Evidence map›Paper›PMID 34062849›Full record

ArticleSensors (Basel, Switzerland)2021

Microwave Sensors for

Ilaria Frau, Stephen Wylie, Patrick Byrne, Patrizia Onnis, Jeff Cullen, Alex Mason, Olga Korostynska

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.6field-weighted citation impact, top 18% of its field
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

9 citing papers in PubMed, 33 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Dielectric Permittivity in Copper Leaching: A Review.Sensors (Basel, Switzerland) · 2025
    Review
  6. Review
  7. Article
  8. Review
  9. 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

7 authors at 4 institutions in 2 countries.

Ilaria FrauFaculty of Engineering and Technology, Built Environment and Sustainable Technologies (BEST) Research Institute, Liverpool John Moores University, Liverpool L3 3AF, UK.ORCID 0000-0001-9238-6606
Stephen WylieFaculty of Engineering and Technology, Built Environment and Sustainable Technologies (BEST) Research Institute, Liverpool John Moores University, Liverpool L3 3AF, UK.
Patrick ByrneSchool of Biological and Environmental Science, Liverpool John Moores University, Liverpool L3 3AF, UK.ORCID 0000-0002-2699-052X
Patrizia OnnisSchool of Biological and Environmental Science, Liverpool John Moores University, Liverpool L3 3AF, UK.
Jeff CullenFaculty of Engineering and Technology, Built Environment and Sustainable Technologies (BEST) Research Institute, Liverpool John Moores University, Liverpool L3 3AF, UK.ORCID 0000-0003-0401-4613
Alex MasonFaculty of Engineering and Technology, Built Environment and Sustainable Technologies (BEST) Research Institute, Liverpool John Moores University, Liverpool L3 3AF, UK.
Olga KorostynskaFaculty of Science and Technology, Norwegian University of Life Sciences, 1432 Ås, Norway.ORCID 0000-0003-0387-6609
Liverpool John Moores University · GBAnimalia (Norway) · NOOsloMet – Oslo Metropolitan University · NOUniversity of Exeter · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thousands of pollutants are threatening our water supply, putting at risk human and environmental health. Between them, trace metals are of significant concern, due to their high toxicity at low concentrations. Abandoned mining areas are globally one of the major sources of toxic metals. Nowadays, no method can guarantee an immediate response for quantifying these pollutants. In this work, a novel technique based on microwave spectroscopy and planar sensors for in situ real-time monitoring of water quality is described. The sensors were developed to directly probe water samples, and in situ trial measurements were performed in freshwater in four polluted mining areas in the UK. Planar microwave sensors were able to detect the water pollution level with an immediate response specifically depicted at three resonant peaks in the GHz range. To the authors' best knowledge, this is the first time that planar microwave sensors were tested in situ, demonstrating the ability to use this method for classifying more and less polluted water using a multiple-peak approach.

Indexed as

in situ measurementsmicrowave spectroscopymining-impacted waterplanar sensorsreal-time monitoringtoxic metalswater quality

Identifiers

PMID34062849
PMCPMC8125159
OpenAlexW3157103193

What Socratic 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 Socratic graph.