Evidence map›Paper›PMID 40401923›Full record

ArticleACS applied materials & interfaces2025

Dielectrophoresis-Enhanced Graphene Field-Effect Transistors for Nano-Analyte Sensing.

Nezhueyotl Izquierdo, Ruixue Li, Peter R Christenson, Sang-Hyun Oh, Steven J Koester

Abstract read
In one paragraph

Article in ACS applied materials & interfaces, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Nezhueyotl IzquierdoDepartment of Electrical and Computer Engineering, University of Minnesota, 200 Union Street SE, Minneapolis, Minnesota 55455, United States.ORCID 0000-0002-5565-1957
Ruixue LiDepartment of Electrical and Computer Engineering, University of Minnesota, 200 Union Street SE, Minneapolis, Minnesota 55455, United States.ORCID 0009-0007-7703-8495
Peter R ChristensonDepartment of Electrical and Computer Engineering, University of Minnesota, 200 Union Street SE, Minneapolis, Minnesota 55455, United States.ORCID 0000-0003-3979-7945
Sang-Hyun OhDepartment of Electrical and Computer Engineering, University of Minnesota, 200 Union Street SE, Minneapolis, Minnesota 55455, United States.ORCID 0000-0002-6992-5007
Steven J KoesterDepartment of Electrical and Computer Engineering, University of Minnesota, 200 Union Street SE, Minneapolis, Minnesota 55455, United States.ORCID 0000-0001-6104-1218

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dielectrophoretic (DEP) sensing is an extremely important sensing modality that enables the rapid capture and detection of polarizable particles of nanoscale size. This makes it a versatile tool for applications in medical diagnostics, environmental monitoring, and materials science. Because DEP relies upon the creation of sharp electrode edges, its sensitivity is fundamentally limited by the electrode thickness. Graphene, with its monolayer thickness, enables scaling of the DEP force, allowing trapping of particles at graphene edges at ultralow voltages. However, to date, this enhanced trapping efficiency of graphene has not been translated into an effective sensing geometry. Here, we demonstrate the expansion of graphene DEP trapping capability into a graphene field effect transistor (GFET) geometry that allows the trapped particles to be electrically detected. This four-terminal multifunctional hybrid device structure operates in three distinct modes: DEP, GFET, and DEP-GFET. By segmenting the channel of the GFET into multiple parallel channels, greatly increased density of particle trapping is demonstrated using fluorescence microscopy analysis. We show further enhancement of the trapping efficiency using engineered "nanosites," which are holes in the graphene with size on the order of 200-300 nm. Scanning electron microscope analysis of immobilized gold nanoparticles (AuNPs) shows trapping efficiency >90% for properly engineered nanosites. We also demonstrate real-time, rapid electrical sensing of AuNPs, with >2% current change occurring in 4.1 s, as well as rapid sensing of a variety of biomolecule-coated nanoparticles. This work shows that graphene DEP is an effective platform for nanoparticle and biomolecule sensing that overcomes diffusion-limited and Brownian motion-based interactions.

Indexed as

dielectrophoresisDNAGFETgraphenepolystyrenesensortrapping

Identifiers

PMID40401923
PMCPMC12147070

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.