Rigorous prognostication and modeling of gas adsorption on activated carbon and Zeolite-5A

Gas adsorption on various adsorbents is of highly important issue for the separation of gas mixtures in many industrial processes. In this work, estimation of pure gases (CH₄, N₂, CO₂, H₂, C₂H₄) adsorption on activated carbon (AC) and CO₂, CH₄, N₂ on Zeolite-5A adsorbent were studied by developing four different computing techniques, namely MLP-ANN, ANFIS, LSSVM, and PSO-ANFIS for a broad range of experimental data found in the literature. Temperature, pressure, pore size (only for AC) and kinetic diameter of adsorbed gases are considered as the inputs and the gas adsorption as the output parameters of the developed models. We also used several statistical and graphical tools to assess the accuracy and applicability of the proposed models. The results of the study suggest the reliability and validity of all the models developed for estimating the equilibrium adsorption of gases on the adsorbents. Also, it is found that of all the models developed, the ANN model estimates experimental data of the gas adsorption on AC more accurately due to its values of R² and AARD%, 0.9865 and 0.8948, respectively. Besides, PSO-ANFIS is the best model to prognosticate gas adsorption on zeolite 5A with R² and AARD%, 0.9897 and 0.9551, respectively.