| AVS 65th International Symposium & Exhibition | |
| Thin Films Division | Thursday Sessions |
| Session TF+AS+EL+PS-ThM |
| Session: | In-situ Characterization and Modeling of Thin Film Processes |
| Presenter: | ShreeRam Acharya, University of Central Florida |
| Authors: | S.R. Acharya, University of Central Florida T.S. Rahman, University of Central Florida |
| Correspondent: | Click to Email |
The Self-Learning Kinetic Monte Carlo (SLKMC) method [1] with a pattern recognition [2] and a diffusion path finder scheme enables collection of a large database of diffusion processes including single- and multiple-atoms, and concerted island motion and their energetics. The databases collected from adatom-island (2-8 atoms) diffusion characteristics for a large set of homo- and hetero-epitaxial metallic systems (Cu, Ni, Pd and Ag) are used to extract a set of easily accessible features, geometrical and energetic, using physical insight which are then encoded. Those features along with activation energy barrier are used to train and test linear and non-linear statistical models. A non-linear model developed based on neural network technique predicts the diffusion energy barriers with high correlation with the calculated ones. In this talk, we present the results of kinetics study of these homo or hetero-epitaxial metallic systems some of whose barriers are used for training of the model and are compared to the corresponding quantities obtained from KMC simulation using energy barriers calculated from computationally intensive interatomic interaction potential based approach.
[1] O. Trushin, et al., Phys. Rev. B72, 115401 (2005).
[2] S.I. Shah, et al., J. Phys.: Condens. Matt.24, 354004 (2012).
Work supported in part by MMN-1710306.