Evidence map›Paper›PMID 39746986›Full record

ArticleNature communications2025

Ultra robust negative differential resistance memristor for hardware neuron circuit implementation.

Yifei Pei, Biao Yang, Xumeng Zhang, Hui He, Yong Sun, Jianhui Zhao, Pei Chen, Zhanfeng Wang, Niefeng Sun, Shixiong Liang and 4 more

Abstract read
PubMed Full text at PMC Publisher
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 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Advances and Perspectives in Graphene-Based Quantum Dots Enabled Neuromorphic Devices.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  5. Gallium Nitride Semiconductor Resonant Tunneling Transistor.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  6. Review
  7. 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

14 authors.

Yifei Pei *Key Laboratory of Brain like Neuromorphic Devices and Systems of Hebei Province, College of Physics Science and Technology, Hebei University, Baoding, Hebei, China.
Biao Yang *College of Electronic and Information Engineering, Hebei University, Baoding, China.
Xumeng Zhang *Frontier Institute of Chip and System, Fudan University, Shanghai, China.ORCID http://orcid.org/0000-0002-3828-151X
Hui HeKey Laboratory of Brain like Neuromorphic Devices and Systems of Hebei Province, College of Physics Science and Technology, Hebei University, Baoding, Hebei, China.
Yong SunCollege of Electronic and Information Engineering, Hebei University, Baoding, China.
Jianhui ZhaoCollege of Electronic and Information Engineering, Hebei University, Baoding, China.
Pei ChenFrontier Institute of Chip and System, Fudan University, Shanghai, China.
Zhanfeng WangKey Laboratory of Brain like Neuromorphic Devices and Systems of Hebei Province, College of Physics Science and Technology, Hebei University, Baoding, Hebei, China.
Niefeng SunNational Key Laboratory of Solid-state Microwave Devices and Circuits, Hebei Semiconductor Research Institute, Shijiazhuang, China.
Shixiong LiangSchool of Microelectronics, Tianjin University, Tianjin, China.
Guodong GuNational Key Laboratory of Solid-state Microwave Devices and Circuits, Hebei Semiconductor Research Institute, Shijiazhuang, China.
Qi LiuFrontier Institute of Chip and System, Fudan University, Shanghai, China. liu@fudan.edu.cn.ORCID http://orcid.org/0000-0001-7062-831X
Shushen LiKey Laboratory of Brain like Neuromorphic Devices and Systems of Hebei Province, College of Physics Science and Technology, Hebei University, Baoding, Hebei, China.
Xiaobing YanKey Laboratory of Brain like Neuromorphic Devices and Systems of Hebei Province, College of Physics Science and Technology, Hebei University, Baoding, Hebei, China. yanxiaobing@ime.ac.cn.ORCID http://orcid.org/0000-0002-6335-336X

Funding

National Natural Science Foundation of China (National Science Foundation of China) 61874158National Natural Science Foundation of China (National Science Foundation of China) 62004056
6 · The paper itself

Abstract

Neuromorphic computing holds immense promise for developing highly efficient computational approaches. Memristor-based artificial neurons, known for due to their straightforward structure, high energy efficiency, and superior scalability, which enable them to successfully mimic biological neurons with electrical devices. However, the reliability of memristors has always been a major obstacle in neuromorphic computing. Here, we propose an ultra-robust and efficient neuron of negative differential resistance (NDR) memristor based on AlAs/In

Identifiers

PMID39746986
PMCPMC11696043

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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.