Diamond CVD Growth Mechanisms and Reaction Rates From First-Principles

2000 ◽  
Vol 616 ◽  
Author(s):  
I.I Oleinik ◽  
D.G. Pettifor ◽  
A.P. Sutton ◽  
C.C. Battaile ◽  
D.J. Srolovitz ◽  
...  
Keyword(s):  
Monte Carlo ◽  
First Principles ◽  
Kinetic Monte Carlo ◽  
Experimental Studies ◽  
Cvd Diamond ◽  
Reaction Rates ◽  
Diamond Growth ◽  
Growth Mechanisms ◽  
Monte Carlo Studies ◽  
Cvd Growth

AbstractCVD diamond is an enabling material for diverse applications. In recent years, multiscale modelling of CVD growth in conjunction with experimental studies of the deposition processes has made a substantial progress towards our understanding of the fundamental growth chemistry and material quality. Macroscopic gas phase simulations of the CVD reactor, the mesoscale kinetic Monte-Carlo (KMC) modelling of the crystal growth and nanoscale modelling of the surface chemistry are three main legs in the multiscale hierarchy. In the framework of this methodology we have performed first-principles quantum mechanical calculations of bonding and reaction kinetics of the elementary growth processes and provided critical input in the form of atomistic growth mechanisms and reaction rates for the mesoscale KMC modelling of CVD diamond growth. A key success was achieved by combining first-principles and Monte Carlo studies to elucidate (100) growth mechanisms that have perplexed the diamond growth community for many years.

scholarly journals Linking ab initio Energetics to Experiment: Kinetic Monte Carlo Simulation of Transient Enhanced Diffusion of B in Si

1998 ◽  
Vol 538 ◽  
Author(s):  
Silva K. Theiss ◽  
M.-J. Caturla ◽  
T. Diaz de la Rubia ◽  
M.C. Johnson ◽  
Ant Uralt ◽  
...  
Keyword(s):  
Experimental Data ◽  
Monte Carlo ◽  
Ab Initio ◽  
Time Scales ◽  
First Principles ◽  
Kinetic Monte Carlo ◽  
Experimental Studies ◽  
Enhanced Diffusion ◽  
Transient Enhanced Diffusion ◽  
Wide Range

AbstractWe have developed a kinetic Monte Carlo (kMC) simulator that links atomic migration and binding energies determined primarily from first principles calculations to macroscopic phenomena and laboratory time scales. Input for the kMC simulation is obtained from a combination of ab initio planewave pseudopotential calculations, molecular dynamics simulations, and experimental data. The simulator is validated against an extensive series of experimental studies of the diffusion of B spikes in self-implanted Si. The implant energy, dose, and dose rate, as well as the detailed thermal history of the sample, are included. Good agreement is obtained with the experimental data for temperatures between 750 and 950°C and times from 15 to 255 s. At 1050°C we predict too little diffusion after 105 s compared to experiment: apparently, some mechanism which is not adequately represented by our model becomes important at this temperature. Below 1050°C, the kMC simulation produces a complete description over macroscopic time scales of the atomic level diffusion and defect reaction phenomena that operate during the anneals. This simulator provides a practical method for predicting technologically interesting phenomena, such as transient enhanced diffusion of B, over a wide range of conditions, using energetics determined from first-principles approaches.

Combined DFT and kinetic Monte Carlo study of a bridging-spillover mechanism on fluorine-decorating graphene

2020 ◽  
Author(s):  
Jing-hua Guo ◽  
Jin-Xiang Liu ◽  
Hongbo Wang ◽  
Haiying Liu ◽  
Gang Chen
Keyword(s):  
Monte Carlo ◽  
First Principles ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Study ◽  
First Principles Calculations ◽  
Graphene Surface

In this work, combining the first-principles calculations with kinetic Monte Carlo (KMC) simulations, we constructed an irregular carbon bridge on the graphene surface and explored the process of H migration...

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.

Atomistic Kinetic Monte Carlo studies of microchemical evolutions driven by diffusion processes under irradiation

2010 ◽  
Vol 406 (1) ◽  
pp. 55-67 ◽  
Author(s):  
F. Soisson ◽  
C.S. Becquart ◽  
N. Castin ◽  
C. Domain ◽  
L. Malerba ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Diffusion Processes ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Studies

CO2 fixation into methanol at Cu/ZrO2 interface from first principles kinetic Monte Carlo

2009 ◽  
Vol 263 (1) ◽  
pp. 114-122 ◽  
Author(s):  
Qian-Lin Tang ◽  
Qi-Jun Hong ◽  
Zhi-Pan Liu
Keyword(s):  
Monte Carlo ◽  
First Principles ◽  
Co2 Fixation ◽  
Kinetic Monte Carlo
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