Adsorptive removal of antipsychotic drug by carbon nanofibers in a batch and fixed bed column system

Abstract

Carbon nanofibers are promising green materials for sustainable technology within a wide range of applications including environment, energy, health and high-technology. Accordingly, drug adsorption is an important subject in connection with its environmental and pharmaceutical applications. This study aims to investigate the adsorption performance of carbon nanofibers in batch and fixed bed column processes. Carbon nanofibers were used as adsorbent to remove triflupromazine hdyrochloride from aqueous solutions. Adsorption kinetics were studied using Lagergren first order and Pseudo second order models. Intraparticle diffusion graph was plotted using kinetic data and showed that intraparticle diffusion is the single step controlling the adsorption rate. Experimental equilibrium data was modeled by using Langmuir and Freundlich equations and has a better fit to the Langmuir model. Triflupromazine adsorption on carbon nanofibers was found to be H-type according to Giles classification. The effect of temperature and the effect of pH on adsorption were studied to determine optimum adsorption conditions. Adsorption capacity of carbon nanofibers was decreased with increasing temperature due to the exothermic and physical nature of the process. Thermodynamic parameters confirmed the exothermic nature of the adsorption. Results showed the effective adsorption of drug molecules by carbon nanofibers. Maximum adsorption capacity was calculated as 165.41 mg/g at pH 9 using Langmuir equation. Modeling of the fixed bed column data was done by using Thomas model and Yoon–Nelson model. Results showed the important effect of the operating conditions on the removal performance of carbon nanofibers. Removal capacity was increased with an increase in the flow rate and the increase in the fixed bed length.

Graphical Abstract

Keywords:

• Carbon nanofibers
• adsorption
• triflupromazine
• nanomaterials
• water treatment

Disclosure statement

Authors confirm that there is no relevant financial or non-financial competing interest to report.

Additional information

Funding

The authors thank the financial support of Marmara University Research Fund [Project SAG-C-YLP-241018-0585].