Evidence map›Paper›PMID 40423114›Full record

ReviewNanomaterials (Basel, Switzerland)2025

A Review of Nanowire Devices Applied in Simulating Neuromorphic Computing.

Tianci Huang, Yuxuan Wang, Zhihan Jin, Hao Liu, Kaili Wang, Tan Leong Chee, Yi Shi, Shancheng Yan

Abstract readReview
In one paragraph

Review in Nanomaterials (Basel, Switzerland), 2025. 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. 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

8 authors.

Tianci HuangSchool of Integrated Circuit Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Yuxuan WangNational Key Laboratory of Solid-State Microwave Devices and Circuits, Nanjing 210005, China.
Zhihan JinSchool of Integrated Circuit Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Hao LiuSchool of Integrated Circuit Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Kaili WangSchool of Integrated Circuit Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Tan Leong CheeSchool of Integrated Circuit Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.ORCID 0000-0002-1350-3577
Yi ShiSchool of Electronic Science and Engineering, Nanjing University, Nanjing 210023, China.
Shancheng YanSchool of Integrated Circuit Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.ORCID 0000-0003-2574-3479

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rapid advancement of artificial intelligence and machine learning technologies, the demand for enhanced device computing capabilities has significantly increased. Neuromorphic computing, an emerging computational paradigm inspired by the human brain, has garnered growing attention as a promising research frontier. Inspired by the human brain's functionality, this technology mimics the behavior of neurons and synapses to enable efficient, low-power computing. Unlike conventional digital systems, this approach offers a potentially superior alternative. This article delves into the application of nanowire materials (and devices) in neuromorphic computing simulations: First, it introduces the synthesis and preparation methods of nanowire materials. Then, it analyzes in detail the key role of nanowire devices in constructing artificial neural networks, especially their advantages in simulating the functions of neurons and synapses. Compared with traditional silicon-based material devices, it focuses on how nanowire devices can achieve higher connection density and lower energy consumption, thereby enabling new types of neuromorphic computing. Finally, it looks forward to the application potential of nanowire devices in the field of future neuromorphic computing, expecting them to become a key force in promoting the development of intelligent computing, with extensive application prospects in the fields of informatics and medicine.

Indexed as

nanowire devicesneural networkneuromorphic computing

Identifiers

PMID40423114
PMCPMC12114477

What OpenQuestion holds

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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.