How is the langmuir model used in adsorption and the process of getting the each component of the formula?
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The Langmuir model is used in adsorption to characterize the adsorption process and predict adsorption equilibria. It provides a simple and elegant method for describing the adsorption behavior of components on a surface . The Langmuir model can be extended to incorporate complexity, such as heterogeneity and cooperative effects among ligands and receptors . Different variations of the Langmuir model have been developed, including the fuzzy Langmuir adsorption equations and the multi-molecular layer Langmuir isothermal adsorption model . These models are used to determine the adsorption relationship, predict chromatographic elution curves, and estimate the isosteric heat of adsorption . The parameters of the Langmuir model, such as the binding free energy and saturation capacity, can be obtained through experimental measurements, computer simulations, and theoretical calculations .
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| The paper discusses the use of the dual-process Langmuir (DPL) model to predict adsorption equilibria in binary gas mixtures. It describes two methodologies for obtaining the parameters of the DPL model for each component in the binary system. | |
24 Citations | The paper explains that the thermodynamic Langmuir isotherm model is used to estimate the isosteric heat of adsorption for pure component adsorption. The isosteric heat of adsorption is calculated using the Clausius-Clapeyron equation. |
01 Jun 2021 2 Citations | The paper describes the development of a Langmuir isothermal adsorption model for multi-molecular layer adsorption. It does not provide details on the process of getting each component of the formula. |
1 Citations | The paper describes the Langmuir binding model as a simple and elegant method for characterizing adsorption processes. It does not provide specific details on how to obtain each component of the Langmuir formula. |
| The paper combines the fuzzy Langmuir adsorption equations with the back propagation-artificial neural network (BP-ANN) to establish fuzzy Langmuir adsorption models. The major adsorption parameter Ci is obtained by solving the equilibrium dispersive chromatography model with the inverse method and genetic algorithm. |
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