Evidence map›Paper›PMID 41537178›Full record

ArticleSmall science2026

Reconfigurable Magneto-Optoelectronic Devices for Multidimensional Optical Neural Network.

Haiyan He, Yuan Cheng, Wenxuan Zhu, Jiacheng Sun, Jiaming Sun, Tonglu Wang, Cheng Song, Feng Pan, Junying Zhang, Yuyan Wang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Small science, 2026. 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. 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

10 authors.

Haiyan HeBeijing National Research Center for Information Science and Technology School of Integrated Circuits Tsinghua University Beijing 100084 China.
Yuan ChengSchool of Artificial Intelligence Shanghai Jiao Tong University Shanghai 200030 China.
Wenxuan ZhuKey Laboratory of Advanced Materials (MOE) School of Materials Science and Engineering Tsinghua University Beijing 100084 China.ORCID https://orcid.org/0009-0003-5088-2865
Jiacheng SunBeijing National Research Center for Information Science and Technology School of Integrated Circuits Tsinghua University Beijing 100084 China.
Jiaming SunBeijing National Research Center for Information Science and Technology School of Integrated Circuits Tsinghua University Beijing 100084 China.
Tonglu WangBeijing National Research Center for Information Science and Technology School of Integrated Circuits Tsinghua University Beijing 100084 China.
Cheng SongKey Laboratory of Advanced Materials (MOE) School of Materials Science and Engineering Tsinghua University Beijing 100084 China.
Feng PanKey Laboratory of Advanced Materials (MOE) School of Materials Science and Engineering Tsinghua University Beijing 100084 China.
Junying ZhangSchool of Physics Beihang University Beijing 100191 China.ORCID https://orcid.org/0000-0002-4860-8774
Yuyan WangBeijing National Research Center for Information Science and Technology School of Integrated Circuits Tsinghua University Beijing 100084 China.ORCID https://orcid.org/0000-0002-6369-7103

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optical neural networks (ONNs) with extremely low latency, low power consumption, and high parallelism, provide an advantageous computational paradigm to address the rapid development of artificial intelligence. Conventional ONNs focus on handling limited information dimensions such as optical amplitude and phase, which are confined to simple small-size image classification, raising demand for significant reconfigurability on the perception of inherent high-dimensional light information. Herein, magneto-optoelectronic devices with polarization sensitivity are theoretically proposed to construct the ONN with high-performance multidimensional recognition, which is composed of 2D magnetic half-metal FeCl

Indexed as

2D magnetic materialsFeCl2magneto‐optoelectronicsoptical neural networkphotogalvanic effect

Identifiers

PMID41537178
PMCPMC12798793

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.