Native oxide reconstructions on AlN and GaN (0001) surfaces. Mirrielees, K. J, Dycus, J H., Baker, J. N, Reddy, P., Collazo, R., Sitar, Z., LeBeau, J. M, & Irving, D. L J. Appl. Phys., 129(19):195304, American Institute of Physics Inc., May, 2021.
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Properties of AlN/GaN surfaces are important for realizing the tunability of devices, as the presence of surface states contributes to Fermi level pinning. This pinning can influence the performance of high electron mobility transistors and is also important for passivation of the surface when developing high-power electronic devices. It is widely understood that both AlN and GaN surfaces oxidize. Since there are many possible reconstructions for each surface, it is a challenge to identify the relevant surface reconstructions in advance of a detailed simulation. Because of this, different approaches are often employed to down select initial structures to reduce the computational load. These approaches usually rely on either electron counting rules or oxide stoichiometry, as both of these models tend to lead to structures that are energetically favorable. Here we explore models from these approaches but also explore a reconstruction of the (0001) surface directly observed using scanning transmission electron microscopy with predictive density functional theory simulations. Two compositions of the observed surface reconstruction - one which obeys oxide stoichiometry and one which is cation deficient and obeys electron counting - are compared to reconstructions from the previous work. Furthermore, surface states are directly calculated using hybrid exchange-correlation functionals that correct for the underestimation of the bandgaps in AlN and GaN and improve the predicted positions of surface states within the gap. It is found that cation deficiency in the observed reconstruction yields surface states consistent with the experiment. Based on all of these results, we provide insight into the observed properties of oxidized AlGaN surfaces.
@ARTICLE{Mirrielees2021-ur,
  title     = "Native oxide reconstructions on {AlN} and {GaN} (0001) surfaces",
  author    = "Mirrielees, Kelsey J and Dycus, J Houston and Baker, Jonathon N
               and Reddy, Pramod and Collazo, Ram{\'o}n and Sitar, Zlatko and
               LeBeau, James M and Irving, Douglas L",
  abstract  = "Properties of AlN/GaN surfaces are important for realizing the
               tunability of devices, as the presence of surface states
               contributes to Fermi level pinning. This pinning can influence
               the performance of high electron mobility transistors and is
               also important for passivation of the surface when developing
               high-power electronic devices. It is widely understood that both
               AlN and GaN surfaces oxidize. Since there are many possible
               reconstructions for each surface, it is a challenge to identify
               the relevant surface reconstructions in advance of a detailed
               simulation. Because of this, different approaches are often
               employed to down select initial structures to reduce the
               computational load. These approaches usually rely on either
               electron counting rules or oxide stoichiometry, as both of these
               models tend to lead to structures that are energetically
               favorable. Here we explore models from these approaches but also
               explore a reconstruction of the (0001) surface directly observed
               using scanning transmission electron microscopy with predictive
               density functional theory simulations. Two compositions of the
               observed surface reconstruction - one which obeys oxide
               stoichiometry and one which is cation deficient and obeys
               electron counting - are compared to reconstructions from the
               previous work. Furthermore, surface states are directly
               calculated using hybrid exchange-correlation functionals that
               correct for the underestimation of the bandgaps in AlN and GaN
               and improve the predicted positions of surface states within the
               gap. It is found that cation deficiency in the observed
               reconstruction yields surface states consistent with the
               experiment. Based on all of these results, we provide insight
               into the observed properties of oxidized AlGaN surfaces.",
  journal   = "J. Appl. Phys.",
  publisher = "American Institute of Physics Inc.",
  volume    =  129,
  number    =  19,
  pages     = "195304",
  month     =  may,
  year      =  2021,
  keywords  = "LeBeau Group;AFOSR",
  issn      = "0021-8979",
  doi       = "10.1063/5.0048820"
}

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