Evidence map›Paper›PMID 35865592›Full record

ArticleRSC advances2022

A novel, highly sensitive electrochemical 1,4-dioxane sensor based on reduced graphene oxide-curcumin nanocomposite.

Sana Fathima T K, Arshiya Banu A, T Devasena, Sundara Ramaprabhu

Abstract read
In one paragraph

Article in RSC advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Sana Fathima T KAlternative Energy and Nanotechnology Laboratory, Nano Functional Materials and Technology Centre (NFMTC), Department of Physics, Indian Institute of Technology Madras Chennai 600036 India ramp@iitm.ac.in.ORCID https://orcid.org/0000-0002-1881-7364
Arshiya Banu ACentre for Nanoscience and Technology, A.C. Tech Campus, Anna University Chennai 600025 India.
T DevasenaCentre for Nanoscience and Technology, A.C. Tech Campus, Anna University Chennai 600025 India.
Sundara RamaprabhuAlternative Energy and Nanotechnology Laboratory, Nano Functional Materials and Technology Centre (NFMTC), Department of Physics, Indian Institute of Technology Madras Chennai 600036 India ramp@iitm.ac.in.ORCID https://orcid.org/0000-0002-7960-9470

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

1,4-Dioxane is a carcinogenic, non-biodegradable, organic water pollutant which is used as a solvent in various industries. It is also formed as an undesired by-product in the cosmetic and pharmaceutical industry. Given its carcinogenicity and ability to pollute, it is desirable to develop a sensitive and selective sensor to detect it in drinking water and other water bodies. Current works on this sensor are very few and involve complex metal oxide composite systems. A sensitive electrochemical sensor for 1,4-dioxane was developed by modifying a glassy carbon electrode (GCE) with a reduced graphene oxide-curcumin (rGO-CM) nanocomposite synthesized by a simple solution approach. The prepared rGO-CM was characterized by X-ray Diffraction (XRD), Fourier Transform Infrared (FTIR) Spectroscopy, Raman spectroscopy, UV-Vis spectroscopy, and Scanning Electron Microscopy (SEM). The rGO-CM/GCE sensor was employed for the detection of 1,4-dioxane in the range of 0.1-100 μM. Although, the detection range is narrower compared to reported literature, the sensitivity obtained for the proposed sensor is far superior. Moreover, the limit of detection (0.13 μM) is lower than the dioxane detection target defined by the World Health Organization (0.56 μM). The proposed rGO-CM/GCE also showed excellent stability and good recovery values in real sample (tap water and drinking water) analysis.

Identifiers

PMID35865592
PMCPMC9251910

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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.