Abstract: Topological superconductivity is of great contemporary interest and has been proposed in doped Bi₂Se₃, in which electron-donating atoms such as Cu, Sr or Nb have been intercalated into the Bi₂Se₃structure. For Nb_{<italic>x</italic>}Bi₂Se₃, with<italic>T</italic>_c ~ 3 K, it is assumed in the literature that Nb is inserted in the van der Waals gap. However, in this work an alternative origin for the superconductivity in Nb-doped Bi₂Se₃is established. In contrast to previous reports, it is deduced that Nb intercalation in Bi₂Se₃does not take place. Instead, the superconducting behaviour in samples of nominal composition Nb_{<italic>x</italic>}Bi₂Se₃results from the (BiSe)_1.10NbSe₂misfit phase that is present in the sample as an impurity phase for small<italic>x</italic>(0.01 ≤ <italic>x</italic> ≤ 0.10) and as a main phase for large<italic>x</italic>(<italic>x</italic> = 0.50). The structure of this misfit phase is studied in detail using a combination of X-ray diffraction and transmission electron microscopy techniques.

Abstract: Colloidal copper(I) sulfide (Cu2-xS) nanocrystals (NCs) have attracted much attention for a wide range of applications because of their unique optoelectronic properties, driving scientists to explore the potential of using Cu2-xS NCs as seeds in the synthesis of heteronanocrystals to achieve new multifunctional materials. Herein, we developed a multistep synthesis strategy toward Cu2-xS/ZnS heteronanorods. The Janus-type Cu2-xS/ZnS heteronanorods are obtained by the injection of hexagonal high-chalcocite Cu2-xS seed NCs in a hot zinc oleate solution in the presence of suitable surfactants, 20 s after the injection of sulfur precursors. The Cu2-xS seed NCs undergo rapid aggregation and coalescence in the first few seconds after the injection, forming larger NCs that act as the effective seeds for heteronucleation and growth of ZnS. The ZnS heteronucleation occurs on a single (100) facet of the Cu2-xS seed NCs and is followed by fast anisotropic growth along a direction that is perpendicular to the c-axis, thus leading to Cu2-xS/ZnS Janus-type heteronanorods with a sharp heterointerface. Interestingly, the high-chalcocite crystal structure of the injected Cu2-xS seed NCs is preserved in the Cu2-xS segments of the heteronanorods because of the highthermodynamic stability of this Cu2-xS phase. The Cu2-xS/ZnS heteronanorods are subsequently converted into single-component Cu2-xS and CuInS2 nanorods by postsynthetic topotactic cation exchange. This work expands the possibilities for the rational synthesis of colloidal multicomponent heteronanorods by allowing the design principles of postsynthetic heteroepitaxial seeded growth and nanoscale cation exchange to be combined, yielding access to a plethora of multicomponent heteronanorods with diameters in the quantum confinement regime.

Abstract: In this chapter, a statistical model-based method to count the number of atoms of monotype crystalline nanostructures from high-resolution annular dark-field (ADF) scanning transmission electron microscopy (STEM) images is discussed in detail together with a thorough study on the possibilities and inherent limitations. We show that this method can be applied to nanocrystals of arbitrary shape, size, and atom type. The validity of the atom-counting results is confirmed by means of detailed image simulations and it is shown that the high sensitivity of our method enables us to count atoms with single atom sensitivity.

Abstract: This chapter provides an overview of statistical and quantitative methodologies that have pushed (scanning) transmission electron microscopy ((S)TEM) toward accurate and precise measurements of unknown structure parameters for understanding the relation between the structure of a material and its properties. Hereby, statistical parameter estimation theory has extensively been used which enabled not only measuring atomic column positions, but also quantifying the number of atoms, and detecting atomic columns as accurately and precisely as possible from experimental images. As a general conclusion, it can be stated that advanced statistical techniques are ideal tools to perform quantitative electron microscopy at the atomic scale. In the future, statistical methods will continue to be developed and novel quantification procedures will open up new possibilities for studying material structures at the atomic scale.

