Nucleation, Growth, and Relaxation of Thin Films: Metal(100) Homoepitaxial Systems

We describe work in our laboratory that has shed new light on nucleation, growth, and relaxation processes in thin metal films. The progress comes from the synergistic and synchronous implementation of theory and experiment, which reveals surprising secrets hidden a very simple model system

Additive-enhanced coarsening and smoothening of metal films: Complex mass-flow dynamics underlying nanostructure evolution

Exposure of Ag/Ag(100) thin films to molecular oxygen (O2) at 220–250 K is shown to activate low-temperature coarsening of submonolayer island distributions, and a smoothing of multilayer films with “mounded” morphologies. Dissociation of O2 at kink sites populates step edges with atomic oxygen (O), modifying the step-edge energetics, and facilitating Ostwald ripening of film nanostructures. We propose that ripening occurs by “easy” detachment and terrace diffusion of an AgnO species. Cluster diffusion does not play a significant role, contrasting with the O-free system

Structure of chalcogen overlayers on Au(111): Density functional theory and lattice-gas modeling

Ordering of different chalcogens, S, Se, and Te, on Au(111) exhibit broad similarities but also some distinct features, which must reflect subtle differences in relative values of the long-range pair and many-body lateral interactions between adatoms. We develop lattice-gas (LG) models within a cluster expansion framework, which includes about 50 interaction parameters. These LG models are developed based on density functional theory (DFT) analysis of the energetics of key adlayer configurations in combination with the Monte Carlo (MC) simulation of the LG models to identify statistically relevant adlayer motifs, i.e., model development is based entirely on theoretical considerations. The MC simulation guides additional DFT analysis and iterative model refinement. Given their complexity, development of optimal models is also aided by strategies from supervised machine learning. The model for S successfully captures ordering motifs over a broader range of coverage than achieved by previous models, and models for Se and Te capture the features of ordering, which are distinct from those for S. More specifically, the modeling for all three chalcogens successfully explains the linear adatom rows (also subtle differences between them) observed at low coverages of ∼0.1 monolayer. The model for S also leads to a new possible explanation for the experimentally observed phase with a (5 × 5)-type low energy electron diffraction (LEED) pattern at 0.28 ML and to predictions for LEED patterns that would be observed with Se and Te at this coverage