Evidence map›Paper›PMID 40789839›Full record

ArticleLight, science & applications2025

A facile photonics reconfigurable memristor with dynamically allocated neurons and synapses functions.

Zhenyu Zhou, Lulu Wang, Gongjie Liu, Yuchen Li, Zhiyuan Guan, Zixuan Zhang, Pengfei Li, Yifei Pei, Jianhui Zhao, Jiameng Sun and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Light, science & applications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

13 authors.

Zhenyu ZhouKey Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China.
Lulu WangKey Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China.
Gongjie LiuKey Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China.
Yuchen LiKey Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China.ORCID http://orcid.org/0009-0006-6831-0963
Zhiyuan GuanKey Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China.
Zixuan ZhangKey Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China.
Pengfei LiKey Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China.
Yifei PeiKey Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China.
Jianhui ZhaoKey Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China.
Jiameng SunKey Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China.
Yahong WangKey Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China.
Yiduo ShaoKey Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China.
Xiaobing YanKey Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China. yanxiaobing@ime.ac.cn.

Funding

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

Abstract

The dynamic neural network function realized by reconfigurable memristors to implement artificial neurons and synapses is an effective method to complete the next generation of neuromorphic computing. However, due to the limitation of reconfiguration conditions, there are inconsistencies in the turn-on voltage and operating current before and after the reconfiguration of neuromorphic devices, which leads to huge difficulties in hardware application development and is an urgent problem to be solved. In this work, we introduced light as a regulatory means in the memristor and achieved the reconfiguration of volatile (endurance ~10

Identifiers

PMID40789839
PMCPMC12340011

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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.