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Cited by 541

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Application of response surface methodology in physicochemical removal of dyes from wastewater: A critical review

Karimifard, Shahab, Alavi Moghaddam, Mohammad Reza·2018·Science of The Total Environment

Abstract

Response surface methodology (RSM) is a powerful tool in designing the experiments and optimizing different environmental processes. However, when it comes to wastewater treatment and specifically dye-containing wastewater, two questions arise; "Is RSM being used correctly?" and "Are all capabilities of RSM being exploited properly?". The current review paper aims to answer these questions by scrutinizing different physicochemical processes that utilized RSM in dye removal. The literature that applied RSM to adsorption, advanced oxidation processes, coagulation/flocculation and electrocoagulation processes were critically reviewed in this paper. The common errors in applying RSM to physicochemical removal of dyes are identified and some suggestions are made for future studies.

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Crossref · 10.1016/j.scitotenv.2018.05.355

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Metadata

Authors
Karimifard, S., & Alavi Moghaddam, M. R.
Venue
Science of The Total Environment
Publisher
Elsevier BV
Published
2018-11
Volume
640-641
Pages
772-797
ISSN
0048-9697 (ISSN-L)
OpenAlex
W2806596768
Cited by
541
References
9
FWCI
18.78
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Application of response surface methodology in physicochemical removal of dyes from wastewater: A critical review. https://app.cochat.ai/papers/10.1016/j.scitotenv.2018.05.355
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Karimifard, S., & Alavi Moghaddam, M. R. (2018). Application of response surface methodology in physicochemical removal of dyes from wastewater: A critical review. Science of The Total Environment. https://doi.org/10.1016/j.scitotenv.2018.05.355

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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.