Investigating different kinetic models for CO2 adsorption on amine silica sorbent

Carbon capture and storage is an effective way of preventing the greenhouse gases emission and alleviate the effect of global warming. The capturing effect can be performed with the help of adsorption processes, which overcomes the limitations associated with absorption process. During this study, CO2 adsorption on amine functional silica sorbent experimental data was gathered. This data was collect at five different temperatures ranging from 313 to 393 K and at various CO2 concentrations. The main objective of this study is to investigate the performance of different kinetic model in validating the CO2 adsorption experimental data. Four different model namely; zero order model, pseudo first and pseudo second order model and Higuchi model were graphically and statistical compared in terms of predicting the CO2 adsorption data. The results of the study showed that the zero order model weak in validating CO2 adsorption experimental test. It was unable to model the CO2 adsorption experimental data between 0.02 and 0.34 mol fractions CO2. The decline in zero order model performance was because this model was based on constant adsorption of CO2 on the adsorbent. However, in reality it is mainly dependent on the availability of active sites on the adsorbent. Moreover, the performance of PSO model was the best. This model works effectively when $${k}_{2}>{k}_{1}$$ . This relationship was established at all temperature in the current study. Furthermore, the R2 for this model was also close to 1, which further validates its efficacy. In addition, the performance of Higuchi model was also efficient because this model was predominantly developed for the diffusion driven systems only. The adsorption of CO2 is based on external and internal diffusion process, where molecules of CO2 diffuse into the adsorbent. Hence, it can be concluded that except of zero order model all kinetic models demonstrates lower inconsistency in modeling the CO2 adsorption experimental data.