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【Epitaxy Papers】Homoepitaxial growth of (100) Si-doped β-Ga₂O₃ films via MOCVD using TMGa: Effects of growth temperature and oxygen flow rate

日期:2026-03-16阅读:15

      Researchers from the Sun Yat-Sen University have published a dissertation titled "Homoepitaxial growth of (100) Si-doped β-Ga2O3 films via MOCVD using TMGa: Effects of growth temperature and oxygen flow rate" in Semiconductor Science and Technology.

Abstract

      The homoepitaxy of (100) β-Ga2O3 via metal-organic chemical vapor deposition (MOCVD) was investigated using trimethylgallium (TMGa) as the gallium source. The study systematically examines how growth temperature and oxygen flow rate affect surface morphology and electrical properties. Growth temperature plays a crucial role in controlling gallium adatom diffusion length, while lower oxygen flow rates also promote gallium diffusion. At high temperatures, step bunching occurs, characterized by periodic mesas and local step flow. As the temperature increases, the density of mesas rises, and atomic steps merge, leading to a fully step-bunched morphology. At 895 °C, optimizing the oxygen flow produces an atomically smooth surface with a root-mean-square roughness of 0.71 nm. Hall effect and secondary ion mass spectrometry (SIMS) analyses reveal that higher growth temperatures and oxygen flow rates suppress carbon impurities, thereby enhancing electrical performance. However, excessive temperatures cause magnesium diffusion from the substrate, which compensates the n-type dopants, and excessive oxygen flow induces the formation of parasitic particles, both of which degrade electrical properties. The optimal conditions identified are 925 °C and 5000 sccm oxygen flow, achieving a room-temperature mobility of 103 cm2/V·s and an electron concentration of 1.17 × 1018 cm−3. A 4.8-μm-thick film with excellent transport properties was successfully produced. This research offers valuable insights into the MOCVD growth process of (100) β-Ga2O3 using TMGa, successfully achieving process optimization and precursor validation.

 

DOI:

https://doi.org/10.1088/1361-6641/ae4d7d