Tackling Disorder in γ‐Ga2O3. Issue 37 (17th August 2022) - Ratcliff, Laura E.; Oshima, Takayoshi; Nippert, Felix; Janzen, Benjamin M.; Kluth, Elias; Goldhahn, Rüdiger; Feneberg, Martin; Mazzolini, Piero; Bierwagen, Oliver; Wouters, Charlotte; Nofal, Musbah; Albrecht, Martin; et al.
Abstract: Ga2 O3 and its polymorphs are attracting increasing attention. The rich structural space of polymorphic oxide systems such as Ga2 O3 offers potential for electronic structure engineering, which is of particular interest for a range of applications, such as power electronics. γ‐Ga2 O3 presents a particular challenge across synthesis, characterization, and theory due to its inherent disorder and resulting complex structure–electronic‐structure relationship. Here, density functional theory is used in combination with a machine‐learning approach to screen nearly one million potential structures, thereby developing a robust atomistic model of the γ‐phase. Theoretical results are compared with surface and bulk sensitive soft and hard X‐ray photoelectron spectroscopy, X‐ray absorption spectroscopy, spectroscopic ellipsometry, and photoluminescence excitation spectroscopy experiments representative of the occupied and unoccupied states of γ‐Ga2 O3 . The first onset of strong absorption at room temperature is found at 5.1 eV from spectroscopic ellipsometry, which agrees well with the excitation maximum at 5.17 eV obtained by photoluminescence excitation spectroscopy, where the latter shifts to 5.33 eV at 5 K. This work presents a leap forward in the treatment of complex, disordered oxides and is a crucial step toward exploring how their electronic structure can be understood in terms of local coordination and overall structure. Abstract : Gallium oxide (Ga2 O3 ) is attracting increasing attention in applications such as power electronics and photodetectors due to its rich structural space and resulting electronic structure. This work explores the influence of structural disorder on a range of crucial material parameters of γ‐phase Ga2 O3 by combining density functional theory and machine learning with a range of experimental probes.