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Feasibility of fluoride removal using calcined Mactra veneriformis shells: Adsorption mechanism and optimization study using RSM and ANN
  • Choi, Moon Yeong ;
  • Kang, Jin Kyu ;
  • Lee, Chang Gu ;
  • Park, Seong Jik
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dc.contributor.authorChoi, Moon Yeong-
dc.contributor.authorKang, Jin Kyu-
dc.contributor.authorLee, Chang Gu-
dc.contributor.authorPark, Seong Jik-
dc.date.issued2022-12-01-
dc.identifier.issn0263-8762-
dc.identifier.urihttps://dspace.ajou.ac.kr/dev/handle/2018.oak/33040-
dc.description.abstractIn this study, Mactra veneriformis shells (MVS), a seafood by-product with high Ca content, was assessed as an adsorbent for fluoride removal from contaminated water. MVS was calcined at various temperatures (100–900 °C), and MVS calcined at 800 and 900 °C (MVS-800 and MVS-900) had the highest adsorption capacity. The high fluoride adsorption of MVS-800 and MVS-900 originated from the conversion of CaCO3 present in the raw MVS to CaO and Ca(OH)2 by calcination at high temperatures. The kinetic and equilibrium adsorption of fluoride by MVS-800 were accurately described by the pseudo-second-order and Langmuir models, respectively. The maximum fluoride adsorption capacity was 244.61 mg/g, which is comparable to that of other adsorbents reported in the literature. The enthalpy and entropy of adsorption were 7.42 kJ/mol and 56.48 J/mol‧K, respectively, and the Gibbs free energy was negative at all reaction temperatures. The interactive effects of pH, reaction time, dosage, and temperature and the optimal values for fluoride removal by MVS-800 were explored using response surface methodology (RSM) and artificial neural networks (ANN). The RSM results demonstrated that reaction time, dosage, and temperature significantly influenced fluoride removal; however, pH was an insignificant term. The accuracy of the ANN model (R2 = 0.9932) for predicting fluoride removal was higher than that of RSM (R2 = 0.9347). The optimal fluoride removal at a dosage of 3.3 g/L under optimized conditions (pH 5; reaction time 9 h; temperature 35 °C) was predicted to be 98.5% by the ANN model.-
dc.description.sponsorshipThis work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean Government (MSIT) [grant number 2020R1C1C1008982 ].-
dc.language.isoeng-
dc.publisherInstitution of Chemical Engineers-
dc.subject.meshAdsorption mechanism-
dc.subject.meshArtificial neural network modeling-
dc.subject.meshContaminated water-
dc.subject.meshFluoride adsorptions-
dc.subject.meshFluoride removal-
dc.subject.meshMactra veneriformis shell-
dc.subject.meshMechanism studies-
dc.subject.meshOptimization studies-
dc.subject.meshPortlandite-
dc.subject.meshResponse-surface methodology-
dc.titleFeasibility of fluoride removal using calcined Mactra veneriformis shells: Adsorption mechanism and optimization study using RSM and ANN-
dc.typeArticle-
dc.citation.endPage1053-
dc.citation.startPage1042-
dc.citation.titleChemical Engineering Research and Design-
dc.citation.volume188-
dc.identifier.bibliographicCitationChemical Engineering Research and Design, Vol.188, pp.1042-1053-
dc.identifier.doi10.1016/j.cherd.2022.10.031-
dc.identifier.scopusid2-s2.0-85141526885-
dc.identifier.urlhttp://www.elsevier.com/wps/find/journaldescription.cws_home/713871/description#description-
dc.subject.keywordArtificial neural networks-
dc.subject.keywordCalcination-
dc.subject.keywordFluoride adsorption-
dc.subject.keywordMactra veneriformis shells-
dc.subject.keywordPortlandite-
dc.subject.keywordResponse surface methodology-
dc.description.isoafalse-
dc.subject.subareaChemistry (all)-
dc.subject.subareaChemical Engineering (all)-
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