Studi Kinetika dan Penentuan Dosis Optimum Koagulan FeCl3 dalam Menurunkan Konsentrasi Cu2+ pada Larutan

MS Fadila, MA Afandy, S Suhirman… - … Journal of Research …, 2023 - reactor.poltekatipdg.ac.id
REACTOR: Journal of Research on Chemistry and Engineering, 2023reactor.poltekatipdg.ac.id
This study aims to determine the efficiency and adsorption capacity of various
concentrations of FeCl 3 coagulants (100-300 mg/L) to reduce Cu 2+ concentrations in
wastewater as well as the kinetic parameters that affect the adsorption mechanism in the
coagulation process when coagulant particles added to wastewater will stick to the surface
of colloidal particles, which will then change the charge. Several adsorption kinetics models
employed in this study include Pseudo-first order, Pseudo-second order, Elovich, and Intra …
Abstract
This study aims to determine the efficiency and adsorption capacity of various concentrations of FeCl 3 coagulants (100-300 mg/L) to reduce Cu 2+ concentrations in wastewater as well as the kinetic parameters that affect the adsorption mechanism in the coagulation process when coagulant particles added to wastewater will stick to the surface of colloidal particles, which will then change the charge. Several adsorption kinetics models employed in this study include Pseudo-first order, Pseudo-second order, Elovich, and Intra-particle diffusion. The applicability of the models produced in this work was evaluated by optimizing the non-linear equations, which provide values that are more precise and in agreement with real situations when compared to the linear kinetic models. These characteristics are measured based on the value of the coefficient of correlation (R 2), Sum Square Error (SSE), and Chi-Square (x 2). The results showed that the highest efficiency value of the FeCl 3 coagulant was 98.705%, with the value of the adsorption capacity increasing along with the concentration of the FeCl 3 coagulant. The kinetic model created in this work has a very excellent fit in terms of experimental data values and prediction data.
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