Green leaching and predictive model for copper recovery from waste smelting slag with choline chloride-based deep eutectic solvent

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dc.contributor.authorTopçu, Mehmet Ali
dc.contributor.authorÇeltek, Seyit Alperen
dc.contributor.authorRüşen, Aydın
dc.date.accessioned2025-01-12T17:19:41Z
dc.date.available2025-01-12T17:19:41Z
dc.date.issued2024
dc.departmentKMÜ, Rektörlüğe Bağlı Bölümler, Bilimsel ve Teknolojik Araştırmalar Uygulama ve Araştırma Merkezi
dc.departmentKMÜ, Mühendislik Fakültesi, Enerji Sistemleri Mühendisliği Bölümü
dc.departmentKMÜ, Mühendislik Fakültesi, Metalurji ve Malzeme Mühendisliği Bölümü
dc.description.abstractThis research was performed to investigate the optimization of copper recovery from copper smelting slag (CSS) with a deep eutectic solvent as a green reagent. The effect of important parameters on the leaching efficiency of copper and zinc (as well as dissolution of iron), such as leaching time, leaching temperature, solid/liquid ratio, and particle size was studied. In order to model the copper recovery, an optimization method was used. According to the chemical analysis of CSS, the slag contains 0.9% copper, 3.3% zinc, and 36.7% iron. Also, it was found that the CSS is mainly composed of Fe2SiO4, Fe3O4 and SiO2. Copper-containing structures were determined as CuO and CuS. As a result of leaching experiments, 80% copper and 61% zinc recoveries were obtained at 48 h, 95 degrees C, 1/25 g center dot ml-1, and -33 mm. It is noted that the iron and silicon dissolution remained negligible under the selected conditions. According to the mathematical model, the highest copper leaching efficiency (up to 100%) could be under optimum working conditions as 48.5 degrees C leaching temperature, 40.1 h leaching duration, and 62.3 ml center dot g-1 solid/liquid ratio. Also, the proposed model revealed that a wide range of experimental levels can be used as leaching parameter to get desired metal leaching efficiency. (c) 2024 The Chemical Industry and Engineering Society of China, and Chemical Industry Press Co., Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
dc.description.sponsorshipKaramanog lu Mehmetbey University Scientific Research Projects (BAP) Coordinating Office [KMU-BAP-17-M-18]
dc.description.sponsorshipThe authors gratefully acknowledge the Karamanog lu Mehmetbey University Scientific Research Projects (BAP) Coordinating Office for support with grant number KMU-BAP-17-M-18. Authors are thankful to RAC-LAB (www.rac-lab.com) for providing the trialversion of their commercial software for this study.
dc.identifier.citationTopçu, M. A., Çeltek, S. A., & Rüşen, A. (2024). Green leaching and predictive model for copper recovery from waste smelting slag with choline chloride-based deep eutectic solvent. Chinese Journal of Chemical Engineering, 75, 14–24. https://doi.org/10.1016/j.cjche.2024.07.005
dc.identifier.doi10.1016/j.cjche.2024.07.005
dc.identifier.endpage24
dc.identifier.issn1004-9541
dc.identifier.issn2210-321X
dc.identifier.scopus2-s2.0-85206997128
dc.identifier.scopusqualityQ1
dc.identifier.startpage14
dc.identifier.urihttps://doi.org/10.1016/j.cjche.2024.07.005
dc.identifier.urihttps://hdl.handle.net/11492/10159
dc.identifier.volume75
dc.identifier.wosWOS:001344161100001
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Sceince
dc.indekslendigikaynakScopus
dc.institutionauthorTopçu, Mehmet Ali
dc.institutionauthorÇeltek, Seyit Alperen
dc.institutionauthorRüşen, Aydın
dc.institutionauthoridTopçu, Mehmet Ali/0000-0002-0007-5665
dc.institutionauthoridÇeltek, Seyit Alperen/0000-0002-7097-2521
dc.institutionauthoridRüşen, Aydın/0000-0001-5592-1411
dc.language.isoen
dc.publisherChemical Industry Press Co Ltd
dc.relation.ispartofChinese Journal of Chemical Engineering
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectDeep eutectic solvents
dc.subjectCopper smelting slag
dc.subjectMetal leaching
dc.subjectHydrometallurgy
dc.subjectGrey wolf optimizer
dc.titleGreen leaching and predictive model for copper recovery from waste smelting slag with choline chloride-based deep eutectic solvent
dc.typeArticle

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