研究目的
To visualize layers with different concentrations of carriers activated by Si in n-type GaN semiconductors using phase-shifting electron holography (PS-EH) and to estimate the thicknesses of the active and inactive layers at each dopant level.
研究成果
PS-EH with multiple biprisms was successfully applied to visualize different dopant concentrations in n-GaN semiconductor materials. All layers in a 350-nm-thick TEM sample were clearly distinguished with enough spatial resolution and phase resolution. A thicker TEM sample (by more than about 700 nm) is necessary to distinguish much lower concentrations, such as 1016 and 1015 atoms cm?3 layers.
研究不足
The ratio of active-layer thickness to total thickness of the TEM sample significantly decreases as dopant concentration decreases, making it necessary to use a thicker TEM sample to visualize lower carrier concentrations. The exact thicknesses might be changed by varying FIB milling conditions.
1:Experimental Design and Method Selection
Phase-shifting electron holography (PS-EH) was applied using a transmission electron microscope (TEM) with three electron biprisms to obtain high-contrast holograms without Fresnel fringes. A cryo-focused-ion-beam (cryo-FIB) was used to prepare a uniform TEM sample.
2:Sample Selection and Data Sources
A model sample composed of n-type GaN (n-GaN) layers with different concentrations of Si dopants was prepared by metal-organic chemical-vapor deposition.
3:List of Experimental Equipment and Materials
300-kV holography TEM (Hitachi High-Technologies, HF3300-EH), 4 k × 4 k CCD camera (Gatan, US4000), cryo-FIB (Hitachi High-Technologies, NB-5000).
4:Experimental Procedures and Operational Workflow
A series of holograms with interference fringes shifted one after another was used for the phase-reconstruction procedure by PS-EH. The fringes were shifted by tilting the incident electron waves. The phase value was obtained pixel by pixel from the holograms.
5:Data Analysis Methods
The phase value in each pixel was retrieved from a cosinusoidal fitting curve of the intensity variation. The fitting curve was calculated by a least-squares method.
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