Abstract: The maximum a posteriori (MAP) probability rule for atom column detection can also be used as a tool to evaluate the relation between scanning transmission electron microscopy (STEM) image quality and atom detectability. In this chapter, a new image-quality measure is proposed that correlates well with atom detectability, namely the integrated contrast-to-noise ratio (ICNR). Furthermore, the working principle of the MAP probability rule is described in detail showing a close relation to the principles of model-selection methods.

Abstract: In this chapter, the principles of detection theory are used to quantify the probability of error for atom counting from high-resolution scanning transmission electron microscopy (HRSTEM) images. Binary and multiple hypothesis testing have been investigated in order to determine the limits to the precision with which the number of atoms in a projected atomic column can be estimated. The probability of error has been calculated when using STEM images, scattering cross-sections or peak intensities as a criterion to count atoms. Based on this analysis, we conclude that scattering cross-sections perform almost equally well as images and perform better than peak intensities. Furthermore, the optimal STEM detector design can be derived for atom counting using the expression of the probability of error. We show that for very thin objects the low-angle annular dark-field (LAADF) regime is optimal and that for thicker objects the optimal inner detector angle increases.

Abstract: Understanding light–matter interactions in nanomaterials is crucial for
optoelectronic, photonic, and plasmonic applications. Specifically, metal
nanoparticles (NPs) strongly interact with light and can undergo shape
transformations, fragmentation and ablation upon (pulsed) laser excitation.
Despite being vital for technological applications, experimental insight into
the underlying atomistic processes is still lacking due to the complexity of
such measurements. Herein, atomic resolution electron tomography is performed
on the same mesoporous-silica-coated gold nanorod, before and after
femtosecond laser irradiation, to assess the missing information. Combined
with molecular dynamics (MD) simulations based on the experimentally
determined 3D atomic-scale morphology, the complex atomistic rearrangements,
causing shape deformations and defect generation, are unraveled.
These rearrangements are simultaneously driven by surface diffusion, facet
restructuring, and strain formation, and are influenced by subtleties in the
atomic distribution at the surface.

Abstract: In oxide heterostructures, different materials are integrated into a single artificial crystal, resulting in a breaking of inversion symmetry across the heterointerfaces. A notable example is the interface between polar and nonpolar materials, where valence discontinuities lead to otherwise inaccessible charge and spin states. This approach paved the way for the discovery of numerous unconventional properties absent in the bulk constituents. However, control of the geometric structure of the electronic wave functions in correlated oxides remains an open challenge. Here, we create heterostructures consisting of ultrathin SrRuO3, an itinerant ferromagnet hosting momentum-space sources of Berry curvature, and
LaAlO3, a polar wide-band-gap insulator. Transmission electron microscopy reveals an atomically sharp LaO/RuO2/SrO interface configuration, leading to excess charge being pinned near the LaAlO3/SrRuO3 interface. We demonstrate through magneto-optical characterization, theoretical calculations and transport measurements that the real-space charge reconstruction drives a reorganization of the topological charges in the band structure, thereby modifying the momentum-space Berry curvature in SrRuO3. Our results illustrate how the topological and magnetic features of oxides can be manipulated by engineering charge discontinuities at oxide interfaces.

Abstract: Advances in controlling energy migration pathways in core-shell lanthanide (Ln)-based hetero-nanocrystals (HNCs) have relied heavily on assumptions about how optically active centers are distributed within individual HNCs. In this article, it is demonstrated that different types of interface patterns can be formed depending on shell growth conditions. Such interface patterns are not only identified but also characterized with spatial resolution ranging from the nanometer- to the atomic-scale. In the most favorable cases, atomic-scale resolved maps of individual particles are obtained. It is also demonstrated that, for the same type of core-shell architecture, the interface pattern can be engineered with thicknesses of just 1 nm up to several tens of nanometers. Total alloying between the core and shell domains is also possible when using ultra-small particles as seeds. Finally, with different types of interface patterns (same architecture and chemical composition of the core and shell domains) it is possible to modify the output color (yellow, red, and green-yellow) or change (improvement or degradation) the absolute upconversion quantum yield. The results presented in this article introduce an important paradigm shift and pave the way toward the emergence of a new generation of core-shell Ln-based HNCs with better control over their atomic-scale organization.

