Evidence map›Paper›PMID 41471648›Full record

ArticleSensors (Basel, Switzerland)2025

Toward Detection of Inert PFAS: Single/Few-CNT Devices for Sensing PFOA.

Collins Dormena, Obed Appiah, Taher Ghomian

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. 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.

Collins DormenaDepartment of Electrical and Computer Engineering, University of Maine, Orono, ME 04469, USA.ORCID 0009-0005-4928-9903
Obed AppiahDepartment of Electrical and Computer Engineering, University of Maine, Orono, ME 04469, USA.
Taher GhomianDepartment of Electrical and Computer Engineering, University of Maine, Orono, ME 04469, USA.ORCID 0000-0001-5566-2085

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electron transport in carbon nanotubes (CNTs) is highly sensitive to interactions with their local environment, making them promising candidates for sensing applications. Specifically, this could allow detection of electrochemically and optically inert compounds that typically require complex and expensive analytical techniques. In this study, we examine how single-walled carbon nanotubes (SWCNTs) respond to perfluorooctanoic acid (PFOA), a common per- and polyfluoroalkyl substance (PFAS). To improve sensitivity, we employ a single/few-CNT device setup where a small number of SWCNTs were aligned across nanogaps between gold electrodes with the dielectrophoresis method. This structure addresses the challenges of large CNT networks, such as inter-CNT interactions, drift, and degradation, resulting in improved stability for practical applications. Results showed that device resistance drops as a function of PFOA concentrations. Additionally, positive gate voltage enhances sensitivity by attracting negatively charged PFOA molecules to the SWCNT surface. Specifically, we report that the sensitivity increases by nearly an order of magnitude under a 0.3 V gate bias. Impedance spectroscopy reveals distinct amplitude and phase signatures, enabling selective detection of PFOA among different analytes. Applying gate voltage further enhances sensor selectivity, highlighting the potential of gated SWCNT devices for accurate and selective environmental monitoring. The device demonstrates promising performance as a robust platform for creating single/few-CNT nanosensors for detecting electrochemically and optically inert substances like PFAS molecules.

Indexed as

carbonCNT-PFAS interactionnanosensornanotube PFAS

Identifiers

PMID41471648
PMCPMC12736847

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.