The effect of heterogeneity in the randomly etched graphite model for carbon pore size characterization

Using perfect slit pores for the determination of the pore size distribution of activated carbons presents some drawbacks such as the observed absence of pores around 12–13 Å and usually poor correlation between simulated and experimental isotherms. In this study, we propose a model to introduce geometric heterogeneity using the randomly etched graphite approach. We calculated kernels of N2 isotherms mixing the etched pores isotherms with the perfect ones. The isotherms were calculated using biased grand canonical Monte Carlo and Lennard–Jones potentials in graphene sheets with explicit carbon atoms and solid–fluid parameters carefully adjusted. We found that the observed absence of pores around 12–13 Å was eliminated with the introduction of a few etched pores. Also, a surprising improvement of the fitting between the theoretical and the experimental isotherms was obtained. The study also showed that this approach can be used to establish a parameter (etched pore volume) that would characterize heterogeneity. Tests using real carbons showed consistently that the volume of etched pores is larger for those samples that present more heterogeneity. The obtained improvements are a strong indication that kernels with randomly etched pore models can effectively improve the pore size distribution of activated carbon.