Abstract:
Two dimensional materials are of increasing interest as building blocks for functional coatings, catalysts, electrochemical devices, and so on. While increasingly sophisticated synthesis and processing routes have been designed to obtain high-quality exfoliated nanosheets and derivative assemblies, structural characterization of these materials remains challenging. Nanosheet materials exhibit disorder across multiple length scales: point defects and surface relaxation driven by surface perturbations influence the local structure; meanwhile sheet-to-sheet correlations influence the mesostructure; and the 2D crystallinity of the nanosheet ensures atom correlations beyond the nanometer scale. The ongoing work presented here develops methods of accounting for these multiple bonding regimes in the analysis of X-ray and neutron total scattering data. The atomic pair distribution function (PDF) is found to be quite sensitive to interlayer correlations, which are critical in correctly modelling nanosheet assemblies with intermediate degrees of layer disorder. Further, the application of a Differential Evolution optimization and of a Markov chain Monte Carlo posterior sampling algorithm to the fitting of computational and experimental data is presented. These techniques are of particular interest to the nano-crystallographer, where the rigid constraints of macro-crystallography are often relaxed. Rather, a description of distributions of likely states can provide a more serviceable approach to understanding trends in the materials design paradigm. Cases presented will include computed data for a graphene-like nanosheet ensemble, and experimental synchrotron X-ray data obtained for a layer-disordered S-Mn02 nanosheet ensemble.