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• W4283123638 startingPage "119639" @default.
• W4283123638 abstract "In this study, six statistical physics (sta-phy) models were used to further describe and enlighten the mechanisms behind the adsorption of a low interaction model molecule through the interpretations of the real and ideal gas. Density functional theory (DFT) was employed for the simulation of electronic structure and reactivity parameters (Eg, η, μ, and ω). Experimental assays were carried out with a representative activated carbon sample and 2,4-dichlorophenoxyacetic acid (2,4-D) pesticide as a base for the modeling and simulation. According to the classical interpretations, the adsorption was a monolayer exothermic process dependent on temperature. From the sta-phy perspective, the Hill model for monolayer adsorption with two energies best described the process. According to the estimations, the number of molecules adsorbed increases with increasing temperature, yet the number of primary adsorption sites (n) decreases with increasing temperature. The concentrations at a half-saturation (Ci), in turn, increase with the increase in temperature. At last, by combining the sta-phy estimations with the DFT interpretations, it was possible to infer that, in addition to the thermal effects, electrostatic repulsion is a possible contribution that increases as the primary receptor sites are occupied. Therefore, the combination of simulations can provide answers to unclear mechanistic steps and help predict the contribution of the adsorbate to the estimated sta-phy parameters, with a very high degree of precision as statistically validated." @default.
• W4283123638 created "2022-06-20" @default.
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• W4283123638 date "2022-09-01" @default.
• W4283123638 modified "2023-10-10" @default.
• W4283123638 title "An advanced combination of density functional theory simulations and statistical physics modeling in the unveiling and prediction of adsorption mechanisms of 2,4-D pesticide to activated carbon" @default.
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• W4283123638 doi "https://doi.org/10.1016/j.molliq.2022.119639" @default.
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