Evidence map›Paper›PMID 40653894›Full record

ReviewAdvanced materials (Deerfield Beach, Fla.)2025

Additive Manufacturing of Neuromorphic Systems.

Jiongyi Yan, Yutai Su, James P K Armstrong, Andrew Gleadall

Abstract readReview
In one paragraph

Review in Advanced materials (Deerfield Beach, Fla.), 2025. 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. Review
  2. Article
  3. Additive Manufacturing of Neuromorphic Systems.Advanced materials (Deerfield Beach, Fla.) · 2025
    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

4 authors.

Jiongyi YanWolfson School of Mechanical Electrical and Manufacturing Engineering, Loughborough University, Loughborough, LE11 3TU, UK.ORCID https://orcid.org/0000-0002-8084-3715
Yutai SuSchool of Mechanics, Civil Engineering and Architecture, Northwestern Polytechnical University, Xi'An, 710129, China.
James P K ArmstrongDepartment of Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 1TH, UK.
Andrew GleadallWolfson School of Mechanical Electrical and Manufacturing Engineering, Loughborough University, Loughborough, LE11 3TU, UK.ORCID https://orcid.org/0000-0003-2439-3120

Funding

UK Research and Innovation 10100435UKRI Future Leaders Fellowship MR/V024965/1
6 · The paper itself

Abstract

Neuromorphic engineering aims to create brain-inspired computing systems based on synaptic electronic hardware and neural network software. It combines intelligent materials, advanced processing technology, and computation programs. Additive manufacturing (AM), despite being one of the advanced manufacturing technologies capable of multimaterial processing at the microscale, is not widely applied in neuromorphic hardware fabrication. This gap suggests not only process incompatibility and limited resolution of AM but opportunities to create novel intelligent systems. Here, the state-of-the-art in AM-printed neuromorphic hardware (synaptic electronics and mechanical systems) is reviewed and discussed the integration of AM techniques with neuromorphic engineering. An outlook of printed neuromorphic systems is provided with low cost and environmental impact but high customizability and design flexibility. With ongoing innovation in AM technologies and materials, AM is envisioned with high throughput and resolution for affordable, scalable, and customizable neuromorphic hardware production. The crossover of AM and neuromorphic engineering facilitates prototyping of brain-inspired computing architectures for efficient and analog computation. This approach may facilitate various applications including neuromorphic robotics, bionics, and real-time sensing.

Indexed as

additive manufacturingartificial neural networksmemristorsneuromorphic computingtransistors

Identifiers

PMID40653894
PMCPMC12506626

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.