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DFT based kinetic Monte Carlo study of metal surface Growth: Comparison of a restricted and an unrestricted diffusion model.
- Source :
-
Computational Materials Science . Jan2024, Vol. 231, pN.PAG-N.PAG. 1p. - Publication Year :
- 2024
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Abstract
- [Display omitted] • Deposition rate affects roughness, activation barrier influences. • Unrestricted diffusion model leads to higher roughness. • Temperature smooth surfaces, alters growth mechanisms. • Higher temperatures increase layer occupancy, favor diffusion. • Steady state is not reached for any materials in unrestricted model. • Dynamic exponent Beta depends of the diffusion mechanism. The growth behavior of Cr and W surfaces using kinetic Monte Carlo (KMC) simulations based on Density-Functional Theory (DFT) is presented in this study. Three models, a growth model with random deposition and no diffusion, a growth model with restricted diffusion and a growth model with unrestricted diffusion model, were compared to understand their influence on the predicted surface roughness and layer density. The impact of deposition rate and temperature on surface growth for both metals were analyzed. For deposition rate studies, five different rates (0.01 ML/s, 0.1 ML/s, 1.0 ML/s, 10.0 ML/s, and 100 ML/s) were considered at 550 K for Cr and W respectively. The effect of temperature on roughness was also studied employing various temperatures from 300 K to 1100 K for both metals and under the two different evolution models. The results show that the unrestricted diffusion model exhibits higher roughness compared to the restricted model for both metals. The restricted model shows a stable region of roughness, whereas the unrestricted model shows a continuous increase in roughness throughout the simulation. Furthermore, layer density analysis revealed that temperature affects the filling of lower monolayers. Finally, dynamic exponents β and α for each studied model were calculated and discussed. The results highlight the influence of diffusion models, deposition rate and temperature on surface, roughness, and layer density. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09270256
- Volume :
- 231
- Database :
- Academic Search Index
- Journal :
- Computational Materials Science
- Publication Type :
- Academic Journal
- Accession number :
- 173519699
- Full Text :
- https://doi.org/10.1016/j.commatsci.2023.112546