Nanostructure determination from the pair distribution function: A parametric study of the INVERT approach

TL;DR

This paper investigates the INVERT method for determining nanostructures from pair distribution functions, analyzing its mechanisms, implementation variations, and the influence of algorithm weighting on structure refinement in disordered materials.

Contribution

It provides a detailed parametric analysis of the INVERT approach, exploring different algorithm implementations and the effects of weighting schemes on structure refinement.

Findings

Variance and fit-to-data terms influence refinement outcomes

Density fluctuations and configurational jamming affect RMC fitting

Challenges in developing transferable weighting schemes are highlighted

Abstract

We present a detailed study of the mechanism by which the INVERT method [Phys. Rev. Lett. 104, 125501] guides structure refinement of disordered materials. We present a number of different possible implementations of the central algorithm and explore the question of algorithm weighting. Our analysis includes quantification of the relative contributions of variance and fit-to-data terms during structure refinement, which leads us to study the roles of density fluctuations and configurational jamming in the RMC fitting process. We present a parametric study of the pair distribution function solution space for C60, a-Si and a-SiO2, which serves to highlight the difficulties faced in developing a transferable weighting scheme.