Experiments in a Perfect World: Computer Simulations of Growth

1997 ◽  
Vol 11 (31) ◽  
pp. 3635-3646 ◽  
Author(s):  
Pablo Jensen ◽  
Hernán Larralde
Keyword(s):  
Thin Films ◽  
Computer Simulations ◽  
Growth Models ◽  
Mean Field ◽  
Field Analysis ◽  
Scaling Analysis ◽  
Size Distributions ◽  
Growth Mechanisms ◽  
Island Size ◽  
Analytical Approaches

We present two examples of computer simulations which can give unique information on the growth mechanisms of nanostructures and thin films. First, the morphologies and the island size distributions in the usual epitaxial growth models are studied. This information cannot be obtained from simple analytical approaches such as mean-field calculations or scaling analysis. Second, we analyze a new model which includes monomer evaporation and we show that computer simulations can help deciding between different mean-field analysis and lead to the correct growth exponents.

Why are computer simulations of growth useful?

1995 ◽  
Vol 407 ◽  
Author(s):  
Pablo Jensen ◽  
Laurent Bardotti ◽  
Albert-László Barabási ◽  
Hernán Larralde ◽  
Shlomo Havlin ◽  
...  
Keyword(s):  
Thin Films ◽  
Computer Simulations ◽  
Mean Field ◽  
Experimental Results ◽  
Small Cluster ◽  
Scaling Analysis ◽  
Size Distributions ◽  
Growth Mechanisms ◽  
Island Size ◽  
Unique Information

ABSTRACTWe show how computer simulations can give unique information on the growth of nanostructures and thin films. Specifically, they can predict the morphologies and the island size distributions corresponding to different growth mechanisms. This information cannot be obtained from other approaches such as mean-field mathematical theories or scaling analysis. Special attention is given to the effects of small cluster mobility on experimental results.

Beyond-Mean-Field Treatments of Island Formation during Submonolayer Deposition: Island Size Distributions for Large Critical Sizes

2004 ◽  
Vol 859 ◽  
Author(s):  
Maozhi Li ◽  
Maria C. Bartelt ◽  
J. W. Evans
Keyword(s):  
Critical Size ◽  
Kinetic Monte Carlo ◽  
Mean Field ◽  
Coarse Grained ◽  
Size Distributions ◽  
Island Size ◽  
Island Formation ◽  
Scaling Properties ◽  
Cpu Time ◽  
Atomistic Models

ABSTRACTKinetic Monte Carlo (KMC) simulation of atomistic models reveals the failure of mean-field treatments of the island size distribution (ISD) for islands formed by homogeneous nucleation during submonolayer deposition on perfect surfaces. KMC also facilitates analysis of scaling properties of the ISD, although here some misperceptions persist which we attempt to clarify. However, KMC becomes inefficient for highly reversible island formation (e.g., for large values of a critical size, i, above which islands are stable) due to the high density of diffusing adatoms on the surface. This reduced efficiency is quantified here with results for CPU time versus i. This feature has motivated development of alternative beyond-mean-field coarse-grained approaches which should be more efficient for large i. We provide results for the ISD for a range of i = 1, 2, 3, and 6 using one such approach, a stochastic geometry-based simulation (GBS) strategy.

scholarly journals Mean Field Analysis of Orientation Selective Grain Growth Driven By Interface-Energy Anisotropy

1994 ◽  
Vol 343 ◽  
Author(s):  
J. A. Floro ◽  
C. V. Thompson
Keyword(s):  
Grain Size ◽  
Size Distribution ◽  
Grain Growth ◽  
Texture Evolution ◽  
Mean Field ◽  
Orientation Distribution ◽  
Interface Energy ◽  
Abnormal Grain Growth ◽  
Field Analysis ◽  
Energy Anisotropy

ABSTRACTAbnormal grain growth is characterized by the lack of a steady state grain size distribution. In extreme cases the size distribution becomes transiently bimodal, with a few grains growing much larger than the average size. This is known as secondary grain growth. In polycrystalline thin films, the surface energy γs and film/substrate interfacial energy γi vary with grain orientation, providing an orientation-selective driving force that can lead to abnormal grain growth. We employ a mean field analysis that incorporates the effect of interface energy anisotropy to predict the evolution of the grain size/orientation distribution. While abnormal grain growth and texture evolution always result when interface energy anisotropy is present, whether secondary grain growth occurs will depend sensitively on the details of the orientation dependence of γi.

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