Reverse Monte Carlo modeling for low-dimensional systems

Abstract

Reverse Monte Carlo (RMC) is one of the commonly used approaches for modeling total scattering data. However, to extend the capability of the RMC method for refining the structure of nanomaterials, the dimensionality and finite size need to be considered when calculating the pair distribution function (PDF). To achieve this, the simulation box must be set up to remove the periodic boundary condition in one, two or three of the dimensions. This then requires a correction to be applied for the difference in number density between the real system and the simulation box. In certain circumstances an analytical correction for the uncorrelated pairings of atoms is also applied. The validity and applicability of our methodology is demonstrated by applying the algorithms to simulate the PDF patterns of carbon systems with various dimensions, and also by using them to fit experimental data of CuO nanoparticles. This alternative approach for characterizing the local structure of nano-systems with the total scattering technique will be made available via the RMCProfile package. The theoretical formulation and detailed explanation of the analytical corrections for low-dimensional systems – 2D nanosheets, 1D nanowires and 0D nanoparticles – is also given.