Local characterization and current–voltage modelling of conductive threading dislocations in AlGaN/GaN heterostructures grown on Si(111) and engineered poly-AlN substrates
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Abstract
Abstract AlGaN/GaN based high-electron-mobility transistors utilize the excellent electronic and transport properties of Gallium Nitride and related compounds, making them highly sought after for high-power and high-frequency applications. However, threading dislocations that form during the GaN epitaxy growth on lattice mismatched Si substrates impact the device performance and reliability by causing an early breakdown and carrier trapping phenomena. For applications exceeding 1 kV, the growth of thick GaN stacks on 200 mm Si wafers introduces significant strain, compromising substrate integrity. This has triggered the development of engineered substrates for GaN epitaxy and the re-evaluation of the subsequent epitaxial growth. In this study, we have investigated the current transport properties of detrimental dislocations in AlGaN/GaN heterostructures grown on AlN engineered substrates (commonly referred to as QST®) and on conventional Si (111) substrates. This study has been achieved by developing a correlative nanoscale characterization methodology implementing conductive atomic force microscopy, cathodoluminescence microscopy, and electron channelling contrast imaging and revisiting dislocation-sensitive etching behaviour. This allowed us to observe vertical conduction paths manifesting themselves only in certain types of dislocations and to analyse the associated current transport mechanisms. Our modelling of the local current–voltage characterization on such dislocations, which are only 1% of the total dislocation density, directly associate them to the conduction mechanism via Poole–Frenkel emission in the reverse bias and variable range hopping in the forward bias.
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Research context
OpenAlex topics: GaN-based semiconductor devices and materials · Ga2O3 and related materials · Nanowire Synthesis and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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