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Experimental and Modeling Studies on the Removal of Bromocresol Green From Aqueous Solutions by Using Pine Cone-Derived Activated Biochar

dc.authorscopusid8851687700
dc.authorscopusid56511715400
dc.authorwosidYildiz'Uzun, Zeynep/Ljk-5266-2024
dc.authorwosidKaya, Nihan/Aao-6120-2021
dc.contributor.authorKaya, Nihan
dc.contributor.authorUzun, Zeynep Yildiz
dc.date.accessioned2025-12-11T00:43:43Z
dc.date.issued2024
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Kaya, Nihan] Ondokuz Mays Univ, Engn Fac, Dept Chem Engn, Samsun, Turkiye; [Uzun, Zeynep Yildiz] Sinop Univ, Boyabat Vocat Sch, Dept Chem & Chem Proc Technol, Sinop, Turkiyeen_US
dc.description.abstractThis study was carried out to evaluate the potential application of pine cone (PC)-derived activated biochar which has a surface area of 1714.5 m(2)/g for bromocresol green (BCG) dye removal from aqueous solution. Batch adsorption experiments involved varying pH, temperature, contact time, adsorbent dosage, and initial dye concentrations and the maximum BCG removal (96.27%) occurred at pH: 2.0, T: 45 degrees C, m: 2 g/L, t: 15 min., and C-o: 25 mg/L. To study the characteristics of adsorption, the adsorption kinetic isotherm and thermodynamic parameters were employed. The experimental data was evaluated to fit well with the Temkin isotherm (R-2=0.99) and the adsorption process followed pseudo-first-order kinetics (R-2=0.96). Thermodynamic parameters obtained from the adsorptive uptake showed that the interaction was endothermic and spontaneous in nature. The regenerated activated PC biochar showed good performance (95.0%), even, after 4th regeneration. To predict the BCG adsorption capacity of activated PC biochar, many different artificial neural network (ANN) models have been developed. The optimal ANN model gave mean absolute error (MAE), mean bias error (MBE), root mean square error (RMSE), and R-2 values of 0.036, 0.578, 0.947, and 0.999, respectively. The results obtained showed that ANN can be used to effectively model the BCG adsorption process.en_US
dc.description.sponsorshipThe authors would like to thank Hitit University for its support and also would like to thank to Assoc. Prof. Dr. Yunus Onal for his support in the preparation of activated biochar product.en_US
dc.description.woscitationindexScience Citation Index Expanded
dc.identifier.doi10.1007/s13399-024-05441-4
dc.identifier.endpage30691en_US
dc.identifier.issn2190-6815
dc.identifier.issn2190-6823
dc.identifier.issue23en_US
dc.identifier.scopus2-s2.0-85186175142
dc.identifier.scopusqualityQ2
dc.identifier.startpage30667en_US
dc.identifier.urihttps://doi.org/10.1007/s13399-024-05441-4
dc.identifier.urihttps://hdl.handle.net/20.500.12712/38818
dc.identifier.volume14en_US
dc.identifier.wosWOS:001172611600001
dc.identifier.wosqualityQ2
dc.language.isoenen_US
dc.publisherSpringer Heidelbergen_US
dc.relation.ispartofBiomass Conversion and Biorefineryen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectArtificial Neural Networken_US
dc.subjectBromocresol Greenen_US
dc.subjectPine Coneen_US
dc.subjectActivated Biocharen_US
dc.subjectPyrolysisen_US
dc.subjectAdsorptionen_US
dc.titleExperimental and Modeling Studies on the Removal of Bromocresol Green From Aqueous Solutions by Using Pine Cone-Derived Activated Biocharen_US
dc.typeArticleen_US
dspace.entity.typePublication

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