Evidence map›Paper›PMID 28594387›Full record

ArticleSensors (Basel, Switzerland)2017

3D Printing-Based Integrated Water Quality Sensing System.

Muinul Banna, Kaustav Bera, Ryan Sochol, Liwei Lin, Homayoun Najjaran, Rehan Sadiq, Mina Hoorfar

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

7 citing papers in PubMed, 31 citations in OpenAlex.

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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 3 countries.

Muinul BannaSchool of Engineering, University of British Columbia, Kelowna, BC V1V 1V7, Canada. banna.mh@gmail.com.
Kaustav BeraIndian Institute of Technology, Kharagpur, West Bengal 721302, India. kaustav0bera@gmail.com.
Ryan SocholDepartment of Mechanical Engineering, University of Maryland, College Park, MD 20742, USA. rsochol@umd.edu.
Liwei LinDepartment of Mechanical Engineering, University of California Berkeley, Berkeley, CA 94720, USA. lwlin@me.berkeley.edu.
Homayoun NajjaranSchool of Engineering, University of British Columbia, Kelowna, BC V1V 1V7, Canada. homayoun.najjaran@ubc.ca.
Rehan SadiqSchool of Engineering, University of British Columbia, Kelowna, BC V1V 1V7, Canada. Rehan.Sadiq@ubc.ca.
Mina HoorfarSchool of Engineering, University of British Columbia, Kelowna, BC V1V 1V7, Canada. mina.hoorfar@ubc.ca.
University of British Columbia · CAIndian Institute of Technology Kharagpur · INUniversity of California, Berkeley · USUniversity of Maryland, College Park · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The online and accurate monitoring of drinking water supply networks is critically in demand to rapidly detect the accidental or deliberate contamination of drinking water. At present, miniaturized water quality monitoring sensors developed in the laboratories are usually tested under ambient pressure and steady-state flow conditions; however, in Water Distribution Systems (WDS), both the pressure and the flowrate fluctuate. In this paper, an interface is designed and fabricated using additive manufacturing or 3D printing technology-material extrusion (Trade Name: fused deposition modeling, FDM) and material jetting-to provide a conduit for miniaturized sensors for continuous online water quality monitoring. The interface is designed to meet two main criteria: low pressure at the inlet of the sensors and a low flowrate to minimize the water bled (i.e., leakage), despite varying pressure from WDS. To meet the above criteria, a two-dimensional computational fluid dynamics model was used to optimize the geometry of the channel. The 3D printed interface, with the embedded miniaturized pH and conductivity sensors, was then tested at different temperatures and flowrates. The results show that the response of the pH sensor is independent of the flowrate and temperature. As for the conductivity sensor, the flowrate and temperature affect only the readings at a very low conductivity (4 µS/cm) and high flowrates (30 mL/min), and a very high conductivity (460 µS/cm), respectively.

Indexed as

3D-Printingminiaturized sensorsonline monitoringwater quality

Identifiers

PMID28594387
PMCPMC5492283
OpenAlexW2622261466

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.