Evidence map›Paper›PMID 32193477›Full record

ArticleScientific reports2020

Green synthesis of ZnO nanoparticles decorated on polyindole functionalized-MCNTs and used as anode material for enzymatic biofuel cell applications.

Inamuddin, Nimra Shakeel, Mohd Imran Ahamed, Suvardhan Kanchi, Heba Abbas Kashmery

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Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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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

14 citing papers in PubMed.

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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

5 authors.

InamuddinChemistry Department, Faculty of Science, King Abdulaziz University, P. O. Box 80203, Jeddah, 21589, Saudi Arabia. inamuddin@zhcet.ac.in.ORCID http://orcid.org/0000-0003-0524-9940
Nimra ShakeelDepartment of Chemistry, Faculty of Science, Aligarh Muslim University, Aligarh, 202002, Uttar Pradesh, India.
Mohd Imran AhamedDepartment of Chemistry, Faculty of Science, Aligarh Muslim University, Aligarh, 202002, Uttar Pradesh, India.
Suvardhan KanchiDepartment of Chemistry, Faculty of Applied Science, Durban University of Technology, Durban, 4000, South Africa.ORCID http://orcid.org/0000-0003-3299-7821
Heba Abbas KashmeryChemistry Department, Faculty of Science, King Abdulaziz University, P. O. Box 80203, Jeddah, 21589, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Presently, one of the most important aspects for the development of enzymatic biofuel cells (EBFCs) is to synthesize the novel electrode materials that possess high current density, low open-circuit voltage (OCV) and long-term stability. To achieve the above attributes, lots of new strategies are being used by the researchers for the development of advanced materials. Nowadays, nanomaterials and nanocomposites are the promising material that has been utilized as effective electrode material in solar cells, supercapacitors and biofuel cells application. Herein, we account for a novel electrocatalyst as electrode material that comprised ZnO nanoparticles decorated on the surface of polyindole (PIn)-multi-walled carbon nanotube (MWCNT), for the immobilization of glucose oxidase (GOx) enzyme and mediator (Ferritin). The PIn-MWCNT scaffold is prepared via in situ chemical oxidative polymerization of indole on the surface of MWCNT and assessed by myriad techniques. The micrograph of scanning electron microscopy (SEM) designated the interconnected morphology of MWCNTs in the polymer matrix. X-ray diffraction spectroscopy (XRD) and Fourier transform infrared spectroscopy (FTIR), confirm the crystallinity and different functional groups available in the synthesized material, respectively. The electrochemical assessment demonstrates that the ZnO/PIn-MWCNT/Frt/GOx nanobiocatalyst exhibits much higher electrocatalytic activity towards the oxidation of glucose with a maximum current density of 4.9 mA cm

Identifiers

PMID32193477
PMCPMC7081323

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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.