Evidence map›Paper›PMID 37244897›Full record

ArticleNature communications2023

Multi-neuron connection using multi-terminal floating-gate memristor for unsupervised learning.

Ui Yeon Won, Quoc An Vu, Sung Bum Park, Mi Hyang Park, Van Dam Do, Hyun Jun Park, Heejun Yang, Young Hee Lee, Woo Jong Yu

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Review
  3. Damage-free van der Waals metal/NbONano convergence · 2026
    Article
  4. Review
  5. Artificial Neuron Based on Electrical Anisotropy from WSeAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  6. Article
  7. Article
  8. Review
  9. Li-Well ZnO Memtransistors: High Reliability for Neuromorphic Applications.Advanced materials (Deerfield Beach, Fla.) · 2026
    Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. Bio-Plausible Multimodal Learning with Emerging Neuromorphic Devices.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    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

9 authors.

Ui Yeon Won *Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, 16419, South Korea.
Quoc An Vu *IBS Center for Integrated Nanostructure Physics, Institute for Basic Science, Sungkyunkwan University, Suwon, 16419, South Korea.
Sung Bum Park *Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, 16419, South Korea.
Mi Hyang Park *Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, 16419, South Korea.
Van Dam DoDepartment of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, 16419, South Korea.
Hyun Jun ParkDisplay R&D Group, Mobile Communication Business, Samsung Electronics, Suwon, 16677, South Korea.
Heejun YangDepartment of Physics, Korea Advanced Institute of Science and Technology, Daejeon, 34141, South Korea.ORCID http://orcid.org/0000-0003-0502-0054
Young Hee LeeIBS Center for Integrated Nanostructure Physics, Institute for Basic Science, Sungkyunkwan University, Suwon, 16419, South Korea. leeyoung@skku.edu.ORCID http://orcid.org/0000-0001-7403-8157
Woo Jong YuDepartment of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, 16419, South Korea. micco21@skku.edu.ORCID http://orcid.org/0000-0002-7399-307X

Funding

Institute for Basic Science (IBS) IBSR011-D1
6 · The paper itself

Abstract

Multi-terminal memristor and memtransistor (MT-MEMs) has successfully performed complex functions of heterosynaptic plasticity in synapse. However, theses MT-MEMs lack the ability to emulate membrane potential of neuron in multiple neuronal connections. Here, we demonstrate multi-neuron connection using a multi-terminal floating-gate memristor (MT-FGMEM). The variable Fermi level (E

Identifiers

PMID37244897
PMCPMC10224934

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.