Computational and statistical modeling for parameters optimization of electrochemical decontamination of synozol red dye wastewater

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dc.contributor.authorKhan, Saad Ullah [UNESP]
dc.contributor.authorKhan, Hammad
dc.contributor.authorAnwar, Sajid
dc.contributor.authorKhan, Sabir [UNESP]
dc.contributor.authorBoldrin Zanoni, Maria V. [UNESP]
dc.contributor.authorHussain, Sajjad
dc.contributor.institutionGIK Institute of Engineering Sciences and Technology
dc.contributor.institutionUniversidade Federal de Mato Grosso do Sul (UFMS)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2020-12-12T02:38:58Z
dc.date.available2020-12-12T02:38:58Z
dc.date.issued2020-08-01
dc.description.abstractIn this study, computational and statistical models were applied to optimize the inherent parameters of an electrochemical decontamination of synozol red. The effect of various experimental variables such as current density, initial pH and concentration of electrolyte on degradation were assessed at Ti/RuO0·3TiO0·7O2 anode. Response surface methodology (RSM) based central composite design was applied to investigate interdependency of studied variables and train an artificial neural network (ANN) to envisage the experimental training data. The presence of fifteen neurons proved to have optimum performance based on maximum R2, mean absolute error, absolute average deviation and minimum mean square error. In comparison to RSM and empirical kinetics models, better prediction and interpretation of the experimental results were observed by ANN model. The sensitive analysis revealed the comparative significance of experimental variables are pH = 61.03%>current density = 17.29%>molar concentration of NaCl = 12.7%>time = 8.98%. The optimized process parameters obtained from genetic algorithm showed 98.6% discolorization of dye at pH 2.95, current density = 5.95 mA cm−2, NaCl of 0.075 M in 29.83 min of electrolysis. The obtained results revealed that the use of statistical and computational modeling is an adequate approach to optimize the process variables of electrochemical treatment.en
dc.description.affiliationFaculty of Materials and Chemical Engineering GIK Institute of Engineering Sciences and Technology
dc.description.affiliationFaculdade de Engenharias Arquitetura e Urbanismo e Geografia Universidade Federal de Mato Grosso do Sul Cidade Universitária
dc.description.affiliationFaculty of Computer Sciences and Engineering GIK Institute of Engineering Sciences and Technology
dc.description.affiliationInstitute of Chemistry Araraquara São Paulo State University (UNESP), Av. Prof. Francisco Degni 55
dc.description.affiliationNational Institute for Alternative Technologies of Detection Toxicological Evaluation and Removal of Micropollutants and Radioactivies (INCT-DATREM) São Paulo State University (UNESP) Institute of Chemistry
dc.description.affiliationUnespInstitute of Chemistry Araraquara São Paulo State University (UNESP), Av. Prof. Francisco Degni 55
dc.description.affiliationUnespNational Institute for Alternative Technologies of Detection Toxicological Evaluation and Removal of Micropollutants and Radioactivies (INCT-DATREM) São Paulo State University (UNESP) Institute of Chemistry
dc.description.sponsorshipGhulam Ishaq Khan Institute of Engineering Sciences and Technology
dc.identifierhttp://dx.doi.org/10.1016/j.chemosphere.2020.126673
dc.identifier.citationChemosphere, v. 253.
dc.identifier.doi10.1016/j.chemosphere.2020.126673
dc.identifier.issn1879-1298
dc.identifier.issn0045-6535
dc.identifier.scopus2-s2.0-85083058232
dc.identifier.urihttp://hdl.handle.net/11449/201679
dc.language.isoeng
dc.relation.ispartofChemosphere
dc.sourceScopus
dc.subjectDegradation
dc.subjectDyes wastewater
dc.subjectElectrochemical degradation
dc.subjectModeling
dc.subjectOptimization
dc.titleComputational and statistical modeling for parameters optimization of electrochemical decontamination of synozol red dye wastewateren
dc.typeArtigo

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