Evidence map›Paper›PMID 34835625›Full record

ArticleNanomaterials (Basel, Switzerland)2021

Artificial Neurons Based on Ag/V

Yu Wang, Xintong Chen, Daqi Shen, Miaocheng Zhang, Xi Chen, Xingyu Chen, Weijing Shao, Hong Gu, Jianguang Xu, Ertao Hu and 3 more

Abstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Artificial sensory system based on memristive devices.Exploration (Beijing, China) · 2024
    Review
  5. Review
  6. 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

13 authors.

Yu WangCollege of Electronic and Optical Engineering & College of Microelectronics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.ORCID 0000-0002-6173-1929
Xintong ChenCollege of Electronic and Optical Engineering & College of Microelectronics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Daqi ShenCollege of Electronic and Optical Engineering & College of Microelectronics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Miaocheng ZhangCollege of Electronic and Optical Engineering & College of Microelectronics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Xi ChenInstitute of Advanced Materials (IAM), Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Xingyu ChenCollege of Electronic and Optical Engineering & College of Microelectronics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Weijing ShaoGusu Laboratory of Materials, Suzhou 215000, China.
Hong GuGusu Laboratory of Materials, Suzhou 215000, China.
Jianguang XuSchool of Materials Science and Engineering, Yancheng Institute of Technology, Yancheng 224051, China.ORCID 0000-0002-1104-2201
Ertao HuCollege of Electronic and Optical Engineering & College of Microelectronics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.ORCID 0000-0002-7659-9422
Lei WangCollege of Electronic and Optical Engineering & College of Microelectronics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.ORCID 0000-0001-7266-148X
Rongqing XuCollege of Electronic and Optical Engineering & College of Microelectronics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Yi TongCollege of Electronic and Optical Engineering & College of Microelectronics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.

Funding

China and Natural Science Foundation of Jiangsu Province BK20191202Jiangsu Specially-Appointed Professor RK106STP18003
6 · The paper itself

Abstract

Artificial synapses and neurons are two critical, fundamental bricks for constructing hardware neural networks. Owing to its high-density integration, outstanding nonlinearity, and modulated plasticity, memristors have attracted emerging attention on emulating biological synapses and neurons. However, fabricating a low-power and robust memristor-based artificial neuron without extra electrical components is still a challenge for brain-inspired systems. In this work, we demonstrate a single two-dimensional (2D) MXene(V

Indexed as

artificial neuronleaky integrate-and-firememristorMXenethreshold switching

Identifiers

PMID34835625
PMCPMC8623555

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.