Abstract: In this chapter, the principles of statistical parameter estimation theory for a quantitative analysis of atomic-resolution electron microscopy images are introduced. Within this framework, electron microscopy images are described by a parametric statistical model. Here, parametric models are introduced for different types of electron microscopy images: reconstructed exit waves, annular dark-field (ADF) scanning transmission electron microscopy (STEM) images, and simultaneously acquired ADF and annular bright-field (ABF) STEM images. Furthermore, the Cramér-Rao lower bound (CRLB) is introduced, i.e. a theoretical lower bound on the variance of any unbiased estimator. This CRLB is used to quantify the precision of the structure parameters of interest, such as the atomic column positions and the integrated atomic column intensities.

Abstract: Dry powder coating is an effective approach to protect the surfaces of layered cathode active materials (CAMs) in lithium-ion batteries. Previous investigations indicate an incorporation of lithium ions in fumed Al2O3, ZrO2, and TiO2 coatings on LiNi0.7Mn0.15Co0.15O2 during cycling, improving the cycling performance. Here, this coating approach is transferred for the first time to fumed ternary LiAlO2, Li4Zr3O8, and Li4Ti5O12 and directly compared with their lithium-free equivalents. All materials could be processed equally and their nanostructured small aggregates accumulate on the CAM surfaces to quite homogeneous coating layers with a certain porosity. The LiNixMnyCozO2 (NMC) coated with lithium-containing materials shows an enhanced improvement in overall capacity, capacity retention, rate performance, and polarization behavior during cycling, compared to their lithium-free analogues. The highest rate performance was achieved with the fumed ZrO2 coating, while the best long-term cycling stability with the highest absolute capacity was obtained for the fumed LiAlO2-coated NMC. The optimal coating agent for NMC to achieve a balanced system is fumed Li4Ti5O12, providing a good compromise between high rate capability and good capacity retention. The coating agents prevent CAM particle cracking and degradation in the order LiAlO2 ≈ Al2O3 > Li4Ti5O12 > Li4Zr3O8 > ZrO2 > TiO2. A schematic model for the protection and electrochemical performance enhancement of high-nickel NMC with fumed metal oxide coatings is sketched. It becomes apparent that physical and chemical characteristics of the coating significantly influence the performance of NMC. A high degree of coating-layer porosity is favorable for the rate capability, while a high coverage of the surface, especially in vulnerable grain boundaries, enhances the long-term cycling stability and improves the cracking behavior of NMCs. While zirconium-containing coatings possess the best chemical properties for high rate performances, aluminum-containing coatings feature a superior chemical nature to protect high-nickel NMCs.

Abstract: The structural and magnetic properties of LaMnO₃/LaFeO₃(LMO/LFO) heterostructures are characterized using a combination of scanning transmission electron microscopy, electron energy-loss spectroscopy, bulk magnetometry, and resonant x-ray reflectivity. Unlike the relatively abrupt interface when LMO is deposited on top of LFO, the interface with reversed growth order shows significant cation intermixing of Mn³⁺and Fe³⁺, spreading ∼8 unit cells across the interface. The asymmetric interfacial chemical profiles result in distinct magnetic properties. The bilayer with abrupt interface shows a single magnetic hysteresis loop with strongly enhanced coercivity, as compared to the LMO plain film. However, the bilayer with intermixed interface shows a step-like hysteresis loop, associated with the separate switching of the “clean” and intermixed LMO sublayers. Our study illustrates the key role of interfacial chemical profile in determining the functional properties of oxide heterostructures.

