SPINVERT: A program for refinement of paramagnetic diffuse scattering data

TL;DR

SPINVERT is a computational tool that refines magnetic diffuse scattering data to recover three-dimensional magnetic correlations in disordered magnetic materials, demonstrated through simulations and experimental data analysis.

Contribution

This paper introduces SPINVERT, a novel reverse Monte Carlo refinement program for analyzing magnetic diffuse scattering in disordered magnets.

Findings

Successfully recovers 3D magnetic correlations from powder data.

Reveals overlooked similarities between compounds in experimental case study.

Assesses sensitivity of refinement to data limitations.

Abstract

We present a program (SPINVERT; http://spinvert.chem.ox.ac.uk)for refinement of magnetic diffuse scattering data for frustrated magnets, spin liquids, spin glasses, and other magnetically disordered materials. The approach uses reverse Monte Carlo refinement to fit a large configuration of spins to experimental powder neutron diffraction data. Despite fitting to spherically-averaged data, this approach allows the recovery of the three-dimensional magnetic diffuse scattering pattern and the spin-pair correlation function. We illustrate the use of the SPINVERT program with two case studies. First we use simulated powder data for the canonical Heisenberg kagome model to discuss the sensitivity of SPINVERT refinement to both pairwise and higher-order spin correlations. The effect of limited experimental data on the results is also considered. Second, we re-analyse published experimental data on the frustrated system Y0.5Ca0.5BaCo4O7. The results from SPINVERT refinement indicate similarities between Y0.5Ca0.5BaCo4O7 and its parent compound YBaCo4O7, which were overlooked in previous analysis using powder data.