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In relation to this article, we declare that there is no conflict of interest.
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Received February 12, 2011
Accepted August 16, 2011
articles This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Experimental study and artificial neural network simulation of methane adsorption on activated carbon

1Department of Chemical Engineering, Shahid Bahonar University of Kerman, Iran 2Mining Industries Research Center, Shahid Bahonar University of Kerman, Iran
h-hashemipour@uk.ac.ir
Korean Journal of Chemical Engineering, May 2012, 29(5), 601-605(5), 10.1007/s11814-011-0215-1
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Abstract

The adsorption of methane on two activated carbons with different physical properties was measured. Adsorption isotherms were obtained by static volumetric method at different temperatures and pressures. The experimental results sow the best gas storage capacity was 113.5 V/V at temperature 280 K and pressure 8.5MPa on an activated carbon with surface area 1,060 m2/gr. An artificial neural network (ANN) based on genetic algorithm (GA) was used to predict amount of adsorption. The experimental data including input pressure, temperature and surface area of adsorbents as input parameters were used to create a GA-ANN simulation. The simulation results were compared with the experimental data and a good agreement was observed. The simulation was applied to calculate isosteric heat of adsorption by using the Clausius-Clapeyron equation. Comparison of the calculated adsorption heat showed different_x000D_ surface heterogeneity of the adsorbents.

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