Sugar beet lignocellulose waste as biosorbents: surface functionality, equilibrium studies and artificial neural network modeling.

Autor: Kukić, D., Šćiban, M., Brdar, M., Vasić, V., Takači, A., Antov, M., Prodanović, J.
Předmět:
Zdroj: International Journal of Environmental Science & Technology (IJEST); Mar2023, Vol. 20 Issue 3, p2503-2516, 14p
Abstrakt: To meet sustainable development criteria, this paper deals with the possible utilization of solid waste materials generated from single and multiple successive processing of sugar beet (i.e., from the production of sugar, bioethanol and pectin) in wastewater treatment. Waste lignocellulose materials after extraction of sucrose, successive extractions of sucrose and pectin, as well as successive extractions of sucrose and pectin followed by enzymatic hydrolysis of cellulose were investigated as biosorbents for heavy metal removal. Surface characterization was performed by Fourier transform infrared spectroscopy and Boehm's titration which showed heterogeneity regarding functional groups and the acidic surface of adsorbents. Also, a possible involvement of certain functional groups (hydroxyl, phenolic, carbonyl, amino) in the adsorption process was discussed. Equilibrium studies showed that these materials had greater adsorption capacity for Cu2+ compared to capacity for Cr6+ ions and that the adsorption process by various adsorbents could not be described by the same isotherm model. Adsorption mechanism study implied that ion exchange was not the only mechanism of Cu2+ binding onto investigated biosorbents. Also, the Cu2+ removal performance of waste materials was successfully predicted by applying a three-layer neural network with 6 neurons in the hidden layer. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index