2, University of Florida, Gainesville, Florida, United States
3, University of South Carolina, Columbia, South Carolina, United States
It has been shown in various metallic systems that chemical stability and nanostructure can be tuned by alloying with a chemically more inert noble metal. For example, Au-Cu alloy and intermetallic nanoparticles with Cu atomic fractions below the parting limit are resistive to dealloying in the presence of a chemical etchant, while those with Cu content above the parting limit tend to form spongy nanoframes. This tuneability thus makes noble metal systems interesting as potential hierarchical waste forms for volatile species such as Mo, Tc, or Rh
Detailed information on atomic scale ordering and nanostructure in order-disorder (intermetallic-solid solution) phase transitions is not easily accessible. This is a result of the so called “nanostructure problem” within the field of classical crystallography. The depth and inverse nature of this problem requires complex modelling to fit observed data, so that structure – processing - property relationships can be leveraged to tailor material performance. Here we probe the correlated nature of disorder in Au-Cu systems, which show prototypical order-disorder (o-d) transformations. We achieve this through a novel approach, by tuning an evolutionary algorithm for global optimization of large ensembles to fit observed pair distribution functions (PDFs). These models are further refined using density functional theory (DFT) to elucidate the subtle bond-length fluctuations associated with correlated disorder.