MnO Spin-Wave Dispersion Curves from Powder Diffraction Data

TL;DR

This paper introduces a model-independent method to extract spin-wave dispersion curves from powder diffraction data using reverse Monte Carlo simulations, providing results consistent with traditional spectroscopic techniques.

Contribution

It presents a novel approach combining reverse Monte Carlo refinement with statistical analysis to determine spin-wave dispersions from powder data, bypassing the need for single-crystal measurements.

Findings

Dispersion curves agree with neutron triple-axis spectroscopic results.

The method is model-independent and applicable to powder diffraction data.

Provides a new tool for studying magnetic excitations in materials.

Abstract

We describe a model-independent approach for the extraction of spin-wave dispersion curves from neutron total scattering data. The method utilises a statistical analysis of real-space spin configurations to calculate spin-dynamical quantities. The RMCProfile implementation of the reverse Monte Carlo refinement process is used to generate a large ensemble of supercell spin configurations from powder diffraction data. Our analysis of these configurations gives spin-wave dispersion curves that agree well with those determined independently using neutron triple-axis spectroscopic techniques.