Investigation of Methane Adsorption Isotherm on Activated Carbon at Low Temperatures Via Artificial Neural Network

In the present article adsorption isotherm of methane on activated carbon (AC) are investigate at low temperatures. To this aim, conventional adsorption isotherm models such as Langmuir,Freundlich, Keller and Jovanovich accompanied with a novel model to isotherm recovery based on multi- layer perceptron (MLP) artificial neural network are presented. The performances of proposed models are compared using methane adsorption experimental data points on AC at -33 °C. Although,the methane adsorption experimental data at low temperature is not enoughavailable for proper training of proposed neural network, however, the obtained results show suitable performances of MLP model like other conventional isotherm equations.