Evidence map›Paper›PMID 42236471›Full record

ArticleNature communications2026

High encoding-sensitivity vision sensor with complementary nonlinear neuromorphic computing.

Quan Yang, Chuanqing Wang, Ziyang Shen, Yu Kang, Cheng Zhang, Yuanyuan Zhou, Zheng Bian, Xiangwei Su, Chunlian Qin, Jiabao Sun and 8 more

Abstract read
PubMed Full text at PMC Publisher
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

18 authors.

Quan Yang *College of Integrated Circuits, ZJU-Hangzhou Global Scientific and Technological Innovation Centre, Zhejiang University, Hangzhou, China.
Chuanqing Wang *Institute of Energy, Hefei Comprehensive National Science Center (Anhui Energy Laboratory), Hefei, China.ORCID http://orcid.org/0000-0001-8585-2437
Ziyang ShenCenBRAIN Neurotech Center of Excellence, School of Engineering, Westlake University, Hangzhou, China.
Yu KangCollege of Integrated Circuits, ZJU-Hangzhou Global Scientific and Technological Innovation Centre, Zhejiang University, Hangzhou, China.ORCID http://orcid.org/0009-0000-6767-1659
Cheng ZhangCollege of Integrated Circuits, ZJU-Hangzhou Global Scientific and Technological Innovation Centre, Zhejiang University, Hangzhou, China.
Yuanyuan ZhouCollege of Integrated Circuits, ZJU-Hangzhou Global Scientific and Technological Innovation Centre, Zhejiang University, Hangzhou, China.
Zheng BianCollege of Integrated Circuits, ZJU-Hangzhou Global Scientific and Technological Innovation Centre, Zhejiang University, Hangzhou, China.
Xiangwei SuCollege of Integrated Circuits, ZJU-Hangzhou Global Scientific and Technological Innovation Centre, Zhejiang University, Hangzhou, China.
Chunlian QinZJU-Hangzhou Global Scientific and Technological Innovation Centre, Zhejiang University, Hangzhou, China.
Jiabao SunMicro-Nano Fabrication Center, Zhejiang University, Hangzhou, China.
Yanhua LiuMicro-Nano Fabrication Center, Zhejiang University, Hangzhou, China.
Bowen ZhuKey Laboratory of 3D Micro/Nano Fabrication and Characterization of Zhejiang Province, School of Engineering, Westlake University, Hangzhou, China.ORCID http://orcid.org/0000-0001-7534-9723
Zhuangjun FanInstitute of Energy, Hefei Comprehensive National Science Center (Anhui Energy Laboratory), Hefei, China.ORCID http://orcid.org/0000-0001-5639-0675
Mohamad SawanCenBRAIN Neurotech Center of Excellence, School of Engineering, Westlake University, Hangzhou, China. sawan@westlake.edu.cn.ORCID http://orcid.org/0000-0002-4137-7272
Yang XuCollege of Integrated Circuits, ZJU-Hangzhou Global Scientific and Technological Innovation Centre, Zhejiang University, Hangzhou, China.ORCID http://orcid.org/0000-0003-3148-7678
Bin YuCollege of Integrated Circuits, ZJU-Hangzhou Global Scientific and Technological Innovation Centre, Zhejiang University, Hangzhou, China.ORCID http://orcid.org/0000-0003-0237-6311
Yang ChaiDepartment of Applied Physics, The Hong Kong Polytechnic University, Hong Kong, China.ORCID http://orcid.org/0000-0002-8943-0861
Yuda ZhaoCollege of Integrated Circuits, ZJU-Hangzhou Global Scientific and Technological Innovation Centre, Zhejiang University, Hangzhou, China. yudazhao@zju.edu.cn.ORCID http://orcid.org/0000-0003-2748-0537

Funding

National Natural Science Foundation of China (National Science Foundation of China) 62261160574, 62090034
6 · The paper itself

Abstract

Building a neuromorphic vision sensor capable of signal processing and spike generation is essential for developing hardware tailored to brain-inspired spiking neural networks. A critical challenge, however, is the constrained adaptive sensitivity when dealing with expanding ranges of light intensity. Here we show a neuromorphic vision sensor built on a one-transistor-one-memristor pixel structure, attaining high encoding-sensitivity over a broad intensity range by fusing complementary superlinear and sublinear encoding. Specifically, the superlinear intensity-to-spike firing is based on the plasmonic volatile Ag/hBN/Au memristor, which has the high time-to-first-spike (TTFS)- and rate- encoding sensitivity in high-brightness. And the sublinear firing behavior is based on the MoS

Identifiers

PMID42236471
PMCPMC13396508

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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.