Atom counting from a combination of two ADF STEM images

Towards atom counting from first moment STEM images: Methodology and possibilities

Through a simulation-based study we develop a statistical model-based quantification method for atomic resolution first moment scanning transmission electron microscopy (STEM) images. This method uses the uniformly weighted least squares estimator to determine the unknown structure parameters of the images and to isolate contributions from individual atomic columns. In this way, a quantification of the projected potential per atomic column is achieved. Since the integrated projected potential of an atomic column scales linearly with the number of atoms it contains, it can serve as a basis for atom counting. The performance of atom counting from first moment STEM imaging is compared to that from traditional HAADF STEM in the presence of noise. Through this comparison, we demonstrate the advantage of first moment STEM images to attain more precise atom counts. Finally, we compare the integrated potential extracted from first-moment images of a wedge-shaped sample to those values from the bulk crystal. The excellent agreement found between these values proves the robustness of using bulk crystal simulations as a reference library. This enables atom counting for samples with different shapes by comparison with these library values.

Atomic-Scale Imaging of Polymers and Precision Molecular Weight Analysis

Polymer design requires fine control over syntheses and a thorough understanding of their macromolecular structure. Herein, near-atomic level imaging of polymers is achieved, enabling the precise determination of one of the most important macromolecular characteristics: molecular weight. By judiciously designing and synthesizing different linear metal(loid)-rich homopolymers, subnanoscale polymer imaging is achieved through annular dark field-scanning transmission electron microscopy (ADF-STEM), owing to the incorporation of high Z atoms in the side chain of the monomeric units. The molecular weight of these polymers can be precisely determined by detecting and counting their metal(loid) atoms upon ADF-STEM imaging, at sample concentrations as low as 10 μg·mL-1. Notably, a commonly used C, H, and O-containing polymer (i.e., poly(methyl acrylate)) that was thus far inaccessible at the atomic scale is derivatized to allow for subnano-level imaging, thus expanding the scope of our approach toward the atomic-level visualization of commodity polymers.

Element specific atom counting for heterogeneous nanostructures: Combining multiple ADF STEM images for simultaneous thickness and composition determination

In this paper, a methodology is presented to count the number of atoms in heterogeneous nanoparticles based on the combination of multiple annular dark field scanning transmission electron microscopy (ADF STEM) images. The different non-overlapping annular detector collection regions are selected based on the principles of optimal statistical experiment design for the atom-counting problem. To count the number of atoms, the total intensities of scattered electrons for each atomic column, the so-called scattering cross-sections, are simultaneously compared with simulated library values for the different detector regions by minimising the squared differences. The performance of the method is evaluated for simulated Ni@Pt and Au@Ag core-shell nanoparticles. Our approach turns out to be a dose efficient alternative for the investigation of beam-sensitive heterogeneous materials as compared to the combination of ADF STEM and energy dispersive X-ray spectroscopy.