<p>The predictive design of alloy (electro)catalysts is necessary to identify catalysts more active, selective, stable, and low-cost than the pure metals. Our fundamental understanding of the catalytic behavior of alloys is limited however as it is typically derived from that of flat, “pristine” surfaces, not the industrially-relevant, defect-rich surfaces found on nanoparticles. We use density functional theory (DFT) modeling to probe strain, ligand, and ensemble effects on transition metal surfaces with step-defects. We find the response of the step to strain and ligand effects is much smaller in magnitude and sometimes opposite in direction to that of a flat surface, due to the breaking of two-dimensional symmetry at the step. Insight gained from flat surfaces alone is therefore not sufficient to understand (alloy) nanoparticles; defect sites must be explicitly considered. We additionally find that the one-dimensional, bimetallic ensemble created by the selective decoration of step defects can break adsorbate scaling, yielding surface alloys with potentially enhanced catalytic performance.</p>