Evidence map›Paper›PMID 32878341›Full record

ArticleNanomaterials (Basel, Switzerland)2020

Aerogels Based on Reduced Graphene Oxide/Cellulose Composites: Preparation and Vapour Sensing Abilities.

Yian Chen, Petra Pötschke, Jürgen Pionteck, Brigitte Voit, Haisong Qi

Erratum issuedAbstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Detection of gases and organic vapors by cellulose-based sensors.Analytical and bioanalytical chemistry · 2023
    Review
  3. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Yian ChenLeibniz-Institut für Polymerforschung Dresden e. V. (IPF), 01069 Dresden, Germany.
Petra PötschkeLeibniz-Institut für Polymerforschung Dresden e. V. (IPF), 01069 Dresden, Germany.ORCID 0000-0001-6392-7880
Jürgen PionteckLeibniz-Institut für Polymerforschung Dresden e. V. (IPF), 01069 Dresden, Germany.ORCID 0000-0003-2310-1106
Brigitte VoitLeibniz-Institut für Polymerforschung Dresden e. V. (IPF), 01069 Dresden, Germany.ORCID 0000-0002-4531-691X
Haisong QiState Key Laboratory of Pulp and Paper Engineering, South China University of Technology, Guangzhou 510640, China.

Funding

China Scholarship Council 201606240112
6 · The paper itself

Abstract

This paper reports on the preparation of cellulose/reduced graphene oxide (rGO) aerogels for use as chemical vapour sensors. Cellulose/rGO composite aerogels were prepared by dissolving cellulose and dispersing graphene oxide (GO) in aqueous NaOH/urea solution, followed by an in-situ reduction of GO to reduced GO (rGO) and lyophilisation. The vapour sensing properties of cellulose/rGO composite aerogels were investigated by measuring the change in electrical resistance during cyclic exposure to vapours with varying solubility parameters, namely water, methanol, ethanol, acetone, toluene, tetrahydrofuran (THF), and chloroform. The increase in resistance of aerogels on exposure to vapours is in the range of 7 to 40% with methanol giving the highest response. The sensing signal increases almost linearly with the vapour concentration, as tested for methanol. The resistance changes are caused by the destruction of the conductive filler network due to a combination of swelling of the cellulose matrix and adsorption of vapour molecules on the filler surfaces. This combined mechanism leads to an increased sensing response with increasing conductive filler content. Overall, fast reaction, good reproducibility, high sensitivity, and good differentiation ability between different vapours characterize the detection behaviour of the aerogels.

Indexed as

aerogelcelluloseconductive polymer compositereduced graphene oxidevapour sensor

Identifiers

PMID32878341
PMCPMC7560231

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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.