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Statistical analysis of adsorption isotherm models and its appropriate selection
Chemosphere ( IF 8.1 ) Pub Date : 2021-03-04 , DOI: 10.1016/j.chemosphere.2021.130176
Ganesh Kumar Rajahmundry , Chandrasekhar Garlapati , Ponnusamy Senthil Kumar , Ranta Surya Alwi , Dai-Viet N. Vo

In adsorption research, there was a good amount of adsorption data on various absorbent-adsorbate systems and many isotherm models were studied but there was no study on applicability of models to a group of adsorbent-adsorbate systems. In order to establish this, adsorption data obtained from literature for activated carbon with different solutes/sorbate(s) were considered and modelled with various adsorption models. The molecular mass of the solutes varies from 78.118(Benzene) to 932(Direct blue 2B dye) g.mol−1 and adsorbent surface area varies from 516 to 1100 m2 g−1. In this work, twelve commonly known isotherms models were employed to correlate the adsorption data. For modelling polymath® software has been used. The input data for the polymath® software were amount of adsorbate per unit amount of adsorbent, qe vs. concentration, ce. Nonlinear optimization of isotherm data gives model parameters. The correlating ability of the various models was compared in terms of arithmetic average relative deviation (AARD) calculated based on qe. The lowest overall AARD% values were observed for Baudu Isotherm and Langmuir-Freundlich and the corresponding AARD% values were 2.6 and 2.8 respectively. The highest overall AARD% value was observed for Marczewski-jaroniec isotherm and the corresponding AARD% is 23.5. Corrected Akaike’s information criterion (AICcorrected) was employed to known the best model. We observed lowest AICcorrected(15.859) value for Langmuir-Freundlich isotherm and the highest AICcorrected(59.283) value for Marczewski-jaroniec isotherm. AICcorrected reveals that Langmuir-Freundlich isotherm was efficient in correlating the isotherm data. Further, Pair-t test was performed between Baudu isotherm and other model.



中文翻译:

吸附等温线模型的统计分析和适当的选择

在吸附研究中,在各种吸收剂-吸附剂系统上都有大量的吸附数据,并且研究了许多等温模型,但没有研究模型对一组吸附剂-吸附剂系统的适用性。为了确定这一点,考虑了从文献中获得的具有不同溶质/吸附物的活性炭吸附数据,并使用各种吸附模型对其进行了建模。溶质的分子量从78.118(苯)到932(直接蓝2B染料)g.mol -1不等,吸附剂表面积从516到1100 m 2  g -1不等。在这项工作中,采用了十二种众所周知的等温线模型来关联吸附数据。为了建模,使用了polymath®软件。该软件的输入数据是每单位吸附剂的吸附量,q e与浓度,ce。等温线数据的非线性优化给出了模型参数。根据基于q e的算术平均相对偏差(AARD),比较了各种模型的关联能力。Baudu等温线和Langmuir-Freundlich的总AARD%值最低,相应的AARD%值分别为2.6和2.8。对于Marczewski-jaroniec等温线,观察到最高的总AARD%值,相应的AARD%为23.5 校正后的Akaike信息准则(经AIC校正)可用于了解最佳模型。我们观察到最低AIC修正为符合Langmuir-Freundlich等温(15.859)值和最高AIC修正为Marczewski-jaroniec等温线(59.283)值。校正后的AIC显示Langmuir-Freundlich等温线在关联等温线数据方面非常有效。此外,在Baudu等温线与其他模型之间执行Pair-t测试。

更新日期:2021-03-10
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