Lake sediment based catalyst for hydrogen generation via methanolysis of sodium borohydride: an optimization study with artificial neural network modelling
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Tarih
2021
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In 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] .
Açıklama
Anahtar Kelimeler
Lake sediment, Sodium borohydride methanolysis, Hydrogen generation, Taguchi, Artificial neural network
Kaynak
Reaction Kinetics Mechanisms and Catalysis
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
134
Sayı
1
