Evidence map›Paper›PMID 34683236›Full record

ArticleMicromachines2021

Integrated Fabrication of Novel Inkjet-Printed Silver Nanoparticle Sensors on Carbon Fiber Reinforced Nylon Composites.

Büşra Karaş, Vimanyu Beedasy, Zhaoyuan Leong, Nicola A Morley, Kamran Mumtaz, Patrick J Smith

Abstract read
In one paragraph

Article in Micromachines, 2021. 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. Article
  2. Article
  3. 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

6 authors.

Büşra KaraşInnovative Process Laboratory, Department of Mechanical Engineering, The University of Sheffield, 64 Garden Street, Sheffield S1 4BJ, UK.
Vimanyu BeedasyApplied Inkjet Printing Laboratory, Department of Mechanical Engineering, The University of Sheffield, 64 Garden Street, Sheffield S1 4BJ, UK.
Zhaoyuan LeongDepartment of Materials Science and Engineering, The University of Sheffield, Sheffield S1 3JD, UK.
Nicola A MorleyDepartment of Materials Science and Engineering, The University of Sheffield, Sheffield S1 3JD, UK.
Kamran MumtazInnovative Process Laboratory, Department of Mechanical Engineering, The University of Sheffield, 64 Garden Street, Sheffield S1 4BJ, UK.
Patrick J SmithApplied Inkjet Printing Laboratory, Department of Mechanical Engineering, The University of Sheffield, 64 Garden Street, Sheffield S1 4BJ, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inkjet-printing technology enables the contactless deposition of functional materials such as conductive inks on surfaces, hence reducing contamination and the risk of substrate damage. In printed electronics, inkjet technology offers the significant advantage of controlling the volume of material deposited, and therefore the fine-tuning of the printed geometry, which is crucial for the performance of the final printed electronics. Inkjet printing of functional inks can be used to produce sensors to detect failure of mechanical structures such as carbon fiber reinforced composite (CFRC) components, instead of using attached sensors, which are subject to delamination. Here, silver nanoparticle-based strain sensors were embedded directly in an insulated carbon-fiber laminate by using inkjet printing to achieve an optimized conductive and adhesive geometry, forming a piezoresistive strain sensor. Following the inkjet-printing optimization process, the sensor conductivity and adhesion performance were evaluated. Finally, the sensor was quantified by using a bending rig which applied a pre-determined strain, with the response indicating an accurate sensitivity as the resistance increased with an increased strain. The ability to embed the sensor directly on the CFRC prevents the use of interfacial adhesives which is the main source of failure due to delamination.

Indexed as

carbon fiber reinforced polymerscross-cut testinkjet printingprinted electronicsstrain sensor

Identifiers

PMID34683236
PMCPMC8541134

What OpenQuestion holds

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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.