An Innovative Approach for Molecular Simulation of Nanostructured Adsorption Isotherms via the Ant Colony Method

Abstract

The original grand canonical Monte Carlo (GCMC) molecular simulation method heavily relies on pure random steps for its various phases of displacement, removal and insertion. A new algorithm is presented in this Article which employs the global optimization ant colony technique in a state-of-the-art algorithm to predict the adsorption isotherm of any adsorbate inside nanostructured adsorbents. Several experimentally measured isotherms are used from the literature to successfully validate the proposed method. A detailed flowchart is presented to describe the entire algorithm. The Akaike information criterion is used as a part of the proposed method to determine the optimum number of required iterations. It was clearly demonstrated that our in-house ant colony molecular simulation (ACMS) method outperforms the conventional GCMC method for all case studies. The simulation results also indicate that the newly proposed algorithm performs several orders of magnitude faster than GCMC with the same or better accuracies.

Experimental and simulation study of the effect of surface functional groups decoration on CH4 and H2 storage capacity of microporous carbons

“…Equilibrium steps were performed with our optimised grand canonical based molecular simulation codes. Then 10 6 Monte Carlo steps were used to predict adsorption capacities to improve the accuracy of the simulations and reduce the number of iterations [28,29]. The chemical potential at the defined thermodynamic states can be computed from the Peng-Robinson equation of state [32,33].…”