Revealing low-energy surfaces of multinary compounds by controlling surface coordination environments

Abstract

When modeling surfaces of multinary compounds, conventional cleavage planes often cut through strongly bonded polyhedra, resulting in unphysical surface energies. Here, we introduce SALAMI (Symmetric Atomic Layers for Arbitrary Multinary Interfaces), a Python package that generates symmetric, charge-neutral, dipole-free, and low-energy slab models for multinary compounds. SALAMI performs combinatorial searches to selectively remove surface atoms and generate corrugated terminations that preserve optimal coordination environments. We applied this workflow to all symmetrically inequivalent crystallographic orientations with Miller indices up to 2 for two prototypical structures: the solid-state electrolyte Li3PS4 and the transparent conducting oxide ZnSb2O6. Density functional theory calculations reveal that Li3PS4 must preserve all PS4 units to achieve the minimum surface energy. For ZnSb2O6, low-energy surfaces are achieved by partial undercoordination of surface Sb atoms to SbO5 or SbO4 from the bulk SbO6, depending on the surface orientations. Compared to surface models generated with unconstrained coordination, applying constraints to achieve optimal local coordination environments significantly lowers surface energies, shrinking the volume of the predicted Wulff shape by approximately 20%. Our results demonstrate that meticulous control of local coordination environments is necessary for accurately predicting the surface energetics of multinary compounds.