Abstract: We report a study of scattering dynamics in crystals employing momentum-resolved scanning transmission
electron microscopy under varying illumination conditions. As we perform successive changes of the probe
focus, multiple real-space signals are obtained in dependence of the shape of the incident electron wave.
With support from extensive simulations, each signal is shown to be characterised by an optimum focus for
which the contrast is maximum and which differs among different signals. For instance, a systematic focus
mismatch is found between images formed by high-angle scattering, being sensitive to thickness and chemical
composition, and the first moment in diffraction space, being sensitive to electric fields. It follows that a single
recording at one specific probe focus is usually insufficient to characterise materials comprehensively. Most
importantly, we demonstrate in experiment and simulation that the second moment (

Abstract: In this study, a new bottom-up approach is proposed to predict the crystal structure of the substrate-induced polymorph (SIP) of an archetypal molecular semiconductor. In spite of intense efforts, the formation mechanism of SIPs is still not fully understood, and predicting their crystal structure is a very delicate task. Here, we selected lead phthalocyanine (PbPc) as a prototypical molecular material because it is a highly symmetrical yet nonplanar molecule and we demonstrate that the growth and crystal structure of the PbPc SIPs can be templated by the corresponding physisorbed self-assembled molecular networks (SAMNs). Starting from SAMNs of PbPc formed at the solution/graphite interface, the structural and energetic aspects of the assembly were studied by a combination of in situ scanning tunneling microscopy and multiscale computational chemistry approach. Then, the growth of a PbPc SIP on top of the physisorbed monolayer was modeled without prior experimental knowledge, from which the crystal structure of the SIP was predicted. The theoretical prediction of the SIP was verified by determining the crystal structure of PbPc thin films using X-ray diffraction techniques, revealing the formation of a new polymorph of PbPc on the graphite substrate. This study clearly illustrates the correlation between the SAMNs and SIPs, which are traditionally considered as two separate but conceptually connected research areas. This approach is applicable to molecular materials in general to predict the crystal structure of their SIPs.

Abstract: Understanding the thermal stability of bimetallic nanoparticles is of vital importance to preserve their functionalities during their use in a variety of applications. In contrast to well-studied bimetallic systems such as Au@Ag, heat-induced morphological and compositional changes in Au@Pt nanoparticles are insufficiently understood, even though Au@Pt is an important material for catalysis. To investigate the thermal instability of Au@Pt nanorods at temperatures below their bulk melting point, we combined in situ heating with two- and three-dimensional electron microscopy techniques, including three-dimensional energy-dispersive X-ray spectroscopy. The experimental results were used as input for molecular dynamics simulations, to unravel the mechanisms behind the morphological transformation of Au@Pt core–shell nanorods. We conclude that thermal stability is influenced not only by the degree of coverage of Pt on Au but also by structural details of the Pt shell.

Abstract: A new methodology is presented to count the number of atoms in multimetallic nanocrystals by combining energy dispersive X-ray spectroscopy (EDX) and high angle annular dark field scanning transmission electron microscopy (HAADF STEM). For this purpose, the existence of a linear relationship between the incoherent HAADF STEM and EDX images is exploited. Next to the number of atoms for each element in the atomic columns, the method also allows quantification of the error in the obtained number of atoms, which is of importance given the noisy nature of the acquired EDX signals. Using experimental images of an Au@Ag core–shell nanorod, it is demonstrated that 3D structural information can be extracted at the atomic scale. Furthermore, simulated data of an Au@Pt core–shell nanorod show the prospect to characterize heterogeneous nanostructures with adjacent atomic numbers.

Abstract: Advanced materials often consist of multiple elements which are arranged in a complicated structure. Quantitative scanning transmission electron microscopy is useful to determine the composition and thickness of nanostructures at the atomic scale. However, significant difficulties remain to quantify mixed columns by comparing the resulting atomic resolution images and spectroscopy data with multislice simulations where dynamic scattering needs to be taken into account. The combination of the computationally intensive nature of these simulations and the enormous amount of possible mixed column configurations for a given composition indeed severely hamper the quantification process. To overcome these challenges, we here report the development of an incoherent non-linear method for the fast prediction of ADF-EDX scattering cross-sections of mixed columns under channelling conditions. We first explain the origin of the ADF and EDX incoherence from scattering physics suggesting a linear dependence between those two signals in the case of a high-angle ADF detector. Taking EDX as a perfect incoherent reference mode, we quantitatively examine the ADF longitudinal incoherence under different microscope conditions using multislice simulations. Based on incoherent imaging, the atomic lensing model previously developed for ADF is now expanded to EDX, which yields ADF-EDX scattering cross-section predictions in good agreement with multislice simulations for mixed columns in a core–shell nanoparticle and a high entropy alloy. The fast and accurate prediction of ADF-EDX scattering cross-sections opens up new opportunities to explore the wide range of ordering possibilities of heterogeneous materials with multiple elements.

