Download or read book GPU Enhanced Simulations of Glancing Angle Deposition of Metal Thin-films written by Xuejing Liu and published by . This book was released on 2012 with total page 67 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thin-films grown via glancing-angle deposition (GLAD) have interesting structural, mechanical, and optical properties and may be used for a variety of applications including sensors, optical filters, antireflection coatings, fuel cells, and magnetic data storage. However, due in part to the complexity of the resulting thin-film structures as well as to the large range of time- and length- scales, realistic simulations of the thin-film growth process for large deposition angles have in the past been difficult. As a result, typically only simulations of effective models of GLAD, or of more realistic models for smaller deposition angles, have been carried out. As a first step in understanding the dependence of the surface morphology and microstructure in GLAD on deposition parameters, here we present the results of large-scale MD simulations of Cu/Cu(100) growth for the case of large deposition angle. In particular, by taking advantage of the speed of recently developed graphical-processing-units (GPUs) we have carried out large-scale GPU-enhanced MD simulations of Cu/Cu(100) growth up to 20 monolayers (ML) for deposition angles (corresponding to the angle with respect to the substrate normal) ranging from 50o to 85o and for both random and fixed azimuthal angles. In general, we find good agreement with experiment results for the dependence of thin-film porosity on deposition angle and film-thickness. Results for the dependence of the surface roughness, lateral correlation length and microstructure (e.g. defect density, vacancy density, surface sites, and strain) on the deposition angle and film thickness are also presented.