Abstract
A cryo-sorption device was built based on a commercial gas sorption analyzer with its sample chamber connected to the 2nd stage of the Gifford-McMahon (GM) cryocooler (by SUMITOMO Corporation), which could provide the operation temperature ranging from 4.5 K to 300 K; The nitrogen adsorption isotherms ranging from 95 to 160 K were obtained by volumetric method on the PICATIF activated carbon. Isosteric heat of adsorption was calculated using the Clausius–Clapeyron equation and was around 8 kJ/mol. Conventional isotherm models and the artificial neural network (ANN) were applied to analyze the adsorption data, the Dual-site Langmuir and the Toth equation turned out to be the most suitable empirical isotherm model; Adsorption equilibrium data at some temperature was used to train the neural network and the rest was used to validate and predict, it turned out that the accuracy of the prediction by the ANN increased with increasing hidden-layer, and it was within ±5% for the three-hidden-layer ANN, and it showed better performance than the conventional isotherm model; Considering large time consumption and complexity of the adsorption experiment, the ANN method can be applied to get more adsorption data based on the already known experimental data.
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