Evidence map›Paper›PMID 38617552›Full record

ReviewResearch (Washington, D.C.)2022

Light-Emitting Artificial Synapses for Neuromorphic Computing.

Chen Zhu, Wen Huang, Wei Li, Xuegong Yu, Xing'ao Li

Abstract readReview
In one paragraph

Review in Research (Washington, D.C.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

5 authors.

Chen ZhuCollege of Integrated Circuit Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.ORCID https://orcid.org/0000-0003-4589-0257
Wen HuangNew Energy Technology Engineering Laboratory of Jiangsu Province & School of Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.ORCID https://orcid.org/0000-0002-2072-7173
Wei LiCollege of Electronic and Optical Engineering & College of Flexible Electronics (Future Technology), Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Xuegong YuState Key Laboratory of Silicon Materials, Zhejiang University, Hangzhou 310027, China.
Xing'ao LiNew Energy Technology Engineering Laboratory of Jiangsu Province & School of Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the key connecting points in the neuromorphic computing systems, synaptic devices have been investigated substantially in recent years. Developing optoelectronic synaptic devices with optical outputs is becoming attractive due to many benefits of optical signals in systems. Colloidal quantum dots (CQDs) are potential luminescent materials for information displays. Light-emitting diodes based on CQDs have become appealing candidates for optoelectronic synaptic devices. Moreover, light-emitting transistors exhibit great application potential in these synaptic devices. From this perspective, light-emitting artificial synapses were discussed on the basis of these structures in the devices. Their mechanisms, performance, and future development were analysed and prospected in detail.

Identifiers

PMID38617552
PMCPMC11014729

What OpenQuestion holds

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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.