Computational Investigation of Selective Movpe of AlXGa1-XAs in Presence of Hcl

2001 ◽  
Vol 696 ◽  
Author(s):  
Maria Nemirovskaya ◽  
Carlo Cavallotti ◽  
Klavs Jensen
Keyword(s):  
Fluid Dynamics ◽  
Monte Carlo ◽  
Transition State ◽  
Gas Phase ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Model ◽  
Operating Conditions ◽  
Morphology Evolution ◽  
Computational Investigation ◽  
Dynamics Simulations

AbstractThe deposition of AlGaAs in the presence of HCl was investigated at the macroscopic and mesoscopic scales. Fluid dynamics simulations were first performed in order to study the dependence of the deposition rate on the operating conditions. Unknown gas phase and surface kinetic parameters were estimated by quantum chemistry and transition state computations. The fluxes of all species to the surface were thus computed and provided the input to a kinetic Monte Carlo model used to investigate the morphology evolution of the film.

Computational Investigation of Selective MOVPE of AlxGa1-xAs in Presence of Hcl

2001 ◽  
Vol 701 ◽  
Author(s):  
Maria Nemirovskaya ◽  
Carlo Cavallotti ◽  
Klavs Jensen
Keyword(s):  
Fluid Dynamics ◽  
Monte Carlo ◽  
Transition State ◽  
Gas Phase ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Model ◽  
Operating Conditions ◽  
Morphology Evolution ◽  
Computational Investigation ◽  
Dynamics Simulations

ABSTRACTThe deposition of AlGaAs in the presence of HCl was investigated at the macroscopic and mesoscopic scales. Fluid dynamics simulations were first performed in order to study the dependence of the deposition rate on the operating conditions. Unknown gas phase and surface kinetic parameters were estimated by quantum chemistry and transition state computations. The fluxes of all species to the surface were thus computed and provided the input to a kinetic Monte Carlo model used to investigate the morphology evolution of the film.

A kinetic Monte Carlo Model of Silicon CVD Growth from a Mixed H2/siH4 Gas Source

1999 ◽  
Vol 584 ◽  
Author(s):  
M. Fearn ◽  
M. Sayed ◽  
J. H. Jefferson ◽  
D. J. Robbins
Keyword(s):  
Experimental Data ◽  
Growth Rate ◽  
Monte Carlo ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Model ◽  
Hydrogen Desorption ◽  
Time Step ◽  
Cvd Growth ◽  
Step Algorithm ◽  
Dynamics Simulations

AbstractWe report the development of an atomistic scale Kinetic Monte Carlo model of silicon CVD growth. By employing a variable time step algorithm, simulations have been performed over a range of time scales, enabling direct comparison with experimental data. The validity of using the kinetic theory of gases for evaluating steady state incoming particle fluxes within the model is demonstrated by comparison with computational fluid dynamics simulations. The model is applied to study hydrogen desorption rates from Si(001) and the dependence of silicon growth rate on substrate temperature, with results found to be in good agreement with experimental data. An experimentally observed decrease of growth rate with increasing H2 partial pressure is also reproduced by the model and shown to be caused by a decrease in silane adsorption on a hydrogen-rich surface.

Kinetic Monte Carlo Model for Gas Phase Diffusion in Nanoscopic Systems

2018 ◽  
Vol 122 (21) ◽  
pp. 11524-11531 ◽  
Author(s):  
Elisabeth M. Dietze ◽  
Philipp N. Plessow
Keyword(s):  
Monte Carlo ◽  
Gas Phase ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Model ◽  
Phase Diffusion

Defect diffusion in hcp Zirconium: A kinetic Monte Carlo approach

2003 ◽  
Vol 792 ◽  
Author(s):  
C. Arévalo ◽  
M.J. Caturla ◽  
J.M. Perlado
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Model ◽  
Average Cluster Size ◽  
Fixed Temperature ◽  
Molecular Dynamics Calculations ◽  
Dynamics Simulations ◽  
Average Cluster ◽  
Cascade Damage

ABSTRACTWe have studied diffusion of defects produced during irradiation in hcp zirconium through a kinetic Monte Carlo model. The input data for these simulations is based on molecular dynamics calculations and from experiments whenever available. The initial cascade damage produced by recoils of 25 keV energy from molecular dynamics simulations has been followed for times of hours at a fixed temperature of 600K. We have calculated the number of freely migrating defects, the recombination ratio between vacancies and interstitials, the defects surviving in the bulk as well as the average cluster size for these remaining defects.

Kinetic Monte Carlo Method

2006 ◽  
Author(s):  
Vasily Bulatov ◽  
Wei Cai
Keyword(s):  
Monte Carlo ◽  
Kinetic Monte Carlo ◽  
Dislocation Core ◽  
Dislocation Motion ◽  
Coarse Grained ◽  
Solid Thin Films ◽  
Finite Set ◽  
And Migration ◽  
Dynamics Simulations ◽  
Straight Segments

The PN model discussed in the preceding chapter is a continuum approach that requires some atomistic input to account for non-linear interactions in the dislocation core. In this chapter, we introduce yet another continuum model that uses atomistic input for a different purpose. The kinetic Monte Carlo (kMC) model does not consider any details of the core structure but instead focuses on dislocation motion on length and time scales far greater than those of the atomistic simulations. The model is especially effective for diamond-cubic semiconductors and other materials in which dislocation motion is too slow to be observed on the time scale of molecular dynamics simulations. The key idea of the kMC approach is to treat dislocation motion as a stochastic sequence of discrete rare events whose mechanisms and rates are computed within the framework of the transition state theory. Built around its unit mechanisms, the kMC model simulates dislocation motion and predicts dislocation velocity as a function of stress and temperature. This data then can be used to construct accurate mobility functions for dislocation dynamics simulations on still larger scales (Chapter 10). In this sense, kMC serves as a link between atomistic models and coarse-grained continuum models of dislocations. The kMC approach is most useful in situations where the system evolves through a stochastic sequence of events with only a few possible event types. The method has been used in a wide variety of applications other than dislocations. For example, the growth of solid thin films from vapor or in solution is known to proceed through attachment and diffusion of adatoms deposited on the surface. Based on a finite set of unit mechanisms of the motion of adatoms, kMC models accurately describe the kinetics of growth and the resulting morphology evolution of the epitaxial films [95, 96, 97]. Similar kMC models have been applied to dislocation motion in crystals with high lattice resistance, such as silicon. In these materials, dislocations consist of long straight segments interspersed with atomic-sized kinks, depicted schematically in Fig. 9.1(a) as short vertical segments. As was explained in Section 1.3, dislocation motion proceeds through nucleation and migration of kink pairs and can be described well by a kMC model.

Kinetic Monte Carlo model for the COVID-19 epidemic: Impact of mobility restriction on a COVID-19 outbreak

2020 ◽  
Vol 102 (3) ◽  
Author(s):  
Leonardo Evaristo de Sousa ◽  
Pedro Henrique de Oliveira Neto ◽  
Demetrio Antônio da Silva Filho
Keyword(s):  
Monte Carlo ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Model

scholarly journals A new methodology to calculate process rates in a kinetic Monte Carlo model of PAH growth

2019 ◽  
Vol 209 ◽  
pp. 133-143 ◽  
Author(s):  
Gustavo Leon ◽  
Nick Eaves ◽  
Jethro Akroyd ◽  
Sebastian Mosbach ◽  
Markus Kraft
Keyword(s):  
Monte Carlo ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Model
Sign in / Sign up

Export Citation Format

Share Document