CO2 adsorption using TiO2 composite polymeric membranes: A kinetic study.
J Environ Sci (China)
; 35: 163-171, 2015 Sep 01.
Article
en En
| MEDLINE
| ID: mdl-26354705
ABSTRACT
CO2 is the main greenhouse gas which causes global climatic changes on larger scale. Many techniques have been utilised to capture CO2. Membrane gas separation is a fast growing CO2 capture technique, particularly gas separation by composite membranes. The separation of CO2 by a membrane is not just a process to physically sieve out of CO2 through the controlled membrane pore size. It mainly depends upon diffusion and solubility of gases, particularly for composite dense membranes. The blended components in composite membranes have a high capability to adsorb CO2. The adsorption kinetics of the gases may directly affect diffusion and solubility. In this study, we have investigated the adsorption behaviour of CO2 in pure and composite membranes to explore the complete understanding of diffusion and solubility of CO2 through membranes. Pure cellulose acetate (CA) and cellulose acetate-titania nanoparticle (CA-TiO2) composite membranes were fabricated and characterised using SEM and FTIR analysis. The results indicated that the blended CA-TiO2 membrane adsorbed more quantity of CO2 gas as compared to pure CA membrane. The high CO2 adsorption capacity may enhance the diffusion and solubility of CO2 in the CA-TiO2 composite membrane, which results in a better CO2 separation. The experimental data was modelled by Pseudo first-order, pseudo second order and intra particle diffusion models. According to correlation factor R(2), the Pseudo second order model was fitted well with experimental data. The intra particle diffusion model revealed that adsorption in dense membranes was not solely consisting of intra particle diffusion.
Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Titanio
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Dióxido de Carbono
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Contaminantes Atmosféricos
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Contaminación del Aire
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Restauración y Remediación Ambiental
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Nanopartículas del Metal
Tipo de estudio:
Prognostic_studies
Idioma:
En
Año:
2015
Tipo del documento:
Article