Atomistic and Coarse-Grained Modeling Strategies for Thin Film Nucleation and Growth on Quasicrystalline Surfaces

2013 ◽  
Vol 1517 ◽  
Author(s):  
James W. Evans ◽  
Patricia A. Thiel ◽  
Bariş Ünal
Keyword(s):  
Lattice Gas ◽  
Film Growth ◽  
Kinetic Monte Carlo ◽  
Coarse Grained ◽  
Dynamics Modeling ◽  
Strain Effects ◽  
Adsorption Sites ◽  
Quantum Size ◽  
Step Dynamics ◽  
Key Aspects

ABSTRACTStrategies are described for modeling the kinetics of non-equilibrium film growth during deposition of metals on quasicrystalline substrates. We review previous atomistic-level lattice-gas modeling and Kinetic Monte Carlo simulation for pseudomorphic (or commensurate) submonolayer growth based on a “disordered or irregular bond-network” (DBN) of neighboring adsorption sites. We describe extensions to treat strain effects and multilayer growth, and discuss a type of commensurate-incommensurate transition expected around 2-3 layers. We also describe a coarse-grained “step dynamics” modeling which tracks the dynamics of island edges in each layer rather than individual atoms. Step dynamics models can also include key aspects of the physics such as layer-dependent energetics, including quantum size effects, and strain effects.

scholarly journals Kinetic Roughening of Multilayer Ag/Ag(100) Films: Complex Temperature-Dependence in a Simple System

2000 ◽  
Vol 619 ◽  
Author(s):  
C.R. Stoldt ◽  
K.J. Caspersen ◽  
M.C. Bartelt ◽  
C.J. Jenks ◽  
J.W. Evans ◽  
...  
Keyword(s):  
Lattice Gas ◽  
Film Growth ◽  
Kinetic Monte Carlo ◽  
Variable Temperature ◽  
Scanning Tunneling ◽  
Tunneling Microscopy ◽  
Adsorption Sites ◽  
Lattice Gas Models ◽  
Temperature Scanning ◽  
Complex Temperature

ABSTRACTMetal(100) homoepitaxial systems constitute perhaps the simplest class of systems in which to study thin film growth. Yet, our Variable-Temperature Scanning Tunneling Microscopy (VTSTM) analysis of Ag/Ag(100) homoepitaxy reveals that the variation of roughness with temperature is extraordinarily complex. As the deposition temperature is reduced from 300K to 50K, the roughness of 25 monolayer films first increases, then decreases, and then increases again. Furthermore, a transition from mound formation to self-affine (semi-fractal) growth occurs at around 135K. We postulate that the following the atomistic mechanisms underly this behavior: the existence of a small step-edge barrier inhibiting diffusive downward transport; “downward funneling” of atoms deposited at step edges and microprotrusions towards lower four-fold hollow adsorption sites; and statistically significant deviations from “complete” downward funneling at lower temperatures, where deposited atoms instead become trapped on the sides of (the more prevalent) small steep microprotrusions. To support these postulates, we employ kinetic Monte Carlo simulations to show that atomistic (lattice-gas) models for epitaxial growth, which incorporate these mechanisms, reproduce the experimental data quantitatively.

scholarly journals Cluster Diffusion and Coalescence on Metal Surfaces: applications of a Self-learning Kinetic Monte-Carlo method

2004 ◽  
Vol 859 ◽  
Author(s):  
Talat S. Rahman ◽  
Abdelkader Kara ◽  
Altaf Karim ◽  
Oleg Trushin
Keyword(s):  
Monte Carlo ◽  
Lattice Gas ◽  
Film Growth ◽  
Diffusion Processes ◽  
Kinetic Monte Carlo ◽  
Automatic Generation ◽  
Point Search ◽  
Novel Method ◽  
Rate Limiting ◽  
Self Learning

ABSTRACTThe Kinetic Monte Carlo (KMC) method has become an important tool for examination of phenomena like surface diffusion and thin film growth because of its ability to carry out simulations for time scales that are relevant to experiments. But the method generally has limited predictive power because of its reliance on predetermined atomic events and their energetics as input. We present a novel method, within the lattice gas model in which we combine standard KMC with automatic generation of a table of microscopic events, facilitated by a pattern recognition scheme. Each time the system encounters a new configuration, the algorithm initiates a procedure for saddle point search around a given energy minimum. Nontrivial paths are thus selected and the fully characterized transition path is permanently recorded in a database for future usage. The system thus automatically builds up all possible single and multiple atom processes that it needs for a sustained simulation. Application of the method to the examination of the diffusion of 2-dimensional adatom clusters on Cu(111) displays the key role played by specific diffusion processes and also reveals the presence of a number of multiple atom processes, whose importance is found to decrease with increasing cluster size and decreasing surface temperature. Similarly, the rate limiting steps in the coalescence of adatom islands are determined. Results are compared with those from experiments where available and with those from KMC simulations based on a fixed catalogue of diffusion processes.

