Evolution of far-from-equilibrium nanostructures on Ag(100) surfaces: Protrusions and indentations at extended step edges

Abstract

Scanning tunneling microscopy is used to monitor the formation and relaxation of nanoprotrusions and nanoindentations at extended step edges following submonolayer deposition of Ag on Ag(100). Deposition of up to about 1/4 ML Ag produces isolated two-dimensional (2D) Ag clusters, which subsequently diffuse, collide, and coalesce with extended step edges, thus forming protrusions. Deposition of larger submonolayer amounts of Ag causes existing step edges to advance across terraces, incorporating 2D islands. The resulting irregular step structure rapidly straightens after terminating deposition, except for a few larger indentations. Relaxation of these far-from-equilibrium step-edge nanoconfigurations is monitored to determine rates for restructuring versus local geometry and feature size. This behavior is analyzed utilizing kinetic Monte Carlo simulations of an atomistic lattice-gas model for relaxation of step-edge nanostructures. In this model, mass transport is mediated by diffusion along the step edge (i.e., "periphery diffusion"). The model consistently fits observed behavior, and allows a detailed characterization of the relaxation process, including assessment of key activation energies. Scanning tunneling microscopy is used to monitor the formation and relaxation of nanoprotrusions and nanoindentations at extended step edges following submonolayer deposition of Ag on Ag͑100͒. Deposition of up to about 1/4 ML Ag produces isolated two-dimensional ͑2D͒ Ag clusters, which subsequently diffuse, collide, and coalesce with extended step edges, thus forming protrusions. Deposition of larger submonolayer amounts of Ag causes existing step edges to advance across terraces, incorporating 2D islands. The resulting irregular step structure rapidly straightens after terminating deposition, except for a few larger indentations. Relaxation of these far-from-equilibrium step-edge nanoconfigurations is monitored to determine rates for restructuring versus local geometry and feature size. This behavior is analyzed utilizing kinetic Monte Carlo simulations of an atomistic lattice-gas model for relaxation of step-edge nanostructures. In this model, mass transport is mediated by diffusion along the step edge ͑i.e., ''periphery diffusion''͒. The model consistently fits observed behavior, and allows a detailed characterization of the relaxation process, including assessment of key activation energies.

Evolution of Two-Dimensional Wormlike Nanoclusters on Metal Surfaces

“…Experiments show that for diffusion of clusters of sizes up to 1000 atoms, mass transport is dominated by diffusion of atoms along the cluster boundary, i.e., the PD mechanism [8]. The same mechanism is also expected to govern the evolution of far-from-equilibrium structures in these systems [9,10]. Cluster dynamics on metal(111) surfaces, including diffusion [11] and restructuring [12], has also been studied extensively.…”

“…Slightly above this coverage, there is a fairly sharp transition from percolating vacancy regions to nonpercolating wormlike vacancy clusters [14]. Such wormlike vacancies are highly irregular; therefore, their reshaping processes yield extra insight as compared to the reshaping of adatom clusters with simpler geometries [10]. We note that adatom clusters cannot be readily prepared with these wormlike shapes.…”

“…However, atomic scale fluctuations will inevitably introduce a stochastic nature to the reshaping process. Their importance will increase as the cluster size further decreases [5,10].…”

“…Figure 4 shows corresponding KMC simulations of the evolution of a Ag(100) vacancy cluster consisting of about 8000 vacancy sites. We choose f 0.26 eV [10,21]. Figure 4(a) shows the initial configuration, and Fig.…”

“…Ideally, the rates would be chosen based on precise ab initio calculations of the associated activation barriers, but these are rarely available. Instead, KMC studies often include reasonable choices based on semiempirical studies and detailedbalance constraints [10,18,19].…”