Evidence map›Paper›PMID 40473631›Full record

ArticleNature communications2025

Bio-inspired mid-infrared neuromorphic transistors for dynamic trajectory perception using PdSe

Huaiyu Gao, Xiaoyong Jiang, Xinyu Ma, Minrui Ye, Jie Yang, Junyao Zhang, Yangchen Gao, Tangxin Li, Hailu Wang, Jian Mei and 10 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 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Gate-Tunable Polarity-Reconfigurable Photovoltaic Response With Dual Linearity in NbSAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  3. Article
  4. Article
  5. Photo-Induced Valence Changed Memristor Based on WOSmall (Weinheim an der Bergstrasse, Germany) · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Devices, Functions, and Applications of Artificial Neuromorphic Visual Systems.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  13. 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

20 authors.

Huaiyu Gao *School of Materials Science and Engineering, Tongji University, Shanghai, P. R. China.
Xiaoyong Jiang *State Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, P. R. China.
Xinyu Ma *State Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, P. R. China.
Minrui YeSchool of Information Science and Technology, ShanghaiTech University, Shanghai, P. R. China.
Jie YangSchool of Materials Science and Engineering, Tongji University, Shanghai, P. R. China. yangj@tongji.edu.cn.ORCID http://orcid.org/0000-0002-1472-198X
Junyao ZhangSchool of Materials Science and Engineering, Tongji University, Shanghai, P. R. China.ORCID http://orcid.org/0000-0002-6300-5875
Yangchen GaoSchool of Materials Science and Engineering, Tongji University, Shanghai, P. R. China.
Tangxin LiState Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, P. R. China.
Hailu WangState Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, P. R. China.ORCID http://orcid.org/0000-0002-6771-7677
Jian MeiState Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, P. R. China.
Xiao FuState Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, P. R. China.
Xu LiuSchool of Materials Science and Engineering, Tongji University, Shanghai, P. R. China.
Tongrui SunSchool of Materials Science and Engineering, Tongji University, Shanghai, P. R. China.
Ziyi GuoSchool of Materials Science and Engineering, Tongji University, Shanghai, P. R. China.
Pu GuoSchool of Materials Science and Engineering, Tongji University, Shanghai, P. R. China.
Fansheng ChenState Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, P. R. China.
Kai ZhangKey Laboratory of Semiconductor Display Materials and Chips & i-Lab, Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences, Suzhou, P. R. China.ORCID http://orcid.org/0000-0001-9378-0947
Jinshui MiaoState Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, P. R. China. jsmiao@mail.sitp.ac.cn.ORCID http://orcid.org/0000-0002-3041-1105
Weida HuState Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, P. R. China.ORCID http://orcid.org/0000-0001-5278-8969
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) 62074111National Natural Science Foundation of China (National Science Foundation of China) 62261136552National Natural Science Foundation of China (National Science Foundation of China) 62304155National Natural Science Foundation of China (National Science Foundation of China) 62334011
6 · The paper itself

Abstract

Mid-infrared (MIR) intelligent sensing technology is essential for precise identification and tracking for dynamic target detection in challenging and low-visibility environments. However, existing MIR vision systems based on traditional von Neumann architecture face significant delays and inefficiencies due to the separation of sensing, memory, and processing units. Neuromorphic motion devices offer better tracking capabilities, but most studies are limited to the near-infrared spectrum. Inspired by the fire beetle's MIR sensing capabilities, we have developed an MIR neuromorphic device using a 2D inorganic/organic heterostructure. The device exhibits biological synaptic behavior in the MIR region (up to 4.25 μm) based on the persistent photoconductivity (PPC) effect, successfully realizing the function of dynamic trajectories memorization with real-time hardware implementation. Additionally, a reservoir computing (RC) system trained on an MIR flame motion dataset achieves a recognition accuracy of 94.79% in classifying flame motion direction. While the research on MIR neuromorphic devices is limited, this study underscores the potential of such devices to advance MIR-based machine vision applications.

Identifiers

PMID40473631
PMCPMC12141662

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.