Kinetic Monte Carlo simulations of self-organization of Ge islands on Si(001)

Literature Information

Publication Date 2021-08-09
DOI 10.1039/D1CP00069A
Impact Factor 3.676
Authors

Paramita Ghosh, Nidhi Gupta, Monika Dhankhar, Madhav Ranganathan


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Abstract

The self-organization of germanium islands on a silicon(001) substrate is studied using lattice-based kinetic Monte Carlo simulations. These islands form spontaneously via the Stranski–Krastanov mode during growth. The interplay of deposition flux and competing surface diffusion leads to a size and shape distribution of islands that varies with temperature and coverage. For the simulation parameters chosen, a kinetic regime of irreversible growth is observed at 500 K, and this changes to quasi-equilibrium growth at 600 K. At 550 K, we see that the surface roughness increases abruptly from a low value and crosses the roughness curve at 600 K. This behavior is explained on the basis of a change in the island formation mechanism. At 500 K, the island formation involves a nucleation barrier; whereas at 600 K this barrier is almost nonexistent. At an intermediate temperature, the stochastic effects due to the incoming flux initially slow down island growth, but the subsequent island nucleation rapidly increases the roughness. These results illustrate how island self-assembly is affected by mechanistic in addition to kinetic and energetic effects. Our results are discussed in the context of experiments on a Si–Ge system and show how the kMC models can be used to understand the processes in heteroepitaxial growth.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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