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Information 2015, 6(1), 14-22; doi:10.3390/info6010014

Modeling of Experimental Adsorption Isotherm Data

1
College of Computer and Information, Hohai University, Nanjing 210098, China
2
School of Mathematical and Information Engineering, Taizhou University, Linhai 317000, China
Academic Editor: Min Yao
Received: 27 November 2014 / Revised: 16 December 2014 / Accepted: 19 January 2015 / Published: 22 January 2015
(This article belongs to the Special Issue Intelligent Data Analysis)
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Abstract

Adsorption is considered to be one of the most effective technologies widely used in global environmental protection areas. Modeling of experimental adsorption isotherm data is an essential way for predicting the mechanisms of adsorption, which will lead to an improvement in the area of adsorption science. In this paper, we employed three isotherm models, namely: Langmuir, Freundlich, and Dubinin-Radushkevich to correlate four sets of experimental adsorption isotherm data, which were obtained by batch tests in lab. The linearized and non-linearized isotherm models were compared and discussed. In order to determine the best fit isotherm model, the correlation coefficient (r2) and standard errors (S.E.) for each parameter were used to evaluate the data. The modeling results showed that non-linear Langmuir model could fit the data better than others, with relatively higher r2 values and smaller S.E. The linear Langmuir model had the highest value of r2, however, the maximum adsorption capacities estimated from linear Langmuir model were deviated from the experimental data. View Full-Text
Keywords: modeling; isotherm data; linear; non-linear; standard errors (S.E.) modeling; isotherm data; linear; non-linear; standard errors (S.E.)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Chen, X. Modeling of Experimental Adsorption Isotherm Data. Information 2015, 6, 14-22.

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