Extended kinetic lattice grand canonical Monte Carlo simulation method for transport of multicomponent ion mixtures through a model nanopore system

Abstract

An extended version of the original kinetic lattice grand canonical Monte Carlo simulation method combined with mean field theory (KLGCMC/MF) (J. Chem. Phys. 2007, 127, 024706) is presented for the study of transport of multicomponent ion mixtures through a model nanopore. Comparison of the extended KLGCMC/MF (eKLGCMC/MF) simulation results with Poisson-Nernst-Planck (PNP) calculations is also made to confirm the validity of the extended simulation approach. Unlike the original version of KLGCMC/MF simulation method that treats only a binary ionic solution with one cation and one anion species, this extended version can deal with a system that includes ternary ion mixtures. A diffusion probability algorithm is also added to the extended version of the simulation method to describe the inhomogeneous diffusivity of ions that is often observed in the ion permeation through nanopores. Both Legendre and Chebyshev polynomials of the second kind were tested as a basis set for the basis set expansion (BSE) method with which to calculate the reaction field energy in the eKLGCMC/MF simulation. It turned out that the Legendre polynomials perform better than the Chebyshev polynomials, and as a result, the Legendre polynomials were implemented in the current version of eKLGCMC/MF simulation algorithm. The presented eKLGCMC/MF simulation method with new features finds its potential applications in nanopore systems where the correlation between ion species with the same sign of charges plays a key role such as oscillating ion currents or anomalous mole fraction effects.

Dimensionality reduction in diffusion–reaction systems

“…Lattice‐based Monte Carlo simulations 33–36 were performed to confirm the theoretical predictions for these models. An initially implanted molecule moves via a random walk.…”

Biomolecular phase separation through theoretical and computational microscope

“…134 The Monte Carlo (MC) scheme tracks a system through probabilistic calculations using random sampling, 135 while MD simulations involve integrating Newton's equations of motion, enabling representation of the positions, velocities, and accelerations of particles as functions of time. 136 Both methods are widely used in simulations of soft matter systems, [137][138][139][140][141][142] and can be applied to biomolecular phase separation.…”