Evidence map›Paper›PMID 42280913›Full record

ArticleSensors (Basel, Switzerland)2026

A Simulation Study of a Novel Electrokinetic-Based Focusing Technique to Enhance the Real-Time Detection of Microplastics in Water Flow.

Abdullah Abdulhameed, Yaqub Mahnashi

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Abdullah AbdulhameedCenter for Communication Systems and Sensing, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia.ORCID 0000-0002-6122-8995
Yaqub MahnashiElectrical Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia.ORCID 0000-0003-3400-466X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The contamination of aquatic environments, including treated and drinking water, by microplastics poses a significant threat to ecosystems and human health. Current detection methods often rely on slow laboratory-based tests and offline analysis, which do not support real-time monitoring. This paper presents a novel focusing and concentrating device designed to enhance the real-time detection of microplastics in flowing water. The device utilizes an electrokinetic manipulation mechanism to focus microplastics toward the center of the water flow inside a pipe or fluid channel. A set of 3D rectangular electrodes, with dimensions of 5 mm × 2.5 mm × 1 mm, are arranged circumferentially and longitudinally along the inner perimeter of the fluid channel to generate an intense, non-uniform electric field. Simulation results indicate that microplastics near the channel wall experience a repulsive force on the order of 10-16 to 10-10 N toward the channel center. The applied signal amplitude and the physical properties of the microplastics strongly influence this repulsive force. The trajectories and output concentration of microplastics are investigated under varied conditions. A Voltage of approximately 25 V and a flow rate of 0.05 m/s are found to be ideal for concentrating microplastics into a narrow particle stream, enabling more efficient downstream detection and analysis. Pre-concentrating microplastics in fluid channels prior to sensing is expected to increase sensor sensitivity and improve selectivity.

Indexed as

3D electrodeselectrokinetic manipulationflow rate optimizationfluid channelmicroplasticsnon-uniform electric fieldparticle focusingpre-concentration for sensingreal-time detectionrepulsive force

Identifiers

PMID42280913
PMCPMC13259111

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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.