Interplay between subsurface ordering, surface segregation, and adsorption on Pt-Ti(111) near-surface alloys.

Using the first-principles cluster expansion (CE) method, we studied the subsurface ordering of Pt/Pt-Ti(111) surface alloys and the effect of this ordering on segregation and adsorption behavior. The clusters included in the CE are optimized by a genetic algorithm to better describe the interactions between Pt and Ti atoms in the subsurface layer. Similar to bulk Pt-Ti alloys, Pt-Ti(111) subsurface alloys show a strong ordering tendency. A series of stable ordered Pt-Ti subsurface structures are identified from the two-dimensional (2D) CE. As an indication of the connection between the 2D and the bulk ordering, the CE predicts a ground-state Pt(8)Ti structure in the (111) subsurface layer, which is the same ordering as the close-packed plane of the bulk Pt(8)Ti compound. We carried out Monte Carlo simulations (MC) using the CE Hamiltonian to study the finite temperature stability of the Pt-Ti subsurface structures. The MC results show that subsurface structures in the Pt-rich range have higher order-disorder transition temperatures than their Ti-rich subsurface counterparts. We calculate the binding energy of different adsorbates (O, S, H, and NO) on Pt-terminated and Ti-segregated surfaces of ordered PtTi and Pt(8)Ti subsurface alloys. The binding of these adsorbates is generally stronger on Ti-segregated surfaces than Pt-terminated surfaces. The adsorption-induced Ti surface segregation is determined by two factors: (i) the unfavorable energy penalty for the Ti atom to segregate to the clean surface and (ii) the favorable energy decrease from stronger adsorbate binding on the Ti-segregated surface. The two factors introduce similar magnitude in energy change for the S and NO adsorption on Ti-segregated surfaces of PtTi subsurface alloys. We predict an adsorption-induced Ti surface segregation that is dependent on the atomic configurations of the Ti-segregated surfaces resulting from the competition of the two factors.