Extension of the effective solid-fluid Steele potential for Mie force fields

Abstract

Molecular simulation of fluid systems in the presence of surfaces require computationally expensive calculations due to the large number of solid–fluid pair interactions involved. Representing the explicit solid as a continuous wall with an effective potential can significantly reduce the computational time and allows exploring larger temporal and spatial scales. The well-known (10-4-3) Steele potential is one such analytic expression that faithfully represents the effective solid–fluid interactions for homonuclear crystalline solids with hexagonal lattice symmetry. However, this and most of the effective potentials found in the literature have been developed for fluids and solids interacting exclusively through Lennard-Jones potentials. In this work, we extend the Steele model to obtain the effective wall–fluid potentials for Mie force fields. We perform molecular dynamics simulations of coarse-grained fluids modelled via the SAFT force field approach in the presence of explicit and implicit surfaces to compare structural and dynamic properties in both representations. Also, we study the adsorption of ethane into slit-like pores with explicit and implicit surfaces via grand canonical Monte Carlo simulations. We explore the validity and the improvement in the simulation performance as well as the limitations of the proposed expression.

GRAPHICAL ABSTRACT

Keywords:

• Steele potential
• adsorption
• coarse-graining
• MD simulations

Acknowledgements

EAM wishes to express his gratitude to Prof. Peter Cummings for the many years of his selfless support, engaging scientific interactions and friendship.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The authors acknowledge support from the U.K. Engineering and Research Council (EPSRC) through grants to the Molecular Systems Engineering group (Grants EP/EP016340, EP/J014958, and EP/R013152). Computations were performed employing the resources of the Imperial College High Performance computing service and the UK Materials and Molecular Modelling Hub, which is partially funded by EPSRC (EP/P020194).