Journal
PROCESSES
Volume 11, Issue 8, Pages -Publisher
MDPI
DOI: 10.3390/pr11082295
Keywords
magnetic biochar; cow manure; cadmium removal; response surface methodology; artificial neural network
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Designing an efficient and recyclable adsorbent for cadmium pollution control is an urgent necessity. In this study, magnetic cow manure biochar was synthesized using cow manure as the raw material. The optimal preparation conditions and reaction conditions were determined through a response surface methodology model. The adsorption mechanism involved ion exchange, electrostatic attraction, pore-filling, co-precipitation, and the formation of complexations.
Designing an efficient and recyclable adsorbent for cadmium pollution control is an urgent necessity. In this paper, cow manure, an abundant agricultural/animal husbandry byproduct, was employed as the raw material for the synthesis of magnetic cow manure biochar. The optimal preparation conditions were found using the response surface methodology model: 160 degrees C for the hydrothermal temperature, 600 degrees C for the pyrolysis temperature, and Fe-loading with 10 wt%. The optimal reaction conditions were also identified via the response surface methodology model: a dosage of 1 g center dot L-1, a pH of 7, and an initial concentration of 100 mg center dot L-1. The pseudo-second-order model and the Langmuir model were used to fit the Cd(II) adsorption, and the adsorption capacity was 612.43 mg center dot g(-1). The adsorption was dominated by chemisorption with the mechanisms of ion-exchange, electrostatic attraction, pore-filling, co-precipitation, and the formation of complexations. Compared to the response surface methodology model, the back-propagation artificial neural network model fit the Cd(II) adsorption better as the error values were less. All these results demonstrate the potential application of CM for Cd(II) removal and its optimization through machine-learning processes.
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