preparation of activated carbon from entada africana guill. & perr for co2 capture: artificial neural network and isotherm modeling

Recent concerns about the greenhouse effect and climate change have been prominent worldwide. in this study, a single-step koh activation was used to prepare entada porous carbon adsorbent. the produced activated carbon was used for co2 adsorption. isotherm models including freundlich, langmuir, dubinin-rudeshkovich, temkin, and hill were used for adsorption isotherm data. in addition, artificial neural networks were used for the prediction of co2 adsorption capacity. trial and error helped us to find the best design, selecting the architecture with the lowest error (mse) and the best regression coefficient. the best mse validation performance of the neural network was 0.00094486. the neural network model can effectively predict co2 adsorption on activated carbon from entada africana guill. & perr. adsorption capacities of activated carbon from entada africana guill. & perr at 273 k and 289 k and 1 bar were 4.34 mmol/g and 6.78 mmol/g, respectively. the brunauer–emmett–teller specific area (sbet) and the micropores volume equated to 2556 m^2/g and 0.78 cm^3/g, respectively. thus, entada african guill & perr activated carbon shows promise in capturing co2.