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Monitoring of decolorization of a two dyes mixture using spectrophotometric data and multivariate curve resolution: modeling the removal process using an experimental design method
Abstract
Developing a simple analytical method to determine azo dyes in environmental samples is important. Spectrophotometric techniques remain largely used in this field because of the easy interpretation and handling of the spectral data. But, this method suffers a main problem, spectral overlapping. In this paper, in spite of spectral overlapping, multivariate curve-alternating least squares was used to determine Acid Red 27 and Methyl Red dyes in a mixture of them. Resolution of binary mixtures of analytes with minimum sample pre-treatment and without analyte separation was successfully achieved by analyzing the UV-Vis spectral data. Also, central composite design was applied for modeling of the decolorization of a dye solution that contains two dyes using the Fenton reaction. The investigated factors (variables) were the initial concentration of Fe(II), the initial concentration of the two dyes and the initial H2O2 concentration.
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“Although it is mainly the mixtures of dyes that are encountered in the actual effluents from textile industry, there are very limited reports examining such mixtures of dyes 216-218 and even fewer that include an anthraquinone dye within the dye mixture 155, 219, 220 .”
From Degradation of anthraquinone dyes from effluents: A review focusing on enzymatic dye degradation with industrial potential (2020) · cites this paper as [216]
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Cited by
Routoula, E., & Patwardhan, S. V. (2020) · Environmental Science & Technology · doi:10.1021/acs.est.9b03737 · Cited by 579
Metadata
- Authors
- Naseri, A., & Ayadi-Anzabi, H.
- Venue
- Anal. Methods
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2012
- Volume
- 4
- Issue
- 1
- Pages
- 153-161
- ISSN
- 1759-9660
- 1759-9679
- Cited by
- 11
- References
- 0
- Language
- en
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- Naseri, A., & Ayadi-Anzabi, H. (2012). Monitoring of decolorization of a two dyes mixture using spectrophotometric data and multivariate curve resolution: modeling the removal process using an experimental design method. Anal. Methods. https://doi.org/10.1039/c1ay05448a
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