaozhiyuan@iccas.ac.cn.ORCID http://orcid.org/0009-0007-5159-5381
Yunqi LiuBeijing National Laboratory for Molecular Sciences, Key Laboratory of Organic Solids, Institute of Chemistry Chinese Academy of Sciences, Beijing, China.ORCID http://orcid.org/0000-0001-5521-2316
Yunlong GuoBeijing National Laboratory for Molecular Sciences, Key Laboratory of Organic Solids, Institute of Chemistry Chinese Academy of Sciences, Beijing, China. guoyunlong@iccas.ac.cn.ORCID http://orcid.org/0000-0003-1602-769X

Funding

CAS | Institute of Chemistry, Chinese Academy of Sciences (ICCAS) XDB0520101, YSBR-053National Natural Science Foundation of China (National Science Foundation of China) 22525506, T2441002, U22A6002 and 82151305
6 · The paper itself

Abstract

Stretchable neuromorphic optoelectronics requiring real-time perception and dynamic adaptive processing create tempting opportunities for wearable intelligent vision equipment. Existing bionic vision devices often lack scale-modulus deformable photosensitive materials and exhibit redundant manufacturing for complex structures to integrate optical neurofunctions, highlighting a critical gap in achieving both ductility and multifunctionality. Herein, we propose a defect-tunable viscoelastic photosensitive bulk-heterojunction based on multidimensional-phase-separation-induced micromesh for all-organic intrinsically stretchable neuromorphic visual adaptive transistors. The resultant devices demonstrate maintained high photosensitivity and multimodal broad-wavelength photoadaptation even under 100% biaxial mechanical strain. Notably, a record-ultrafast adaptive time down to 0.4 s is achieved by the all-organic intrinsically stretchable visual adaptive transistors, allowing a high energy-saving ratio of 88.4%. Moreover, a low paired-pulse depression index down to 44.37% is also accomplished, exhibiting the ability of abnormal discharges reduction and normal neural network function restore. The superior bionic visual adaptive systems allowing detailed time-varying intelligent information conversion, can realize highly misleading encrypted wireless optical communications. Furthermore, contrast vision-adaptive pixels are successfully constructed to avoid element absence for advanced driving assistance systems simulation in extreme environments. This technology promises to advance skin-like neuromorphic vision systems for applications including visual cryptography, bioinspired robots and unmanned intelligence.

Identifiers

PMID41690917
PMCPMC13022258

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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.