Kinetic Monte Carlo Simulation of Diamond Film Growth with the Inclusion of Surface Migration

1998 ◽  
Vol 527 ◽  
Author(s):  
Armando Netto ◽  
Michael Frenklach
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Film Growth ◽  
Kinetic Monte Carlo ◽  
Diamond Films ◽  
State Theory ◽  
Diamond Surface ◽  
Diamond Growth ◽  
Gaseous Species ◽  
Surface Migration

ABSTRACTDiamond films are of interest in many practical applications but the technology of producing high-quality, low-cost diamond is still lacking. To reach this goal, it is necessary to understand the mechanism underlying diamond deposition. Most reaction models advanced thus far do not consider surface diffusion, but recent theoretical results, founded on quantum-mechanical calculations and localized kinetic analysis, highlight the critical role that surface migration may play in growth of diamond films. In this paper we report a three-dimensional time-dependent Monte Carlo simulations of diamond growth which consider adsorption, desorption, lattice incorporation, and surface migration. The reaction mechanism includes seven gas-surface, four surface migration, and two surface-only reaction steps. The reaction probabilities are founded on the results of quantum-chemical and transition-state-theory calculations. The kinetic Monte Carlo simulations show that, starting with an ideal {100}-(2×1) reconstructed diamond surface, the model is able to produce a continuous film growth. The smoothness of the growing film and the developing morphology are shown to be influenced by rate parameter values and by deposition conditions such as temperature and gaseous species concentrations.

Simulations of chemical vapor deposition diamond film growth using a kinetic Monte Carlo model

2010 ◽  
Vol 108 (1) ◽  
pp. 014905 ◽  
Author(s):  
P. W. May ◽  
J. N. Harvey ◽  
N. L. Allan ◽  
J. C. Richley ◽  
Yu. A. Mankelevich
Keyword(s):  
Monte Carlo ◽  
Chemical Vapor Deposition ◽  
Diamond Film ◽  
Vapor Deposition ◽  
Film Growth ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Model ◽  
Chemical Vapor ◽  
Chemical Vapor Deposition Diamond ◽  
Diamond Film Growth

Kinetic Monte Carlo simulations of nanoscale compositional patterning during film growth of phase-separated systems

2006 ◽  
Vol 73 (23) ◽  
Author(s):  
J. H. He ◽  
C. A. Carosella ◽  
G. K. Hubler ◽  
S. B. Qadri ◽  
J. A. Sprague
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Film Growth ◽  
Kinetic Monte Carlo ◽  
Kinetic Monte Carlo Simulations

A kinetic Monte Carlo simulation of film growth by physical vapor deposition on rotating substrates

2005 ◽  
Vol 391 (1-2) ◽  
pp. 390-401 ◽  
Author(s):  
J. Cho ◽  
S.G. Terry ◽  
R. LeSar ◽  
C.G. Levi
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Vapor Deposition ◽  
Physical Vapor Deposition ◽  
Film Growth ◽  
Kinetic Monte Carlo ◽  
Kinetic Monte Carlo Simulation

Coarse-grained molecular dynamics modeling of the kinetics of lamellar block copolymer defect annealing

2016 ◽  
Vol 15 (1) ◽  
pp. 013508 ◽  
Author(s):  
Andrew J. Peters ◽  
Richard A. Lawson ◽  
Benjamin D. Nation ◽  
Peter J. Ludovice ◽  
Clifford L. Henderson
Keyword(s):  
Molecular Dynamics ◽  
Block Copolymer ◽  
Coarse Grained ◽  
Dynamics Modeling ◽  
Defect Annealing ◽  
Molecular Dynamics Modeling ◽  
Kinetics Of ◽  
Coarse Grained Molecular Dynamics
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