Evidence map›Paper›PMID 33352634›Full record

ArticleSensors (Basel, Switzerland)2020

Perfluorooctanesulfonic Acid Detection Using Molecularly Imprinted Polyaniline on a Paper Substrate.

Ting-Yen Chi, Zheyuan Chen, Jun Kameoka

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.5field-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

9 citing papers in PubMed, 28 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Review
  9. Review
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 at 1 institution in 1 country.

Ting-Yen ChiDepartment of Materials Science and Engineering, Texas A&M University, College Station, TX 77843, USA.ORCID 0000-0002-8160-7239
Zheyuan ChenDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA.
Jun KameokaDepartment of Materials Science and Engineering, Texas A&M University, College Station, TX 77843, USA.
Texas A&M University · US

Funding

Bill and Melinda Gates Institute for Population and Reproductive Health OPP 1199456
6 · The paper itself

Abstract

Perfluorinated compounds like perfluorooctanesulfonic acid (PFOS) are synthetic water pollutants and have accumulated in environments for decades, causing a serious global health issue. Conventional assays rely on liquid chromatography and mass spectroscopy that are very expensive and complicated and thus limit the large-scale monitoring of PFOS in wastewater. To achieve low-cost and accurate detection of PFOS, we designed a paper-based sensor with molecularly imprinted polyaniline electrodes that have recognition sites specific to PFOS. The calibration curve of resistivity ratios as a function of PFOS concentrations has a linear range from 1 to 100 ppt with a coefficient of determination of 0.995. The estimated limit of detection is 1.02 ppt. We also investigated attenuated total reflectance Fourier-transform infrared spectroscopy (ATR-FTIR) and X-ray photoelectron spectroscopy (XPS) spectra of the surface of the polyaniline (PANI) electrodes to propose the potential recognition sites in polyaniline matrix and the detection mechanism. This electrical paper sensor with low cost and excellent sensitivity and selectivity provides the potential for large-scale monitoring of wastewater.

Indexed as

low-costmolecularly imprinted polymerpaper sensorperfluorooctanesulfonic acidpolyaniline

Identifiers

PMID33352634
PMCPMC7765859
OpenAlexW3113124179

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.