Quantitative Scanning Transmission Electron Microscopy for III-V Semiconductor Heterostructures Utilizing Multi-Slice Image Simulations
Quantitative STEM can satisfy the demand of modern semiconductor device development for atomically resolved structural information. Thereby, quantitative evaluations can be based on STEM intensities only, a combination of STEM intensities with different methods or a comparison of STEM intensities to...
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|Quantitative STEM can satisfy the demand of modern semiconductor device development for atomically resolved structural information. Thereby, quantitative evaluations can be based on STEM intensities only, a combination of STEM intensities with different methods or a comparison of STEM intensities to image simulations.
Based on STEM intensities only, quantitative evaluations of the “W”-QWH are conducted and reveal information about its structure. Simplistic one-dimensional layer-by-layer concentration profiles can be assigned through a combination with concentration results from XRD that do not provide layer-by-layer information.
However, the composition can be determined more accurately, i.e. without further assumptions from other methods, and with two-dimensional atomic resolution based on STEM results only. Composition determination by STEM is possible because ADF-STEM images show dominant atomic-number contrast. This can be taken into account by image simulations that are used for a direct comparison to experimental results.
With these more accurate two-dimensional atomically resolved composition results, a deeper analysis of, amongst others, the interfaces of QWHs is possible. For the “W”-QWH, this analysis and comparison to single QWs reveals strong interaction of In and Sb during MOVPE growth. This interaction leads to an alteration of the interfaces compared to single QWs with interfaces to GaAs only.
As the goal of quantitative STEM is to locate, count and distinguish atoms in an atomic column, established composition determination for ternary III-V semiconductors is further developed towards potential capability of single-atom accuracy, i.e. counting substitute atoms. Image simulations are a great tool to explore this capability. The capability of single-atom accuracy is determined by statistics and leads to a probability for correct composition determination of an atomic column: For a given number of substitute atoms in an atomic column, a certain range of intensities can result due to different z-height configurations of the same atoms in that column. The probability for correct composition determination of an atomic column is influenced by the composition, i.e. the number of substitute atoms, and the thickness of that atomic column, i.e. the total number of atoms. Both increase the number of possible z-height configurations and therefore decrease the probability for correct composition determination. Additionally, the capability for composition determination is strongly influenced by the material system. This manifests in the difference in atomic number of substitute and matrix atom. However, for the characterization of technologically relevant specimens the material system and its composition are dictated by device requirements leaving only specimen thickness as parameter. This is a matter of optimum specimen preparation. Specimen preparation also has to ensure good quality of specimens, e.g. limited surface damage.
While correct composition determination for one atomic column is statistically determined, the overall accuracy as the average over many atomic columns is very good. Statistical deviations cancel each other which leads to an exact overall composition result. This is usually the case experimentally where many atomic columns are evaluated.
To distinguish atoms in an atomic column, one needs to count them first. STEM probes the total atomic number of an atomic column and thus intensity changes by composition and thickness are indistinguishable looking at the intensity. A wrong assumption for the number of atoms impedes accurate composition determination. Therefore, accurate knowledge of the local thickness is necessary. Commonly, the thickness of a QW was interpolated from regions with known composition obviously leading to local errors. A method to achieve local thickness and composition determination for ternary III-V semiconductors from a single STEM image is part of this work. It utilizes the crystal symmetry in -viewing direction and knowledge about cross scattering from image simulations. Then, thickness and composition can be determined iteratively.
Since the effects of thickness and composition on the intensity are interchangeable, the principle of this method can also be applied to quaternary III-V semiconductors with two elements on each sub lattice. The thickness has to be interpolated from regions of known composition or has to be determined in a different manner. Again, the intensity of both sub lattices combined with knowledge about cross scattering from image simulations can be used to determine both compositions iteratively.
All composition determination methods can be optimized with regards to the ADF-STEM detector range. The exploitation of angular dependencies of electron scattering offers great potential for further improvements and developments in the future. In particular, this is made possible by the available experimental hardware, i.e. pixelated detectors. Next to optimizing the composition determination of the material systems investigated in this work, this kind of composition determination which is looking for single-atom accuracy can also be extended to different III/V semiconductors as well as other crystalline materials with unknown composition.