Predicting Mixed-Gas Adsorption Equilibria on Activated Carbon for Precombustion CO2 Capture

We present experimentally measured adsorption isotherms of CO2, H-2, and N-2 on a phenol-formaldehyde resin-based activated carbon, which had been previously synthesized for the separation of CO2 in a precombustion capture process. The single component adsorption isotherms were measured in a magnetic suspension balance at three different temperatures (298, 318, and 338 K) and over a large range of pressures (from 0 to 3000-4000 kPa). These values cover the temperature and pressure conditions likely to be found in a precombustion capture scenario, where CO2 needs to be separated from a CO2/H-2/N-2 gas stream at high pressure (similar to 1000-1500 kPa) and with a high CO2 concentration (similar to 20-40 vol %). Data on the pure component isotherms were correlated using the Langmuir, Sips, and dual-site Langmuir (DSL) models, i.e., a two-, three-, and four-parameter model, respectively. By using the pure component isotherm fitting parameters, adsorption equilibrium was then predicted for multicomponent gas mixtures by the extended models. The DSL model was formulated considering the energetic site-matching concept, recently addressed in the literature. Experimental gas-mixture adsorption equilibrium data were calculated from breakthrough experiments conducted in a lab-scale fixed-bed reactor and compared with the predictions from the models. Breakthrough experiments were carried out at a temperature of 318 K and five different pressures (300, 500, 1000, 1500, and 2000 kPa) where two different CO2/H-2/N-2 gas mixtures were used as the feed gas in the adsorption step. The DSL model was found to be the one that most accurately predicted the CO2 adsorption equilibrium in the multicomponent mixture. The results presented in this work highlight the importance of performing experimental measurements of mixture adsorption equilibria, as they are of utmost importance to discriminate between models and to correctly select the one that most closely reflects the actual process.