Journal
ENVIRONMENTAL RESEARCH
Volume 233, Issue -, Pages -Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.envres.2023.116503
Keywords
Antibiotics; Multicomponent adsorption; Carbon nanotubes; Green functionalization; Artificial neural networks
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This paper investigated the adsorption of CIP and OFL in single and multicomponent systems using modified carbon nanotubes as adsorbents. Characterization analyses and kinetic studies revealed the involvement of n-n and π-π interactions and the equilibrium time and adsorptive capacity of the drugs. The selectivity analysis showed identical selectivities in equimolar fractions, and mathematical modeling and artificial neural networks improved the prediction of system behavior.
This paper investigated the uptake of CIP and OFL in single and multicomponent adsorptive systems using modified carbon nanotubes (CNTs) as adsorbent material. The characterization analyses of the pre-and post-process material by XPS, TG/DTG, FT-IR, SEM/EDS, and XRD helped in the elucidation of the mechanisms, indicating greater involvement of n-n and & pi; -& pi; interactions. In the kinetic studies, the simple systems with CIP and OFL were similar, both showed equilibrium time around 20/30 min and increased adsorptive capacity with increasing initial drug concentration. In the multicomponent system, different fractions of CIP and OFL were tested and the time to reach equilibrium also varied between 20 and 30 min. In general, the adsorption capacity of CIP is slightly lower than that of OFL under the conditions tested. The selectivity analysis of the system showed that the selectivity's of the two drugs are identical in equimolar fractions. The mathematical modeling of the kinetic data indicated that in monocomponent systems, the model of pseudo-second order (PSO) adequately described both CIP and OFL kinetics. Furthermore, with the implementation of Artificial Neural Networks (ANN), it was possible to obtain a more assertive prediction of the behavior of single and binary systems.
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