Evidence map›Paper›PMID 28275317›Full record

ArticleSensing and imaging2017

A Proof of Concept Study on Utilising a Non-invasive Microwave Analysis Technique to Characterise Silver Based Materials in Aqueous Solution.

Muhammad Ateeq, Andy Shaw, Rob Garrett, Paul Dickson

Abstract read
In one paragraph

Article in Sensing and imaging, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Microwave Sensors forSensors (Basel, Switzerland) · 2021
    Article
  4. 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.

Muhammad AteeqLow Carbon Eco-Innovatory, Faculty of Engineering and Technology, Liverpool John Moores University, Liverpool, L3 3AF UK.
Andy ShawFaculty of Engineering and Technology, Liverpool John Moores University, Liverpool, L3 3AF UK.
Rob GarrettAmesGoldsmith UK Ltd, Acornfield Road, Knowsley Industrial Park, Kirkby, Liverpool, L33 7UF UK.
Paul DicksonLow Carbon Eco-Innovatory, Faculty of Engineering and Technology, Liverpool John Moores University, Liverpool, L3 3AF UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper reports on the feasibility of using a novel and robust microwave sensing technique to analyse and detect silver materials in an aqueous solution. Two products are tested, namely: silver chloride and silver oxide. The study mainly focused on indicating the difference between them and also any change in the size/size distribution of the sample. A microwave sensor designed previously is utilised to identify the potential of the technique to carry out the analysis. The results are presented as microwave spectrums that are the material response to microwaves. The results have shown that the technique has reasonably indicated the change in material type as well as size distribution. The results also show that these curves are distinguishable and can be related to the material and the change in its size. It is concluded that there is a potential of extending this technique to determine various other properties of silver products. The study suggests a design and development of a bespoke unit as a dedicated analysis tool and to address any anomalies arising from the current feasibility. This will have a huge industrial benefit in terms of cost reduction and time associated with the industrial analysis of silver material.

Indexed as

Cavity resonatorIndustrial analysisMicrowave sensingNon-destructive analysisNovel microwave analysisSilver productsSilver products characterisation

Identifiers

PMID28275317
PMCPMC5320009

What OpenQuestion holds

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LicenceCC BY
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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.