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The presence of emerging contaminants in wastewater poses a global environmental challenge, requiring the development of innovative materials or methods for their treatment. This study focused on the production of green functionalized carbon nanotubes (CNTs) and using them in the adsorption of the pharmaceuticals Losartan (LOS) and Diclofenac (DIC). The efficiency of the methodology was verified by characterization techniques. Elemental composition analysis indicated a significant increase in the iron content after the green functionalization, proving the effectiveness of the method. Thermogravimetric analysis showed similar thermal degradation profiles for pristine CNTs and functionalized CNTs, indicating better post-functionalization thermal stability. BET analysis revealed mesoporous characteristics of CNTs, with increased surface area and pore volumes after functionalization. X-Ray diffraction confirmed the preservation of the lattice structure of the CNTs post-functionalization and post-adsorption, with changes in peak broadening suggesting surface modifications. LOS and DIC adsorption were evaluated via kinetic studies at four different concentrations (0.1-0.4 mmol/L) that were best represented by the pseudo-second order model, suggesting chemisorption mechanisms, with faster and higher uptakes for DIC (0.084-0.261 mmol/g; t eq  = 5 min) when compared to LOS (0.058-0.235 mmol/g; t eq  = 20 min). The curves were also studied via artificial neural networks (ANN) and revealed that the best ANN architecture for representing the experimental data is a network with [3 5 5 2] neurons trained using the Bayesian-Regularization algorithm and the Log-sigmoid (hidden layers) and Linear (output layer) transfer functions. The desorption study showed that CaCl 2 had better performance in CNT regeneration, reaching its removal capacity above 50% up to 3 cycles, for both pharmaceuticals. These findings reveal the potential of the developed material as a promising adsorbent for targeted removal of pollutants, contributing to advances in the remediation of emerging contaminants and the application of artificial intelligence in adsorption research., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

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 π -π 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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)