(28c) Molecular Dynamics Simulation of Ge Deposition and Islanding on Amorphous Silica Substrates | AIChE

(28c) Molecular Dynamics Simulation of Ge Deposition and Islanding on Amorphous Silica Substrates

Authors 

Sinno, T. - Presenter, University of Pennsylvania
Chuang, C. Y. - Presenter, University of Pennsylvania
Han, S. - Presenter, University of New Mexico
Zepeda-Ruiz, L. A. - Presenter, Lawrence Livermore National Laboratory

Selective epitaxial growth (SEG) of Ge on Si substrates has proven to be a versatile pathway for producing Ge substrates to enable III-V device integration on Si.  However, persistent problems remain, including dislocation formation and high stresses due to lattice parameter and thermal expansion coefficient mismatches between Si and Ge.  Further optimization of the SEG process may be significantly assisted by atomistic simulation.  Here, we present an atomistic analysis of Ge deposition on SiO2.  We begin by describing a validation process for a Tersoff-based model for the ternary Si-Ge-O system [1,2], in which we compare simulation predictions to detailed experimental data [3,4] for bulk SiO2 structural parameters, Si-SiO2 and Ge-SiO2 interface energies, and the Ge-on-SiO2 desorption energy. 

Using this validated interatomic potential, Ge deposition and islanding on an amorphous SiO2 surface was studied with direct molecular dynamics and the results compared to experimental measurements [4].  These quantitative comparisons were enabled by using an analytical rate model as a bridge between simulations and experiments, which are necessarily performed at deposition fluxes that are different by many orders of magnitude.  The simulations are shown to provide accurate predictions of the island critical size and the scaling of island density as a function of temperature.  Finally, we present some recent efforts at accelerating molecular dynamics simulations with “equation-free” coarse projective integration [5].  Here, coarse measures of the island size distribution dynamics are obtained from short molecular dynamics simulations and then used to evolve numerically the size distribution over large time intervals.  In particular, we show that the reconstruction of atomic configurations from size distribution moments represents the key challenge in deposition simulations and we propose approaches for achieving this in a computationally tractable manner.

[1] J. Tersoff, Phys. Rev. B 39, 5566 (1989).

[2] S. Munetoh, T. Motooka, K. Moriguchi and A. Shintani, Comput. Mater. Sci 39, 334 (2007).

[3] Q. Li, J. L. Krauss, S. Hersee, and S. M. Han, J. Phys. Chem. C 111, 779 (2007).

[4] D. Leonhardt and S. M. Han, Surf. Sci. 603, 2624 (2009).

[5] M.E. Kavousanakis, R. Erban, A.G. Boudouvis, C.W. Gear, I.G. Kevrekidis, J. Comput. Phys. 225 (2007) 382-407.