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 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 [010]-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

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 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 [010]-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

Optimization of imaging conditions for composition determination by annular dark field STEM

Quantitative scanning transmission electron microscopy (STEM) allows composition determination for nanomaterials at an atomic scale. To improve the accuracy of the results obtained, optimized imaging parameters should be chosen for annular dark field imaging. In a simulation study, we investigate the influence of imaging parameters on the accuracy of the composition determination with the example of ternary III-V semiconductors. It is shown that inner and outer detector angles and semi-convergence angle can be optimized, also in dependence on specimen thickness. Both, a minimum sampling of the image and a minimum electron dose are required. These findings are applied experimentally by using a fast pixelated detector to allow free choice of detector angles

Influence of plasmon excitations on atomic‑resolution quantitative 4D scanning transmission electron microscopy

Scanning transmission electron microscopy (STEM) allows to gain quantitative information on the atomic‑scale structure and composition of materials, satisfying one of todays major needs in the development of novel nanoscale devices. The aim of this study is to quantify the impact of inelastic, i.e. plasmon excitations (PE), on the angular dependence of STEM intensities and answer the question whether these excitations are responsible for a drastic mismatch between experiments and contemporary image simulations observed at scattering angles below∼40 mrad. For the two materials silicon and platinum, the angular dependencies of elastic and inelastic scattering are investigated. We utilize energy filtering in two complementary microscopes, which are representative for the systems used for quantitative STEM, to form position‑averaged diffraction patterns as well as atomically resolved 4D STEM data sets for different energy ranges. The resulting five‑dimensional data are used to elucidate the distinct features in real and momentum space for different energy losses. We find different angular distributions for the elastic and inelastic scattering, resulting in an increased low‑angle intensity (∼10–40 mrad). The ratio of inelastic/elastic scattering increases with rising sample thickness, while the general shape of the angular dependency is maintained. Moreover, the ratio increases with the distance to an atomic column in the low‑angle regime. Since PE are usually neglected in image simulations, consequently the experimental intensity is underestimated at these angles, which especially affects bright field or low‑angle annular dark field imaging. The high‑angle regime, however, is unaffected. In addition, we find negligible impact of inelastic scattering on first‑ moment imaging in momentum‑resolved STEM, which is important for STEM techniques to measure internal electric fields in functional nanostructures. To resolve the discrepancies between experiment and simulation, we present an adopted simulation scheme including PE. This study highlights the necessity to take into account PE to achieve quantitative agreement between simulation and experiment. Besides solving the fundamental question of missing physics in established simulations, this finally allows for the quantitative evaluation of low‑angle scattering, which contains valuable information about the material investigated

Simultaneous determination of local thickness and composition for ternary III-V semiconductors by aberration-corrected STEM

Scanning transmission electron microscopy (STEM) is a suitable method for the quantitative characterization of nanomaterials. For an absolute composition determination on an atomic scale, the thickness of the specimen has to be known locally with high accuracy. Here, we propose a method to determine both thickness and composition of ternary III-V semiconductors locally from one STEM image as shown for the example material systems Ga(AsBi) and (GaIn)As. In a simulation study, the feasibility of the method is proven and the influence of specimen thickness and detector angles used is investigated. An application to an experimental STEM image of a Ga(AsBi) quantum well grown by metal organic vapour phase epitaxy yields an excellent agreement with composition results from high resolution X-ray diffraction

Segregation at interfaces in (GaIn)As/Ga(AsSb)/(GaIn)As- quantum well heterostructures explored by atomic resolution STEM

Surface segregation and interaction effects of In and Sb in (GaIn)As/Ga(AsSb)/(GaIn)As- “W”-type quantum well heterostructures (“W”-QWHs) are investigated by high angle annular dark field scanning transmission electron microscopy with atomic resolution. “W”-QWHs are promising candidates for type-II laser applications in telecommunications. In this study, independent (GaIn)As and Ga(AsSb) quantum wells as well as complete “W”-QWHs are grown by metal organic vapour phase epitaxy on GaAs substrate. The composition is determined with atomic resolution by comparison of the experimental data to complementary contrast simulations. From concentration profiles, an altered segregation in “W”-QWHs in comparison to single (GaIn)As and Ga(AsSb) quantum wells grown on GaAs is detected. In and Sb are clearly influencing each other during the growth, including blocking effects of In incorporation by Sb and vice versa. Especially, growth rate and total amount of Sb incorporated into Ga(AsSb) are decreased by In being present