Evidence map›Paper›PMID 38073859›Full record

ArticleEnvironmental science. Nano2023

A cross-reactive plasmonic sensing array for drinking water assessment.

Justin R Sperling, Baptiste Poursat, Laurie Savage, Iain Christie, Calum Cuthill, Badri L Aekbote, Katie McGuire, Affar S Karimullah, Jill Robbie, William T Sloan and 3 more

Abstract read
In one paragraph

Article in Environmental science. Nano, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

13 authors.

Justin R SperlingJames Watt School of Engineering, University of Glasgow Glasgow UK Alasdair.Clark@glasgow.ac.uk.ORCID https://orcid.org/0000-0002-1708-2474
Baptiste PoursatJames Watt School of Engineering, University of Glasgow Glasgow UK Alasdair.Clark@glasgow.ac.uk.ORCID https://orcid.org/0000-0001-5029-9897
Laurie SavageJames Watt School of Engineering, University of Glasgow Glasgow UK Alasdair.Clark@glasgow.ac.uk.ORCID https://orcid.org/0000-0003-0167-4122
Iain ChristieJames Watt School of Engineering, University of Glasgow Glasgow UK Alasdair.Clark@glasgow.ac.uk.
Calum CuthillJames Watt School of Engineering, University of Glasgow Glasgow UK Alasdair.Clark@glasgow.ac.uk.
Badri L AekboteJames Watt School of Engineering, University of Glasgow Glasgow UK Alasdair.Clark@glasgow.ac.uk.
Katie McGuireSchool of Chemistry, University of Glasgow Glasgow UK.
Affar S KarimullahSchool of Chemistry, University of Glasgow Glasgow UK.ORCID https://orcid.org/0000-0002-8792-9829
Jill RobbieSchool of Law, University of Glasgow Glasgow UK.ORCID https://orcid.org/0000-0002-5376-8908
William T SloanJames Watt School of Engineering, University of Glasgow Glasgow UK Alasdair.Clark@glasgow.ac.uk.
Caroline Gauchotte-LindsayJames Watt School of Engineering, University of Glasgow Glasgow UK Alasdair.Clark@glasgow.ac.uk.ORCID https://orcid.org/0000-0002-4970-5031
William J PevelerSchool of Chemistry, University of Glasgow Glasgow UK.ORCID https://orcid.org/0000-0002-9829-2683
Alasdair W ClarkJames Watt School of Engineering, University of Glasgow Glasgow UK Alasdair.Clark@glasgow.ac.uk.ORCID https://orcid.org/0000-0001-9797-5776

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The continuous monitoring of remote drinking water purification systems is a global challenge with direct consequences for human and environmental health. Here, we utilise a "nano-tastebud" sensor comprised of eight chemically-tailored plasmonic metasurfaces, for testing the composition of drinking water. Through undertaking a full chemometric analysis of the water samples and likely contaminants we were able to optimise the sensor specification to create an array of suitable tastebuds. By generating a unique set of optical responses for each water sample, we show that the array-based sensor can differentiate between untreated influent and treated effluent water with over 95% accuracy in flow and can detect compositional changes in distributed modified tap water. Once fully developed, this system could be integrated into water treatment facilities and distribution systems to monitor for changes in water composition.

Identifiers

PMID38073859
PMCPMC10702629

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Registered trials

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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.