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Cited by 69

The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.

Iron nanoparticles synthesized using green tea extracts for the fenton-like degradation of concentrated dye mixtures at elevated temperatures

Truskewycz, Adam, Shukla, Ravi, Ball, Andrew S.·2016·Journal of Environmental Chemical Engineering
DOI 10.1016/j.jece.2016.10.008
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Abstract

Abstract Environmental harm caused by the release of textile dye contaminated wastewater from industry is an issue that requires immediate attention, particularly in developing countries. We herein demonstrate that green tea derived amorphous iron nanoparticles, in conjunction with Fenton like chemical processes, catabolise anthraquinone and azo dye mixtures that constitute a significant proportion of industrial dye waste. Iron nanoparticles, synthesized following a green tea mediated greener synthesis approach were able to degrade concentrated dye mixtures with over 90% decolourisation in only 20 min with 0.53 ppm nanoparticle concentration at a temperature of 70 °C. Detailed experimental degradation efficiencies were significantly pH and temperature dependant favouring lower pH values at temperatures between 70 and 90 °C, conditions which are commonly found in textile wastewaters. This research has shown the capacity for green tea synthesized nanoparticles to be used as a promoter for Fenton like dye degradation reactions. This rapid treatment approach may gain interest in the textile industries for dye waste remediation.

Overview

Integrity signals

Registry

Crossref · 10.1016/j.jece.2016.10.008

Cites

55 of 55 references verified0 citation errors · 0 not checkable

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Verification

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Citations

Cites

1 retracted

Research works printed but not linked: 1

  1. Kosaric, 2001, Biosurfactants and their application for soil bioremediation, biosurfactants for soil bioremediation, Food Technol. Biotechnol., 39, 295

Cited by

See all 69

Metadata

Authors
Truskewycz, A., Shukla, R., & Ball, A. S.
Venue
Journal of Environmental Chemical Engineering
Publisher
Elsevier BV
Published
2016-12
Volume
4
Issue
4
Pages
4409-4417
ISSN
2213-3437
DOI
10.1016/j.jece.2016.10.008
Cited by
69
References
55
Language
en
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.