Lake sediment based catalyst for hydrogen generation via methanolysis of sodium borohydride: an optimization study with artificial neural network modelling

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dc.contributor.authorBekirogullari, Mesut
dc.contributor.authorAbut, Serdar
dc.contributor.authorDuman, Fatih
dc.contributor.authorHansu, Tulin Avci
dc.date.accessioned2024-12-24T19:24:45Z
dc.date.available2024-12-24T19:24:45Z
dc.date.issued2021
dc.departmentSiirt Üniversitesi
dc.description.abstractIn the current study, lake sediment, a heterogeneous and complex organic matter, utilized as a catalyst upon acid treatment for efficient hydrogen generation from sodium borohydride. In order to synthesise the catalyst that bears the best catalytic activity, ANOVA, cubic stepwise linear regression and artificial neural network optimization techniques were applied to determine the optimal level of treatment parameters. The results suggest that only Taguchi orthogonal arrays method was able to accurately reflect the overall surface of objective variable. Among the 16 catalyst samples Exp(15) showed the superior catalytic activity followed by Exp(13), Exp(12), Exp(14) and Exp(7). The minimum reaction completion time for Exp(15) corresponding to maximum hydrogen production rate of 3247.15 mL/min/gcat was 2.25 min. A detailed characterization of the final product was carried out by using a Fourier transform infrared spectra (FTIR-Perkin Elmer), an X-ray diffractometer (Bruker D8 Advance XRD), a scanning electron microscopy and energy dispersive X-ray spectroscopy. [GRAPHICS] .
dc.identifier.doi10.1007/s11144-021-02057-x
dc.identifier.endpage74
dc.identifier.issn1878-5190
dc.identifier.issn1878-5204
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85113340931
dc.identifier.scopusqualityQ3
dc.identifier.startpage57
dc.identifier.urihttps://doi.org/10.1007/s11144-021-02057-x
dc.identifier.urihttps://hdl.handle.net/20.500.12604/6126
dc.identifier.volume134
dc.identifier.wosWOS:000687915600001
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofReaction Kinetics Mechanisms and Catalysis
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241222
dc.subjectLake sediment
dc.subjectSodium borohydride methanolysis
dc.subjectHydrogen generation
dc.subjectTaguchi
dc.subjectArtificial neural network
dc.titleLake sediment based catalyst for hydrogen generation via methanolysis of sodium borohydride: an optimization study with artificial neural network modelling
dc.typeArticle

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