Abstract: Quantitative structure determination is needed in order to study and understand nanomaterials at the atomic scale. Materials characterisation resulting in precise structural information is a crucial point to understand the structure–property relation of materials. Counting the number of atoms and retrieving the 3D atomic structure of nanoparticles plays an important role here. In this paper, an overview will be given of the atom-counting methodology and its applications over the past decade. The procedure to count the number of atoms will be discussed in detail and it will be shown how the performance of the method can be further improved. Furthermore, advances toward mixed element nanostructures, 3D atomic modelling based on the atom-counting results, and quantifying the nanoparticle dynamics will be highlighted.

Abstract: Reducible supports can affect the performance of metal catalysts by the formation of suboxide overlayers upon reduction, a process referred to as the strong metal-support interaction (SMSI). A combination of operando electron microscopy and vibrational spectroscopy revealed that thin TiOx overlayers formed on nickel/titanium dioxide catalysts during 400 degrees C reduction were completely removed under carbon dioxide hydrogenation conditions. Conversely, after 600 degrees C reduction, exposure to carbon dioxide hydrogenation reaction conditions led to only partial reexposure of nickel, forming interfacial sites in contact with TiOx and favoring carbon-carbon coupling by providing a carbon species reservoir. Our findings challenge the conventional understanding of SMSIs and call for more-detailed operando investigations of nanocatalysts at the single-particle level to revisit static models of structure-activity relationships.

Abstract: Quantification of annular dark field (ADF) scanning transmission electron microscopy (STEM) images in terms
of composition or thickness often relies on probe-position integrated scattering cross sections (PPISCS). In
order to compare experimental PPISCS with theoretically predicted ones, expensive simulations are needed for
a given specimen, zone axis orientation, and a variety of microscope settings. The computation time of such
simulations can be in the order of hours using a single GPU card. ADF STEM simulations can be efficiently
parallelized using multiple GPUs, as the calculation of each pixel is independent of other pixels. However, most
research groups do not have the necessary hardware, and, in the best-case scenario, the simulation time will
only be reduced proportionally to the number of GPUs used. In this manuscript, we use a learning approach and
present a densely connected neural network that is able to perform real-time ADF STEM PPISCS predictions as
a function of atomic column thickness for most common face-centered cubic (fcc) crystals (i.e., Al, Cu, Pd, Ag,
Pt, Au and Pb) along [100] and [111] zone axis orientations, root-mean-square displacements, and microscope
parameters. The proposed architecture is parameter efficient and yields accurate predictions for the PPISCS
values for a wide range of input parameters that are commonly used for aberration-corrected transmission
electron microscopes.

Abstract: Short-wave infrared (SWIR) fluorescence could become the new gold standard in optical imaging for biomedical applications due to important advantages such as lack of autofluorescence, weak photon absorption by blood and tissues, and reduced photon scattering coefficient. Therefore, contrary to the visible and NIR regions, tissues become translucent in the SWIR region. Nevertheless, the lack of bright and biocompatible probes is a key challenge that must be overcome to unlock the full potential of SWIR fluorescence. Although rare-earth-based core-shell nanocrystals appeared as promising SWIR probes, they suffer from limited photoluminescence quantum yield (PLQY). The lack of control over the atomic scale organization of such complex materials is one of the main barriers limiting their optical performance. Here, the growth of either homogeneous (α-NaYF₄) or heterogeneous (CaF₂) shell domains on optically-active α-NaYF₄:Yb:Er (with and without Ce³⁺co-doping) core nanocrystals is reported. The atomic scale organization can be controlled by preventing cation intermixing only in heterogeneous core-shell nanocrystals with a dramatic impact on the PLQY. The latter reached 50% at 60 mW/cm²; one of the highest reported PLQY values for sub-15 nm nanocrystals. The most efficient nanocrystals were utilized for in vivo imaging above 1450 nm.

Abstract: In this study, the multi-layer self-assembled molecular network formation of an alkylated tetrathiafulvalene compound is studied at the liquid-solid interface between 1-phenyloctane and graphite. A combined theoretical/experimental approach associating force-field and quantum-chemical calculations with scanning tunnelling microscopy is used to determine the two-dimensional self-assembly beyond the monolayer, but also to further the understanding of the molecular adsorption conformation and its impact on the molecular packing within the assemblies at the monolayer and bilayer level.