4.4 Article

Activated carbon characterization with heterogenous kernel using CO2 at high pressure

Publisher

SPRINGER
DOI: 10.1007/s10450-023-00375-1

Keywords

Activated carbon; CO2 adsorption; Monte Carlo simulation; Characterization

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We compared the pore size distribution (PSD) obtained from CO2 adsorption isotherms on homogeneous and heterogeneous slit activated carbon models. The reactive molecular dynamics model (rMD) showed better fitting to the experimental isotherm and predicted a higher volume of ultramicropores in all activated carbons. Both PSD models accurately predicted light hydrocarbon isotherms, with rMD being more accurate. The study also revealed the limitations of implicit heterogeneous DFT-based models due to differences between AA and UA CO2 models in rMD heterogeneous ultramicropores.
We investigated the pore size distribution obtained from adsorption isotherms kernels of CO2 at 298 K on homogeneous and heterogeneous slit activated carbon models. The heterogenous activated carbon surface was created using the reactive molecular dynamics model (rMD) which explicitly incorporates heterogeneities resulting from the oxidative etching of graphene walls. PSDs obtained with homogeneous and rMD models have been compared for different activated carbons. The rMD model resulted in an improved fit to the experimental isotherm, compared to homogenous model. The pore size distribution obtained from CO2 isotherm with rMD model systematically predicts a greater volume of ultramicropores in all activated carbons studied. Both PSDs are able to predict C1 to C4 light hydrocarbon isotherms with the rMD kernel being more accurate than the homogeneous one. The rMD model considerably reduces the discrepancies between atom-atom (AA) and unit atom (UA) molecular models of CO2. The study brings evidences that CO2 at high pressures can be used to simultaneously measure the interval between ultramicropores and mesopores. Moreover, the differences between AA and UA CO2 model in rMD heterogenous ultra-micropores, limits the application of implicit heterogenous DFT-based kernel.

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