(525c) Adsorption of Acid Dye in Aqueous Solution by Mesoporous Carbons

Authors: 
Hu, Q. - Presenter, General Motors R&D Center
Pang, J. - Presenter, Tulane University
Lu, Y. - Presenter, Tulane University


Due to the fast development of textile industry, synthetic organic dyes are widely used for dyeing textile fibers and then lead to massive dye-containing wastewater. The dye contamination in wastewater poses serious health hazards and environmental pollution. So it is very important to find an efficient way to remove the dyes from industrial wastewater. Activated carbons are commonly used as adsorbents in both gas-phase and liquid-phase adsorption processes. However, the micropores of the activated carbons may limit their applications, especially in some applications involving large molecules or macromolecules which cannot easily penetrate into the micropores and adsorb onto them. To overcome this problem, many kinds of new type alternative adsorbents were employed. In this report, mesoporous carbons with tunable pore sizes were fabricated and used as adsorbent for large dye molecules, for example, Rose Bengal (acid red 94), from aqueous solution. As analytical comparisons, commercial mesopore-containing activated carbon was also used as adsorbent for the adsorption of the acid dye at various initial concentrations. Compared with activated carbon, mesoporous carbons showed much higher adsorption capacity due to their larger pore size. The experimental results showed that in the process of larger size molecular adsorption, both surface area and pore size have significant effect on the adsorption capacity of porous carbons. In order to further understand the adsorption process, the adsorption isotherm and kinetics were studied. The experimental results showed that the Langmuir isotherm equation appeared to fit the isotherm data better than Freundlich isotherm model. It was further found that the adsorption process can be well described with the pseudo-second-order model and less fitted by the pseudo-first-order model.