Reliable prediction of adsorption isotherms via genetic algorithm molecular simulation

Abstract

Conventional molecular simulation techniques such as grand canonical Monte Carlo (GCMC) strictly rely on purely random search inside the simulation box for predicting the adsorption isotherms. This blind search is usually extremely time demanding for providing a faithful approximation of the real isotherm and in some cases may lead to non-optimal solutions. A novel approach is presented in this article which does not use any of the classical steps of the standard GCMC method, such as displacement, insertation, and removal. The new approach is based on the well-known genetic algorithm to find the optimal configuration for adsorption of any adsorbate on a structured adsorbent under prevailing pressure and temperature. The proposed approach considers the molecular simulation problem as a global optimization challenge. A detailed flow chart of our so-called genetic algorithm molecular simulation (GAMS) method is presented, which is entirely different from traditions molecular simulation approaches. Three real case studies (for adsorption of CO and H over various zeolites) are borrowed from literature to clearly illustrate the superior performances of the proposed method over the standard GCMC technique. For the present method, the average absolute values of percentage errors are around 11% (RHO-H), 5% (CHA-CO), and 16% (BEA-CO), while they were about 70%, 15%, and 40% for the standard GCMC technique, respectively.

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

“…Evidently, the ACMS method performs much faster and more accurately than the conventional GCMC method. The values corresponding to the GAMS method are for the similar results as presented in our previous work …”

“…A brief comparison of Figure with our previously presented flowchart of the GAMS method clearly reveals that the new ACMS method is not only much simpler to understand and develop, but it also will perform much faster, as will be discussed later.…”

“…The Akaike information criterion was also used to find the optimal number of iterations required in the most inner loop to provide the best configuration. As Table shows, the new ACMS method performs much faster than our previous GAMS technique . Moreover, the ACMS algorithm is much simpler than the GAMS method and it can be developed more easily.…”

“…A brief comparison of Figure 1 with our previously presented flowchart of the GAMS method 23 clearly reveals that the new ACMS method is not only much simpler to understand and develop, but it also will perform much faster, as will be discussed later. As before, the following cost function should be optimized to find the proper number of molecules inside the simulation box at the prevailing temperature and pressure…”

“…In our previous research, a new approach was proposed to predict the adsorption isotherms by coupling the genetic algorithm with molecular simulation and presenting the so-called GAMS method. 23 Several adsorption isotherms were borrowed from the literature to clearly demonstrate that the proposed method successfully outperforms the conventional GCMC technique. While our new GAMS method predicted the corresponding adsorption isotherms very brilliantly, its complexity made its application too limited for nonmathematicians.…”