Abstract: Chirality in inorganic nanoparticles and nanostructures has gained increasing scientific interest, because of the possibility to tune their ability to interact differently with left- and right-handed circularly polarized light. In some cases, the optical activity is hypothesized to originate from a chiral morphology of the nanomaterial. However, quantifying the degree of chirality in objects with sizes of tens of nanometers is far from straightforward. Electron tomography offers the possibility to faithfully retrieve the three-dimensional morphology of nanomaterials, but only a qualitative interpretation of the morphology of chiral nanoparticles has been possible so far. We introduce herein a methodology that enables us to quantify the helicity of complex chiral nanomaterials, based on the geometrical properties of a helix. We demonstrate that an analysis at the single particle level can provide significant insights into the origin of chiroptical properties.

Abstract: We introduce a Bayesian genetic algorithm for reconstructing atomic models of monotype crystalline nanoparticles from a single projection using Z-contrast imaging. The number of atoms in a projected atomic column obtained from annular dark field scanning transmission electron microscopy images serves as an input for the initial three-dimensional model. The algorithm minimizes the energy of the structure while utilizing a priori information about the finite precision of the atom-counting results and neighbor-mass relations. The results show promising prospects for obtaining reliable reconstructions of beam-sensitive nanoparticles during dynamical processes from images acquired with sufficiently low incident electron doses.

Abstract: Electron microscopy is an indispensable tool for the characterization of (nano) materials. Electron microscopes are typically very expensive and their internal operation is often shielded from the user. This situation can provide fast and high quality results for researchers focusing on e.g. materials science if they have access to the relevant instruments. For researchers focusing on technique development, wishing to test novel setups, however, the high entry price can lead to risk aversion and deter researchers from innovating electron microscopy technology further. The closed attitude of commercial entities about how exactly the different parts of electron microscopes work, makes it even harder for newcomers in this field. Here we propose an affordable, easy-to-build electron detector for use in a scanning electron microscope (SEM). The aim of this project is to shed light on the functioning of such detectors as well as show that even a very modest design can lead to acceptable performance while providing high flexibility for experimentation and customization.

Abstract: Advanced electron microscopy techniques, including scanning electron microscopes (SEM), scanning transmission electron microscopes (STEM), and transmission electron microscopes (TEM), have revolutionized imaging capabilities. However, achieving high-quality experimental images remains a challenge due to various distortions stemming from the instrumentation and external factors. These distortions, introduced at different stages of imaging, hinder the extraction of reliable quantitative insights. In this paper, we will discuss the main sources of distortion in TEM and S(T)EM images, develop models to describe them, and propose a method to correct these distortions using a convolutional neural network. We validate the effectiveness of our method on a range of simulated and experimental images, demonstrating its ability to significantly enhance the signal-to-noise ratio. This improvement leads to a more reliable extraction of quantitative structural information from the images. In summary, our findings offer a robust framework to enhance the quality of electron microscopy images, which in turn supports progress in structural analysis and quantification in materials science and biology.

Abstract: Activated carbon (AC) materials from renewable sources are widely used in electrochemical applications due to their well‐known high surface area. However, their application as electrode material in double‐layer electrochemical devices may be limited due to their relatively low electrical conductivity and lightweight. To overcome these limitations, the incorporation of pseudocapacitance metal oxide nanoparticles is an optimum approach. These nanoparticles can provide a second energy storage mechanism to the composite, mitigating the loss of surface area associated with their incorporation. As a result, the composite material is endowed with increased conductivity and higher density, making it more suitable for practical implementation in real devices. In this study, we have incorporated a fine dispersion of 1 % of MnO clusters into a highly porous activated carbon synthesized from walnut shells (WAC). The high‐resolution electron microscopy studies, combined with their related analytical techniques, allow us to determine the presence of the cluster within the matrix carbon precisely. The resulting MnO@WAC composite demonstrated significantly improved capacitive behavior compared with the WAC material, with increased volumetric capacitance and higher charge retention at higher current densities. The composite‘s electrochemical performance suggests its potential as a promising electrode material for supercapacitors, addressing drawbacks associated with traditional AC materials.