Evidence map›Paper›PMID 40340983›Full record

ArticleNature communications2025

CMOS-integrated organic neuromorphic imagers for high-resolution dual-modal imaging.

Salihuojia Talanti, Kerui Fu, Xiaolong Zheng, Youzhi Shi, Yimei Tan, Chenxi Liu, Yanfei Liu, Ge Mu, Qun Hao, Kangkang Weng and 1 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 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Differential Image Sensor With Decoupled Static and Dynamic Outputs.Advanced materials (Deerfield Beach, Fla.) · 2026
    Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Devices, Functions, and Applications of Artificial Neuromorphic Visual Systems.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    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

11 authors.

Salihuojia TalantiSchool of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China.
Kerui FuSchool of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China.
Xiaolong ZhengSchool of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China.
Youzhi ShiSchool of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China.
Yimei TanSchool of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China.
Chenxi LiuSchool of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China.
Yanfei LiuXinIR Technology (Beijing) Co., LTD, Beijing, 101102, China.ORCID http://orcid.org/0009-0007-9446-4111
Ge MuSchool of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China.ORCID http://orcid.org/0000-0001-6391-9725
Qun HaoSchool of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China.ORCID http://orcid.org/0000-0002-9819-731X
Kangkang WengSchool of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China. kangkangweng@bit.du.cn.
Xin TangSchool of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China. xintang@bit.edu.cn.ORCID http://orcid.org/0000-0003-0008-207X

Funding

National Natural Science Foundation of China (National Science Foundation of China) 62035004National Natural Science Foundation of China (National Science Foundation of China) 62405023National Natural Science Foundation of China (National Science Foundation of China) U22A2081
6 · The paper itself

Abstract

Simultaneously capturing static images and processing dynamic visual information within a single sensor enables a more comprehensive and efficient acquisition of scene information, thereby enhancing the understanding and processing of complex scenes. However, current artificial visual systems present significant challenges in device integration and multimodal operation. Here, we developed a 640×512-pixel CMOS-integrated organic neuromorphic imager featuring dual modes: standard (frame-based imaging) and synaptic (neuromorphic imaging). In synaptic mode, the system extracts high-resolution spatiotemporal maps (light distribution and motion trajectories) from final frames, decoding temporal sequences of light events through contrast analysis. The neuromorphic device demonstrates adjustable memory behavior through modulation of charge recombination-trapping dynamics, enabling multi-level memory functionality. We further developed a CMOS-compatible photolithography method, which supports high-resolution and non-destructive patterning of organic neuromorphic devices. The fabricated imager allows in-sensor memorization (>18 min) and real-world spatiotemporal imaging with reduced computation resource, demonstrating its potential for industrial monitoring and motion detection.

Identifiers

PMID40340983
PMCPMC12062424

What OpenQuestion holds

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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.