Theoretical calculating the thermodynamic properties of solid sorbents for CO_2 capture applications

摘要

Since current technologies for capturing CO_2to fight global climate change are still tooenergy intensive, there is a critical need for development of new materials that cancapture CO_2 reversibly with acceptable energy costs. Accordingly, solid sorbents havebeen proposed to be used for CO_2 capture applications through a reversible chemicaltransformation. By combining thermodynamic database mining with first principlesdensity functional theory and phonon lattice dynamics calculations, a theoreticalscreening methodology to identify the most promising CO_2 sorbent candidates from thevast array of possible solid materials has been proposed and validated. The calculatedthermodynamic properties of different classes of solid materials versus temperature andpressure changes were further used to evaluate the equilibrium properties for the CO_2adsorption/desorption cycles. According to the requirements imposed by the pre- andpost- combustion technologies and based on our calculated thermodynamic propertiesfor the CO_2 capture reactions by the solids of interest, we were able to screen onlythose solid materials for which lower capture energy costs are expected at the desiredpressure and temperature conditions. Only those selected CO_2 sorbent candidates werefurther considered for experimental validations. The ab initio thermodynamic techniquehas the advantage of identifying thermodynamic properties of CO_2 capture reactionswithout any experimental input beyond crystallographic structural information of thesolid phases involved. Such methodology not only can be used to search for goodcandidates from existing database of solid materials, but also can provide someguidelines for synthesis new materials. In this presentation, we first introduce ourscreening methodology and the results on a testing set of solids with knownthermodynamic properties to validate our methodology. Then, by applying ourcomputational method to several different kinds of solid systems, we demonstrate thatour methodology can predict the useful information to help developing CO_2 captureTechnologies.