In this thesis, a scanning electron microscope (SEM) based technique known as electron backscatter diffraction (EBSD) is utilised and developed to investigate types of
crystalline defects known as threading dislocations (TDs) in the III-nitride semiconductor gallium nitride (GaN). GaN is used prolifically in electronic and optoelectronic
devices such as in high electron mobility transistors (HEMTs) and light-emitting diodes
(LEDs). However, the high densities of TDs in GaN limits device performance by reducing electron mobility due to their associated strain and scattering effects, causing
non-radiative recombination, and inducing local bandgap variations across the semiconductor. TDs in GaN are most commonly edge, screw, and mixed TDs. Each of
these types has its own unique associated strain and misorientation profile that can
affect the semiconductor’s structure, and also its (opto)electronic properties.
The first step in analysing these defects within GaN is to obtain high-quality images of their distributions near to the surface of the semiconductor. By doing so it is
possible to calculate TD densities (TDDs) and, if the imaging conditions are correct
such that surface steps are also visible, identify which TDs are edge type or have screw
component. This was achieved through the development of the virtual diode centre
of mass (VDCOM) imaging technique. This is a post-processing technique applied to
EBSD datasets that produces high signal images of the same area with different dominant contrast mechanisms- either crystallographically dominated (showing TDs) or
topographically dominated (showing surface steps and TDs)- by monitoring changes in
signal within different regions of the EBSD detector. By utilising the pixelated EBSD
detector in this way, there is much greater flexibility in the different images that can be
acquired with only one dataset, versus the more traditional SEM imaging technique of electron channelling contrast imaging (ECCI) which uses individual hardware diodes.
Next, the strain and misorientation (lattice rotations) associated with TDs were
simulated using an analytical simulation written in Python. It was found that the misorientation and strain associated with a screw TD is significant both in-plane (around
the specimen z axis) and out-of-plane, while that of the edge TD is significant for
current EBSD measurements only in-plane. This indicated that if the misorientation
and strain profiles could be measured and mapped with sufficient resolution, then by
comparing in-plane and out-of-plane strain and misorientation, it would be possible to
distinguish between edge TDs and screw component TDs (screw and mixed) in GaN.
Strain and misorientation maps were then produced using EBSD with sufficient
resolution to resolve individual TDs. This allowed the overall subgrain structure to
be qualitatively interrogated and also for the TDs to be correctly identified as screwcomponent or edge TDs. In combination with the VDCOM technique, this means that
TDs were identified and their densities calculated for a range of GaN samples. The
mapping of relative strain and misorientation with such a high resolution also provides
a mechanism to visualise how the strain and misorientation due to TDs varies across a
particular GaN sample.
Another post-processing imaging modality was developed using Radon transformations, Radon centre of mass (RCOM) imaging. This allows EBSD users to image using
the distortion of a particular crystal plane to provide contrast, much like in transmission electron microscopy (TEM). This means that only TDs affecting a particular plane
are imaged, and when utilising particular invisibility criteria, the TD types can then be
identified. For plan-view measurements however, this technique is limited by surface
relaxation, and so full identification would require cross-sectional EBSD.
Date of Award | 4 Mar 2025 |
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Original language | English |
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Awarding Institution | - University Of Strathclyde
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Sponsors | EPSRC (Engineering and Physical Sciences Research Council) |
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Supervisor | Carol Trager-Cowan (Supervisor) & Jochen Bruckbauer (Supervisor) |
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