UC Berkeley

Robust ab initio investigations of nanoparticle surface properties require a method to identify candidate low-energy surface facets a priori. By assuming that low-energy surfaces are planes with high atomic density, we devise an efficient algorithm to screen for low-energy surface orientations, even if they have high (hkl) miller indices. We successfully predict the observed low-energy, high-index {1012¯} and {101¯4} surfaces of hematite α-Fe2O3, the {311} surfaces of cuprite Cu2O, and the {112} surfaces of anatase TiO2. We further tabulate candidate low-energy surface orientations for nine of the most common binary oxide structures. Screened surfaces are found to be generally applicable across isostructural compounds with varying chemistries, although relative surface energies between facets may vary based on the preferred coordination of the surface atoms.