Mathematical Modelling of As(V) Adsorption by Humic Acid-Coated Magnetite Nanoparticles

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Proceedings of the 8th International Conference on Computational Science and Technology

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 835))

Abstract

In recent years, arsenic contamination in our surface water sources has become a major problem. Therefore, water treatment is the key to alleviate this problem. Adsorption as one of the polluted water remediation methods has proven to be efficient and rapid. Its underlying mechanisms can be ascertained through the study of isotherm, kinetics and thermodynamics parameters of the adsorption process itself. Therefore, in the present paper, existing data of arsenate (As(V)) adsorption mechanisms by multiple samples of adsorbents will be interpreted by modelling the data. The data were obtained from experiments conducted previously involving humic acid-coated magnetite nanoparticles (NP). The effect of variables such as the synthesis temperatures and humic acid concentrations on the adsorption was thoroughly investigated via the experiments. In this paper, both linear and non-linear models were applied, and the results were compared. The non-linear model fitting was done with Microsoft Excel 2016 solver. The equilibrium adsorption data was fitted to the Freundlich, Langmuir and Temkin isotherms as well as the kinetic pseudo-first order (PFO) and pseudo-second order (PSO) models. Linear coefficient of determination was used for linear regression while non-linear regressions was done through the non-linear error function chi-square (χ2). The best model that fits the experimental data were decided accordingly for the different adsorbent samples.

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Mubarak bin Hamzah, A.A., Devaraj, N.K. (2022). Mathematical Modelling of As(V) Adsorption by Humic Acid-Coated Magnetite Nanoparticles. In: Alfred, R., Lim, Y. (eds) Proceedings of the 8th International Conference on Computational Science and Technology. Lecture Notes in Electrical Engineering, vol 835. Springer, Singapore. https://doi.org/10.1007/978-981-16-8515-6_29

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