Hosted by: Ian Robinson

Materials with significant local distortions from the bulk average structure often show novel and useful properties. Identifying and quantifying the nature and extent of this correlated disorder1 is however quite challenging, as traditional crystallography and the associated tools often do not adequately describe such nanostructured materials. This is a manifestation of the "nanostructure problem"2 and the solution requires complex modelling incorporating multiple techniques. This talk focuses on the application of X-ray scattering and complex modelling as tools for understanding various nanostructured materials, including nanocrystalline nickel with large clusters of planar defects, interlayered non-silicon photovoltaics, geometrically frustrated ternary alkaline earth hexaborides, manganese dioxide nanosheet assemblies, and nanostructured noble metal alloys. Complex modelling leveraging both standard techniques as well as genetic algorithms, Markov chain Monte Carlo, and machine learning together provide synergistic understanding spanning length scales from a few Ångstrom to hundreds of nanometers. Additionally, an example of how complex modelling can be used to shed understanding on the nature of crystallographic disorder in superconducting alloys of 2H-TaSe2−xSx is discussed. A potential model is proposed whereby alloys of 2H-TaSe2−xSx are composed of interlayered sheets with two unique c-axes. This model is consistent with the observed 00l Bragg profile broadening trend and may help explain the suppression of charge density waves and maximization of superconductivity in these systems. 1. Keen, D. A. & Goodwin, A. L. The crystallography of correlated disorder. Nature 521, 303–309 (2015). 2. Billinge, S. J. L. & Levin, I. The problem with determining atomic structure at the nanoscale. Science 316, 561–565 (2007).