Evidence map›Paper›PMID 42783194›Full record

ArticleBiosensors2026

Electric-Field-Assisted Enrichment and Electrochemical Detection of Gram-Positive Bacteria Using an FEM-Guided Interdigitated Electrode Biosensor.

Zeeshan, Naeem Iqbal, Jaeyoung Choi

Abstract read
In one paragraph

Article in Biosensors, 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

3 authors.

ZeeshanSchool of Computing, Gachon University, Seongnam-si 13120, Gyeonggi-do, Republic of Korea.
Naeem IqbalCentre for Secure Information Technologies, Queen's University Belfast, Belfast BT3 9DT, UK.
Jaeyoung ChoiSchool of Computing, Gachon University, Seongnam-si 13120, Gyeonggi-do, Republic of Korea.ORCID 0000-0001-9118-8050

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dielectrophoretic (DEP) enrichment is a powerful strategy to enhance bacterial capture efficiency and accelerate the response of electrochemical biosensors by actively concentrating target bioparticles at the sensing interface. In this study, a combined numerical-experimental framework is developed to rationally design a DEP-assisted electrochemical biosensor with improved bacterial capture and detection performance. A finite-element modeling (FEM) approach was used to model the coupled electric field, dielectrophoretic force, and particle-transport phenomena, providing a quantitative basis for comparing bacterial trapping efficiency across different interdigitated electrode geometries. The modeling reveals that a wave-shaped interdigitated electrode (W_IDE) generates extended high-field regions and an enlarged effective capture area, resulting in an improved bacterial capture efficiency of 19% compared to 12% for the conventional rectangular interdigitated electrodes (R_IDE) under positive DEP (pDEP) conditions. Based on these insights, the W_IDE was fabricated on a printed circuit board (PCB) substrate, modified with platinum-black (Pt-black) to increase electroactive surface area, and interfaced with a custom-built 16-channel portable potentiostat unit, enabling sequential impedance measurements. The developed biosensor was applied to pDEP-assisted impedance detection of

Indexed as

Biosensing TechniquesElectrochemical TechniquesGram-Positive BacteriaElectrodesFinite Element AnalysisStaphylococcus aureuselectrochemical biosensorfinite-element modeling (FEM)gram-positive bacteriapassive bacterial detectionpDEP-assisted bacterial detectionpositive dielectrophoresis (pDEP)wave-shaped interdigitated electrode (W_IDE)

Identifiers

PMID42783194
PMCPMC13604522

What OpenQuestion holds

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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.