ACID MODIFICATION OF ACTIVATED CARBONS AND THE INFLUENCE OF SUBSTITUENT GROUP IN THE ADSORTION OF PHENOLIC COMPOUNDS

• Autores: Aylas Orejón, Edwin Javier, Picasso Escobar, Gino, Sun Kou, María del Rosario
• Formato: artículo
• Fecha de Publicación: 2016
• Institución: Sociedad Química del Perú
• Repositorio: Revista de la Sociedad Química del Perú
• Lenguaje: español
• OAI Identifier: oai:rsqp.revistas.sqperu.org.pe:article/94
• Enlace del recurso: http://revistas.sqperu.org.pe/index.php/revistasqperu/article/view/94
• Nivel de acceso: acceso abierto
• Materia: Activated carbon; oxidation; phenolic compounds; Carbón activado; oxidación; compuestos fenólicos

In this work, it has been studied the influence of oxygenated functional groups on adsorption property of an activated carbon (CA), which was prepared from aguaje seeds (Mauritia flexuosa L. F.) by a chemical activation with phosphoric acid. Later the activated carbon was oxidized with nitric acid. The adsorptive capacity of phenolic compounds such as phenol, 4-chlorophenol and 4-nitrophenol were compared using both of the adsorbents, the activated carbon (CA) and the oxidized activated carbon (ACA). The characterizations of both activated carbons were analyzed by nitrogen adsorption measurements, Boehm titration, scanning electron microscopy (SEM) and FTIR spectroscopy. The oxidized sample (ACA) showed an increase in the microporous area from 756 m2/g to 1272 m2/g, likewise ACA presented an increase in the concentration of oxygenated functional groups from 4,22 mmolH+.g-1 to 4,82 mmolH+.g-1. In contrast, the point of zero charge (pHPZC) decreased from 2,450 to 2,014. This suggested that there is a strong influence of the substituent group on the carbon adsorption. The increase in the oxygenated functional groups originated the decrease in the adsorptive capacity of activated carbons. The adsorption capacity of both carbons CA and ACA showed the following order: 4-nitrophenol > 4-chlorophenol > phenol. It was found that the pseudo second-order model was the best fit model for the experimental data.