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Condensed Matter > Materials Science

arXiv:2607.24871 (cond-mat)
[Submitted on 27 Jul 2026]

Title:A flexible kinetic Monte Carlo framework for GaN molecular beam epitaxy with adaptive on-the-fly barrier evaluation

Authors:Sajid Ali, Norbert Krause, Carla Verdi
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Abstract:We present a lattice-based kinetic Monte Carlo (KMC) framework for simulating GaN(0001) growth by molecular beam epitaxy. The framework captures the key microscopic processes governing epitaxial growth, including temperature-dependent surface diffusion, flux-driven deposition, Ehrlich--Schwoebel (ES) step-edge barriers, Ostwald ripening, and species-specific desorption, within a scalable architecture that enables systematic exploration of experimentally relevant growth conditions. In addition to predefined activation-energy catalogs, the framework supports adaptive on-the-fly barrier evaluation using machine-learned interatomic potentials. When previously unencountered local atomic configurations arise, activation barriers are computed via nudged elastic band, potential energy scans, or Brønsted--Evans--Polanyi methods, and cached for reuse. Predefined-barrier simulations reproduce compact triangular island formation, and further capture Ostwald ripening during growth interruptions and ES barrier-induced multilayer nucleation. At elevated temperatures, desorption drives an island ``walking'' regime, in which N--Ga exchange generates weakly bound Ga adatoms (AdGa) at trailing edges; preferential desorption of AdGa leads to asymmetric edge retreat and net island translation. Our KMC framework provides a flexible platform for predictive simulations of GaN epitaxy at the atomic scale and, more broadly, non-equilibrium growth of compound semiconductors.
Subjects: Materials Science (cond-mat.mtrl-sci)
Cite as: arXiv:2607.24871 [cond-mat.mtrl-sci]
  (or arXiv:2607.24871v1 [cond-mat.mtrl-sci] for this version)
  https://doi.org/10.48550/arXiv.2607.24871
arXiv-issued DOI via DataCite
Journal reference: Applied Surface Science, 2026
Related DOI: https://doi.org/10.1016/j.apsusc.2026.167867
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From: Ali Sajid [view email]
[v1] Mon, 27 Jul 2026 00:02:25 UTC (10,016 KB)
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