Experiment and molecular simulation for liquid phase adsorption of triethylenetetramine on activated carbon: equilibrium, kinetics, thermodynamics and molecular behavior
Source abstract
Abstract
Modification of the surface of raw activated carbon using chemical solvents can significantly improve the adsorption performance of activated carbon. Triethylenetetramine is one of the most important chemical solvents used to modify raw activated carbon for formaldehyde removal indoor. We conducted the liquid impregnation experiments at different initial concentrations, temperatures, adsorbent dosage and time ranges to fully investigate the adsorption of triethylenetetramine on the surface of raw activated carbon for modification. We found that the Langmuir isotherm model and pseudo-first-order kinetic model fit quite well with the experimental data and the R2 are 0.9883 and 0.9954, respectively. The theoretical maximum adsorption capacity is 166.67 mg/g. The change in Gibbs free energy (ΔG0), enthalpy change (ΔH0) and entropy change (ΔS0) were also calculated to study the direction and driving force of the liquid adsorption process. In order to understand the adsorption process at the molecular level, a new activated carbon model based on the actual physical and chemical properties of activated carbon was carefully established in the Materials Studio to simulate the liquid-phase adsorption. The pore structure, elemental composition, functional group content, density, pore volume, and porosity of the activated carbon model converge close to the actual activated carbon and the adsorption isotherms obtained from the simulation agree well with the experimental results. The results show that the adsorption of triethylenetetramine on activated carbon is a spontaneous, endothermic and monolayer physical adsorption process.
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Research context
OpenAlex topics: Adsorption and biosorption for pollutant removal · Covalent Organic Framework Applications · Carbon Dioxide Capture Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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