Advertisement

Concluding Remarks

Part of the Materials Science book series (SSMATERIALS, volume 108)

In writing this monograph, we do not intend to provide a detailed survey of the vast number of experimental results on thin film growth reported in the literature. Instead, we hope to present a simplified view of the modeling techniques used to describe thin films grown by different experimental deposition techniques. In particular, we want to highlight the importance of nonlocal effects in thin film growth, as nonlocal effects are necessary to describe many experimental observations. For example, Fig. 4.1 provides a summary of the range of growth exponents β predicted by both local and nonlocal models. Local models, both continuum models and discrete models, typically give a β value smaller than 0.25. On the other hand, depending on the magnitude of the sticking coefficient s0, the competition between shadowing and reemission in nonlocal models can give a β value in the range 0–1. In the same graph, we also display a characteristic range of β values reported in experimental papers in the literature for different deposition techniques including thermal evaporation, sputter deposition, chemical vapor deposition, and oblique angle deposition. It appears that local models account for the measured exponent values reasonably well for thermal evaporation with normally incident flux, a situation where there is no geometrical shadowing. The sticking coefficient for most materials in thermal evaporation is equal to 1 because particles in the incident flux tend to have a small kinetic energy, typically less than a fraction of an eV. In this case, dynamic scaling should be applicable, and the surface is likely to be self-affine with no mound formation.

Keywords

Chemical Vapor Deposition Local Model Thermal Evaporation Nonlocal Effect Incident Flux 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Personalised recommendations