Self‐Diffusion on Au(100): A Density Functional Theory Study

Abstract

We used density functional theory to detail new self-diffusion mechanisms on perfect and imperfect Au(100) surfaces. Herein, we report binding energies of stable intermediates and transition states lying on the potential energy surface for these systems. We report migration pathways in the presence of a variety of surface defects and along different step edges, explaining their energetics in terms of chemical bonding. Furthermore, diffusion rate constants are deduced, which are useful for both experimental verification and for implementation into large-scale kinetic Monte Carlo simulations.

First-principles kinetics study of carbon monoxide promoted Ostwald ripening of Au particles on FeO/Pt(111)

“…the contact angle between the metal particles and the support as a measurement of metal particle-support interaction; ν s is the vibration frequency of monomer species on supports, which will be considered as constant 6 × 10 13 s − 1 as a good approximation [69][70][71][72] ; is the volume of bulk metal atoms (16.96 Å 3 for Au) [73] ; a 0 is the lattice constant of the support (3.10 Å for FeO/Pt(111)) [62,63]…”

Neural network and ReaxFF comparison for Au properties

“…Vacancy formation and diffusion calculations were also included in the bulk dataset. Our surface dataset includes calculations on fcc(111) surfaces as well as a variety of fcc(100) surface diffusion pathways that were originally generated in a previous work by Pötting et al The training set used single‐point energies on the latter coordinates (without geometry relaxations) calculated using the methods listed above. Our cluster data include various 3D ordered, planar, and disordered structures that contain up to 126 atoms.…”

Growth regimes of porous gold thin films deposited by magnetron sputtering at oblique incidence: from compact to columnar microstructures

“…In the literature there are numerical codes that consider more complex processes [26,27], such as thermally activated mechanisms or ion induced damage of the films during growth, which require the previous knowledge of activation energies or thresholds for the diverse processes. Although the precise values of these parameters do not appear in the literature in most of the cases, we have solved the NASCAM code in multiple conditions estimating the energy thresholds for these processes through [28] as a test for our model. Results of these simulations corroborate the assumptions of our model and indicate that, in our experimental conditions, surface shadowing determines the main features of the film microstructure, the rest of the processes being responsible for the removal of some occluded voids inside the material.…”