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, q_e vs. concentration, c_e. 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 q_e. 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 (AIC_corrected) was employed to known the best model. We observed lowest AIC_corrected(15.859) value for Langmuir-Freundlich isotherm and the highest AIC_corrected(59.283) value for Marczewski-jaroniec isotherm. AIC_corrected reveals that Langmuir-Freundlich isotherm was efficient in correlating the isotherm data. Further, Pair-t test was performed between Baudu isotherm and other model.

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。