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

Accurate first-principle bandgap predictions in strain-engineered ternary III-V semiconductors

Tuning the bandgap in ternary III-V semiconductors via modification of the composition or the strain in the material is a major approach for the design of optoelectronic materials. Experimental approaches screening a large range of possible target structures are hampered by the tremendous effort to optimize the material synthesis for every target structure. We present an approach based on density functional theory efficiently capable of providing the bandgap as a function of composition and strain. Using a specific density functional designed for accurate bandgap computation (TB09) together with a band unfolding procedure and special quasirandom structures, we develop a computational protocol efficiently able to predict bandgaps. The approach's accuracy is validated by comparison to selected experimental data. We thus map the phase space of composition and strain (we call this the ``bandgap phase diagram'') for several important III-V compound semiconductors: GaAsP, GaAsN, GaPSb, GaAsSb, GaPBi, and GaAsBi. We show the application of these diagrams for identifying the most promising materials for device design. Furthermore, our computational protocol can easily be generalized to explore the vast chemical space of III-V materials with all other possible combinations of III- and V-elements.Comment: 13 pages, 7 figures, GitHub (https://bmondal94.github.io/Bandgap-Phase-Diagram/

Coating versus Doping: Understanding the Enhanced Performance of High‐Voltage Batteries by the Coating of Spinel LiNi0.5_{0.5}Mn1.5_{1.5}O4_4 with Li0.35_{0.35}La0.55_{0.55}TiO3_3

Li$_{0.35}$La$_{0.55}$TiO$_3$ (LLTO) coated spinel LiNi$_{0.5}$Mn$_{1.5}$O$_4$ (LNMO) as cathode material is fabricated by a new method using hydrogen-peroxide as activating agent. The structure of the obtained active materials is investigated using scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS), and the electrochemical properties of the prepared cathodes are probed by the charge–discharge studies. The morphology of the coating material on the surface and the degree of coverage of the coated particles is investigated by the SEM, which shows a fully dense and homogeneous coating (thickness ≈ 7 nm, determined by TEM) on the surface of active material. XRD studies of the coated active materials treated at different temperatures (between 300 °C and 1000 °C) reveal expansion or contraction of the unit cell in dependence of the coating concentration and degree of Ti diffusion. It is concluded, that for the LNMO particles calcined at low temperatures, the LLTO coating layer is still intact and protects the active material from the interaction with the electrolyte. However, for the coated particles treated at high temperatures, Ti ions migrate into the structure of LNMO during the modification process between 500 °C and 800 °C, resulting in “naked” and unprotected particles