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, AIP Publishing, May, 2021. doi abstract bibtex 1 download 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 = "AIP Publishing",
volume = 129,
number = 19,
pages = "195304",
month = may,
year = 2021,
keywords = "LeBeau Group;AFOSR;All papers",
language = "en",
issn = "0021-8979, 1089-7550",
doi = "10.1063/5.0048820"
}
Downloads: 1
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L"],"bibdata":{"bibtype":"article","type":"article","title":"Native oxide reconstructions on AlN and GaN (0001) surfaces","author":[{"propositions":[],"lastnames":["Mirrielees"],"firstnames":["Kelsey","J"],"suffixes":[]},{"propositions":[],"lastnames":["Dycus"],"firstnames":["J","Houston"],"suffixes":[]},{"propositions":[],"lastnames":["Baker"],"firstnames":["Jonathon","N"],"suffixes":[]},{"propositions":[],"lastnames":["Reddy"],"firstnames":["Pramod"],"suffixes":[]},{"propositions":[],"lastnames":["Collazo"],"firstnames":["Ramón"],"suffixes":[]},{"propositions":[],"lastnames":["Sitar"],"firstnames":["Zlatko"],"suffixes":[]},{"propositions":[],"lastnames":["LeBeau"],"firstnames":["James","M"],"suffixes":[]},{"propositions":[],"lastnames":["Irving"],"firstnames":["Douglas","L"],"suffixes":[]}],"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. 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Since there are many possible\n reconstructions for each surface, it is a challenge to identify\n the relevant surface reconstructions in advance of a detailed\n simulation. Because of this, different approaches are often\n employed to down select initial structures to reduce the\n computational load. These approaches usually rely on either\n electron counting rules or oxide stoichiometry, as both of these\n models tend to lead to structures that are energetically\n favorable. Here we explore models from these approaches but also\n explore a reconstruction of the (0001) surface directly observed\n using scanning transmission electron microscopy with predictive\n density functional theory simulations. Two compositions of the\n observed surface reconstruction---one which obeys oxide\n stoichiometry and one which is cation deficient and obeys\n electron counting---are compared to reconstructions from the\n previous work. 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