Artificial Neurons and Synapses Based on Al/a-SiN

Kangmin Leng, Xu Zhu, Zhongyuan Ma, Xinyue Yu, Jun Xu, Ling Xu, Wei Li, Kunji Chen

Abstract read

In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2022. 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

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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.

Organic Memristor with Synaptic Plasticity for Neuromorphic Computing Applications.Nanomaterials (Basel, Switzerland) · 2023
Article

4 · The record

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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

8 authors.

Kangmin LengThe School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China.

Xu ZhuThe School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China.

Zhongyuan MaThe School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China.

Xinyue YuThe School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China.

Jun XuThe School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China.

Ling XuThe School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China.

Wei LiThe School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China.

Kunji ChenThe School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China.ORCID 0000-0002-4990-9253

Funding

Research Fund for the Doctoral Program of the Higher Education of China Grant No. 20130091110024Six Talent Peaks Project in Jiangsu Province DZXX-001the National Nature Science Foundation of China Grant Nos. 61634003, 61571221

6 · The paper itself

Abstract

As the building block of brain-inspired computing, resistive switching memory devices have recently attracted great interest due to their biological function to mimic synapses and neurons, which displays the memory switching or threshold switching characteristic. To make it possible for the Si-based artificial neurons and synapse to be integrated with the neuromorphic chip, the tunable threshold and memory switching characteristic is highly in demand for their perfect compatibility with the mature CMOS technology. We first report artificial neurons and synapses based on the Al/a-SiN

Indexed as

brain-inspired computingmemory switchingresistive switchingthreshold switching

Identifiers

PMID35159656

DOI10.3390/nano12030311

PMCPMC8839940

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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.