Adsorption of ciprofloxacin from aqueous solution and fresh synthetic urine by graphene oxide: conventional and statistical physics modeling approaches

This work uses conventional and statistical physics modeling approaches to address ciprofloxacin (CIP) adsorption by graphene oxide (GO) from aqueous solution and fresh synthetic urine. Instrumental techniques such as FTIR, XRD, SEM, TGA, BET, and EDS were employed to characterize the adsorbent material. The adsorption experiments were performed in a typical batch using different initial concentrations of CIP, adsorbent dosage, pH, and temperatures. Besides, the statistical physics approach was employed to investigate the CIP adsorption onto GO. Five models based on mono, double, and multilayers were used to describe the equilibrium isotherms. Steric and energetic parameters such as the number of adsorbed molecules per site, receptor site density, and half-saturation were considered. The kinetic data were adjusted using three conventional models (pseudo 1st order, pseudo 2nd order, and general order). The pH effect and influence of adsorbent dosage on adsorption performance were also investigated and discussed. In addition, adsorption mechanisms hypotheses were proposed based on experimental data and adsorption modeling using a statistical physics approach. Furthermore, the current work reports the removal of CIP at concentrations commonly found in urine considering factors such as fraction excreted in unmetabolized form, daily defined dose, and average daily urine volume excreted. The adsorption capacity values in aqueous medium and fresh synthetic urine were were 354.24 and 291.39 mg g−1, respectively.

• Autores: da Silva Bruckmann, Franciele; Piazzi Fuhr, Ana Carolina Ferreira; Zibetti, Letícia; Bender, Caroline Raquel; Oliveira Silva, Luis Felipe; DA BOIT MARTINELLO, KATIA; Ahmad, Naushad; Mohandoss, Sonaimuthu; Dotto, Guilherme Luiz
• Tipo de recurso: Article of investigation
• Fecha de publicación: 2024
• Institución: Corporación Universidad de la Costa
• Repositorio: REDICUC - Repositorio CUC
• Idioma: eng
• OAI Identifier: oai:repositorio.cuc.edu.co:11323/13303
• Acceso en línea: https://hdl.handle.net/11323/13303; https://repositorio.cuc.edu.co/
• Palabra clave: Antibiotic; Carbon nanomaterials; Fresh synthetic urine; Statistical physics modeling
• Rights: embargoedAccess
• License: Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)