| The focus of the present research is to develop novel kinetic lattice Monte Carlo (KLMC) models to study the nature of thin film deposition. The research can be divided into two phases.; In the first phase, three levels of simulation models, namely embedded atom method (EAM), KLMC, and FACET (a two dimensional geometric model), are integrated to investigate the growth of physical vapor deposition (PVD) Cu thin films for a range of processing conditions. The EAM method is used to calculate the activation energies of some important diffusion events on Cu surfaces in a system with thousands of atoms, and then the activation energies are input into our KLMC model to simulate facet growth rates as a function of processing conditions on a submicron scale. These facet growth rates can be input into FACET code to describe microstructural evolution on a Micron scale. The integration makes it possible to investigate the microstructural evolution of Cu films spanning many orders of magnitude in size and time scales.; In the second phase, Molybdenum (Mo) tip growth in a pre-etched hole is studied by developing POLYGROW, a three dimensional KLMC model which is capable of simulating polycrystalline thin film growth including multiple grain orientations and grain boundaries. This is the first polycrystalline KLMC code which can fully model multiple lattices of any orientation. POLYGROW simulates the deposition of Mo atoms into pre-etched holes, including surface diffusion, nucleation and growth of Mo clusters, and impingement of growing clusters to form grain boundaries. Narrowing of the growth aperture results in a narrowing of the growth flux, so that conical tips are grown. The critical issue is determining the sharpness of the tips and their long-term stability, as that dominates their electron emission efficiency. Some important results, such as the crystal orientation, the grain shape, the grain size, and the sharpness of Mo tips as a function of the processing conditions including deposition rate, substrate temperature, etching rate, annealing temperature, and annealing time, are discussed.; The ultimate goal of the present research is to develop and share design tools which will assist in optimizing the final microstructure of thin films based on intelligent process optimization. Therefore, the future goals of this study are to improve POLYGROW's computational speed and capacity by parallelizing the code, share it with the computational materials community, and eventually help process engineers to better understand and optimize their processing conditions. |
