Atomistic Monte Carlo simulations of three-dimensional polycrystalline thin films

Rubio, J. E.; Jaraı́z, M.; Martín-Bragado, Ignacio; Hernandez-Mangas, J. M.; Barbolla, J.; Gilmer, George H.

doi:10.1063/1.1577814

Cited by 23 publications

(13 citation statements)

References 14 publications

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“…Although this method allows for different grain orientations, the simulated films were at most one monolayer thick. Based on a similar approach, Rubio et al 47 were able to grow comparatively larger films, but still less than 50 monolayers in thickness. Huang and Zhou 46 proposed an improved method called memoryefficient algorithm to map multiple lattices onto a single lattice; still, however, only films less than 100 monolayers thick could be simulated.…”

Section: Plasma Enhanced Chemical Vapor Deposition (Pecvd)mentioning

confidence: 98%

A hybrid kinetic Monte Carlo method for simulating silicon films grown by plasma-enhanced chemical vapor deposition

Tsalikis

Baig

Mavrantzas

et al. 2013

The Journal of Chemical Physics

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We present a powerful kinetic Monte Carlo (KMC) algorithm that allows one to simulate the growth of nanocrystalline silicon by plasma enhanced chemical vapor deposition (PECVD) for film thicknesses as large as several hundreds of monolayers. Our method combines a standard n-fold KMC algorithm with an efficient Markovian random walk scheme accounting for the surface diffusive processes of the species involved in PECVD. These processes are extremely fast compared to chemical reactions, thus in a brute application of the KMC method more than 99% of the computational time is spent in monitoring them. Our method decouples the treatment of these events from the rest of the reactions in a systematic way, thereby dramatically increasing the efficiency of the corresponding KMC algorithm. It is also making use of a very rich kinetic model which includes 5 species (H, SiH 3 , SiH 2 , SiH, and Si 2 H 5 ) that participate in 29 reactions. We have applied the new method in simulations of silicon growth under several conditions (in particular, silane fraction in the gas mixture), including those usually realized in actual PECVD technologies. This has allowed us to directly compare against available experimental data for the growth rate, the mesoscale morphology, and the chemical composition of the deposited film as a function of dilution ratio. © 2013 AIP Publishing LLC. [http://dx

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Section: Plasma Enhanced Chemical Vapor Deposition (Pecvd)mentioning

confidence: 98%

A hybrid kinetic Monte Carlo method for simulating silicon films grown by plasma-enhanced chemical vapor deposition

Tsalikis

Baig

Mavrantzas

et al. 2013

The Journal of Chemical Physics

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“…The initial islands have an important role in determining the initial orientations and density of the grains in the polycrystalline film [37]. Our purpose is to explore the influence of materials properties and processing conditions on cluster morphology.…”

Section: Nucleation Of Films On Foreign Substratesmentioning

confidence: 99%

Monte Carlo Simulations of Crystal Growth

Zepeda-Ruiz

Gilmer

2015

Handbook of Crystal Growth

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“…[18][19][20][21][22][23][24][25][26][27] Among these models, the most realistic ones incorporate vacancy and void formation but only consider the growth of a single crystal. [28][29][30][31] Bruschi and co-workers 28 used a quasicontinuous coordinate system, such that the simulated film was represented by a two-dimensional array of square cells with the exact positions of the atoms within each cell represented by a continuous x-y coordinate system. However, this approach is computationally expensive and has not been successful at simulating film growth over a reasonable time scale.…”

Section: Introductionmentioning

confidence: 99%

“…[19][20][21][22] One approach to extend this method to the growth of polycrystalline films is to use multiple lattices to represent different grain orientations. Using similar concepts as Bruschi et al, Rubio et al 30 restricted the positions within each cell to those commensurate with ten possible sublattices. [28][29][30][31] Bruschi and co-workers 28 used a quasicontinuous coordinate system, such that the simulated film was represented by a two-dimensional array of square cells with the exact positions of the atoms within each cell represented by a continuous x-y coordinate system.…”

Section: Introductionmentioning

confidence: 99%

Kinetic Monte Carlo simulations of nanocrystalline film deposition

Ruan

Schuh

2010

Journal of Applied Physics

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Simulations of chemical vapor deposition diamond film growth using a kinetic Monte Carlo model and twodimensional models of microwave plasma and hot filament chemical vapor deposition reactors A full diffusion kinetic Monte Carlo algorithm is used to model nanocrystalline film deposition, and study the mechanisms of grain nucleation and microstructure formation in such films. The major finding of this work is that new grain nucleation occurs predominantly on surface peaks. Consequently, development of a nanocrystalline structure is promoted by a growth surface with nanoscale roughness, on which new grains can nucleate and grow separately from one another. The grain minor dimension ͑in the plane of the film͒ is primarily dictated by surface peak spacing, which in turn is reduced at low temperatures and high deposition rates. The grain major dimension ͑in the growth direction͒ is related to the probability of nucleating new grains on top of pre-existing ones, with finer grains being formed at low temperatures and low grain boundary energies. Because vacancies kinetically pin grain boundaries, high vacancy content, which is obtained at high deposition rate, also favors nanograins. Consistent with empirical observations common in the experimental literature, it is found that as grains shrink, they transition from elongated to equiaxed.

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Atomistic Monte Carlo simulations of three-dimensional polycrystalline thin films

Abstract: Large crystal grain niobium thin films deposited by energetic condensation in vacuum arc

Cited by 23 publications

References 14 publications

A hybrid kinetic Monte Carlo method for simulating silicon films grown by plasma-enhanced chemical vapor deposition

A hybrid kinetic Monte Carlo method for simulating silicon films grown by plasma-enhanced chemical vapor deposition

Monte Carlo Simulations of Crystal Growth

Kinetic Monte Carlo simulations of nanocrystalline film deposition

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