The standard technique for sub-pixel estimation of atom positions from atomic resolution scanning transmission electron microscopy images relies on fitting intensity maxima or minima with a two-dimensional Gaussian function. While this is a widespread method of measurement, it can be error prone in images with non-zero aberrations, strong intensity differences between adjacent atoms or in situations where the neighboring atom positions approach the resolution limit of the microscope. Here we demonstrate mpfit , an atom finding algorithm that iteratively calculates a series of overlapping two-dimensional Gaussian functions to fit the experimental dataset and then subsequently uses a subset of the calculated Gaussian functions to perform sub-pixel refinement of atom positions. Based on both simulated and experimental datasets presented in this work, this approach gives lower errors when compared to the commonly used single Gaussian peak fitting approach and demonstrates increased robustness over a wider range of experimental conditions.
Scanning transmission electron microscopy (STEM) at low energies (≤ 30 keV) in a scanning electron microscope is well suited to distinguish weakly scattering materials with similar materials properties and analyze their microstructure. The capabilities of the technique are illustrated in this work to resolve material domains in PTB7:PC 71 BM bulk-heterojunctions, which are commonly implemented for light-harvesting in organic solar cells. Bright-field (BF-) and high-angle annular dark-field (HAADF-) STEM contrast of pure PTB7 and PC 71 BM was first systematically analyzed using a wedge-shaped sample with well-known thickness profile. Monte-Carlo simulations are essential for the assignment of material contrast for materials with only slightly different scattering properties. Different scattering cross-sections were tested in Monte-Carlo simulations with screened Rutherford scattering cross-sections yielding best agreement with the experimental data. The STEM intensity also depends on the local specimen thickness, which can be dealt with by correlative STEM and scanning electron microscopy (SEM) imaging of the same specimen region yielding additional topography information. Correlative STEM/SEM was applied to determine the size of donor (PTB7) and acceptor (PC 71 BM) domains in PTB7:PC 71 BM absorber layers that were deposited from solution with different contents of the processing additive 1,8-diiodooctane (DIO).
The automated detection of defects in high-angle annular dark-field Z-contrast (HAADF) scanning-transmission-electron microscopy (STEM) images has been a major challenge. Here, we report an approach for the automated detection and categorization of structural defects based on changes in the material's local atomic geometry. The approach applies geometric graph theory to the already-found positions of atomic-column centers and is capable of detecting and categorizing any defect in thin diperiodic structures (i.e., "2D materials") and a large subset of defects in thick diperiodic structures (i.e., 3D or bulk-like materials). Despite the somewhat limited applicability of the approach in detecting and categorizing defects in thicker bulk-like materials, it provides potentially informative insights into the presence of defects. The categorization of defects can be used to screen large quantities of data and to provide statistical data about the distribution of defects within a material. This methodology is applicable to atomic column locations extracted from any type of high-resolution image, but here we demonstrate it for HAADF STEM images.
Hole-free phase plates (HFPPs), also known as Volta phase plates, were already demonstrated to be well suited for in-focus transmission electron microscopy imaging of organic objects. However, the underlying physical processes have not been fully understood yet. To further elucidate the imaging properties of HFPPs, phase shift measurements were carried out under different experimental conditions. Both positive and negative phase shifts occur depending on the diameter of the zero-order electron beam and the HFPP film temperature. The analysis of Thon ring patterns of an amorphous carbon test sample reveals that the phase-shifting patch can be significantly larger than the size of the zero-order beam on the HFPP film. An HFPP was used for in-focus phase contrast imaging of carbon nanotube (CNT) bundles under positive and negative phase-shifting conditions. The comparison of experimental and simulated images of CNT bundles gives detailed information on the phase shift profile, which depends on the spatial frequency in the vicinity of the zero-order beam. The shape of the phase shift profile also explains halo-like image artifacts that surround the imaged objects.
STEM XEDS spectrum images can be drastically denoised by application of the principal component analysis (PCA). This paper looks inside the PCA workflow step by step on an example of a complex semiconductor structure consisting of a number of different phases. Typical problems distorting the principal components decomposition are highlighted and solutions for the successful PCA are described. Particular attention is paid to the optimal truncation of principal components in the course of reconstructing denoised data. A novel accurate and robust method, which overperforms the existing truncation methods is suggested for the first time and described in details.
