Evidence map›Paper›PMID 25694783›Full record

ArticleInternational journal of analytical chemistry2015

High Sensitive Sensor Fabricated by Reduced Graphene Oxide/Polyvinyl Butyral Nanofibers for Detecting Cu (II) in Water.

Rui Ding, Zhimin Luo, Xiuling Ma, Xiaoping Fan, Liqun Xue, Xiuzhu Lin, Sheng Chen

Abstract read
In one paragraph

Article in International journal of analytical chemistry, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Ultrasensitive Optical Chemosensor for Cu(II) Detection.International journal of analytical chemistry · 2019
    Article
  4. 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

7 authors.

Rui DingCollege of Environmental Science and Engineering, Fujian Normal University, 8 Shangsan Road, Fuzhou 350007, China.
Zhimin LuoJiangsu Key Laboratory for Organic Electronics & Information Displays and Institute of Advanced Materials (IAM), Nanjing University of Posts and Telecommunications, Nanjing 210046, China.
Xiuling MaCollege of Chemistry and Chemical Engineering, Fujian Normal University, 8 Shangsan Road, Fuzhou 350007, China.
Xiaoping FanCollege of Environmental Science and Engineering, Fujian Normal University, 8 Shangsan Road, Fuzhou 350007, China.
Liqun XueDepartment of Biology and Chemistry Engineering, Fuqing Branch of Fujian Normal University, 1 Longjiang Road, Fuqing 350300, China.
Xiuzhu LinDepartment of Biology and Chemistry Engineering, Fuqing Branch of Fujian Normal University, 1 Longjiang Road, Fuqing 350300, China.
Sheng ChenDepartment of Biology and Chemistry Engineering, Fuqing Branch of Fujian Normal University, 1 Longjiang Road, Fuqing 350300, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Graphene oxide (GO)/polyvinyl butyral (PVB) nanofibers were prepared by a simple electrospinning technique with PVB as matrix and GO as a functional nanomaterial. GO/PVB nanofibers on glassy carbon electrode (GCE) were reduced through electrochemical method to form reduced graphene oxide (RGO)/PVB nanofibers. The morphology and structure of GO/PVB nanofiber were studied by scanning election microscopy (SEM), transmission electron microscopy (TEM), and Fourier transform infrared (FTIR). RGO/PVB modified GCE was used for fabricating an electrochemical sensor for detecting Cu (II) in water. The analysis results showed that RGO/PVB modified GCE had good analytical results with the linear range of 0.06-2.2 μM, detection limit of 4.10 nM (S/N = 3), and the sensitivity of 103.51 μA·μM(-1)·cm(-2).

Identifiers

PMID25694783
PMCPMC4324952

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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.