Abstract: Strain has a strong effect on the properties of materials and the performance of electronic devices. Their ever shrinking size translates into a constant demand for accurate and precise measurement methods with a very high spatial resolution. In this regard, transmission electron microscopes are key instruments thanks to their ability to map strain with a subnanometer resolution. Here, we present a method to measure strain at the nanometer scale based on the diffraction of electron Bessel beams. We demonstrate that our method offers a strain sensitivity better than 2.5 × 10−4 and an accuracy of 1.5 × 10−3, competing with, or outperforming, the best existing methods with a simple and easy to use experimental setup.

Abstract: One of the emerging challenges in the field of 3D characterization of nanoparticles by electron tomography is to avoid degradation and deformation of the samples during the acquisition of a tilt series. In order to reduce the required electron dose, various undersampling approaches have been proposed. These methods include lowering the number of 2D projection images, reducing the probe current during the acquisition, and scanning a smaller number of pixels in the 2D images. A comparison is made between these approaches based on tilt series acquired for a gold nanoparticle.

Abstract: We present a first-principles computational study of CO and OH adsorption on non-polar ZnO (10¯10) surfaces doped with indium. The calculations were performed using a model ZnO slab. The position of the In dopants was varied from deep bulk-like layers to
the surface layers. It was established that the preferential location of the In atoms is at the surface by examining the dependence of
the defect formation energy as well as the surface energy on In location. The adsorption sites on the surface of ZnO and the energy
of adsorption of CO molecules and OH-species were determined in connection to In doping. It was found that OH has higher
bonding energy to the surface than CO. The presence of In atoms at the surface of ZnO is favorable for CO adsorption, resulting
in an elongation of the C-O bond and in charge transfer to the surface. The effect of CO and OH adsorption on the electronic
and conduction properties of surfaces was assessed. We conclude that In-doped ZnO surfaces should present a higher electronic
response upon adsorption of CO.

Abstract: The precipitation mechanism of the Q phase in Al-Mg-Si-Cu alloys has long been the subject of ambiguity and debate since its metastable phase (Q 0) has the same crystal structure and similar lattice parameters as its equilibrium counterparts. In the present work, the evolution of the Q 0 (Q) phase during aging is studied by combination of quantitative atomic-resolution scanning transmission electron microscopy and atom probe tomography. It was found that the transformation from the Q 0 to the Q phase involves changes of the occupancy of Al atoms in atomic columns of the Q 0 (Q) phase. The Al atoms incorporated in the Cu, Si and Mg columns are gradually released into the Al matrix, while mixing between Cu and Si atoms occurs in the Si columns. This transformation process is mainly attributed to the low lattice misfit of the equilibrium Q phase. Besides, the formation of various compositions of the Q phase is due to the different occupancy in the atomic columns of the Q phase. The occupancy changes in the columns of the Q phase are kinetically controlled and are strongly influenced by the alloy composition and aging temperature.

Abstract: Recently, the maximum a posteriori (MAP) probability rule has been proposed as an objective and quantitative method to detect atom columns and even single atoms from high-resolution high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) images. The method combines statistical parameter estimation and model-order selection using a Bayesian framework and has been shown to be especially useful for the analysis of the structure of beam-sensitive nanomaterials. In order to avoid beam damage, images of such materials are usually acquired using a limited incoming electron dose resulting in a low contrast-to-noise ratio (CNR) which makes visual inspection unreliable. This creates a need for an objective and quantitative approach. The present paper describes the methodology of the MAP probability rule, gives its step-by-step derivation and discusses its algorithmic implementation for atom column detection. In addition, simulation results are presented showing that the performance of the MAP probability rule to detect the correct number of atomic columns from HAADF STEM images is superior to that of other model-order selection criteria, including the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). Moreover, the MAP probability rule is used as a tool to evaluate the relation between STEM image quality measures and atom detectability resulting in the introduction of the so-called integrated CNR (ICNR) as a new image quality measure that better correlates with atom detectability than conventional measures such as signal-to-noise ratio (SNR) and CNR.

Abstract: When slow ions incident on a surface are neutralized, the excess potential energy is passed on to an electron inside the surface, leading to emission of secondary electrons. The microscopic description of this process, as
well as the calculation of the secondary electron yield, is a challenging problem due to its complexity as well
as its sensitivity to surface properties. One of the first quantitative descriptions was articulated in the 1950s by
Hagstrum, who based his calculation on a parametrization of the density of states of the material. In this paper, we
present a model for calculating the secondary electron yield, derived from Hagstrum’s initial approach. We use
first-principles density functional theory calculations to acquire the necessary input and introduce the concept of
electron cascades to Hagstrum’s model in order to improve the calculated spectra, as well as remove its reliance
on fitting parameters. We apply our model to He+ and Ne+ ions incident on Ge(111) and Si(111) and obtain
yield spectra that match closely to the experimental results of Hagstrum.

Abstract: Engineering morphology and size of CeO2-based nanostructures on a (sub)nanometer scale will greatly influence their performance; this is because of their high oxygen storage capacity and unique redox properties, which allow faster switching of the oxidation state between Ce4+ and Ce3+. Although tremendous research has been carried out on the shapecontrolled synthesis of CeO2, the characterization of these nanostructures at the atomic scale remains a major challenge and the origin of debate. The rapid developments of aberration-corrected transmission electron microscopy (AC-TEM) have pushed the resolution below 1 Å, both in TEM and in scanning transmission electron microscopy (STEM) mode. At present, not only morphology and structure, but also composition and electronic structure can be analyzed at an atomic scale, even in 3D. This review summarizes recent significant achievements using TEM/ STEM and associated spectroscopic techniques to study CeO2-based nanostructures and related catalytic phenomena. Recent results have shed light on the understanding of the different mechanisms. The potential and limitations, including future needs of various techniques, are discussed with recommendations to facilitate further developments of new and highly efficient CeO2-based nanostructures.

Abstract: Supported MnO2-based nanomaterials were fabricated on fluorine-doped tin oxide substrates by plasma enhanced-chemical vapor deposition (PE-CVD) between 100 °C and 400 °C, starting from a fluorinated Mn(II) diamine diketonate precursor. Growth experiments yielded -MnO2 nanosystems with hierarchical morphology tuneable from dendritic structures to quasi-1D nanosystems as a function of growth temperature, whose variation enabled also a concomitant tailoring of the system fluorine content, and of the optical absorption and band gap. Preliminary photocatalytic tests were aimed at the investigation of photoinduced hydrophilic (PH) and solid phase photocatalytic (PC) performances of the present nanomaterials, as well as at the photodegradation of Plasmocorinth B azo-dye aqueous solutions. The obtained findings highlighted an attractive system photoactivity even under visible light, finely tailored by fluorine content, morphological organization and optical properties of the prepared nanostructures. The results indicate that the synthesized MnO2 nanosystems have potential applications as advanced smart materials for anti-fogging/self-cleaning end uses and water purification.

Abstract: The atomic lensing model has been proposed as a promising method facilitating atom-counting in heterogeneous nanocrystals [1]. Here, image simulations will validate the model, which describes dynamical diffraction as a superposition of individual atoms focussing the incident electrons. It will be demonstrated that the model is reliable in the annular dark field regime for crystals having columns containing dozens of atoms. By using the principles of statistical detection theory, it will be shown that this model gives new opportunities for detecting compositional differences.

Abstract: The evolution of the uranium chemical state in uranium compounds, principally in the oxides, is of concern in the context of nuclear fuel degradation under storage and repository conditions, and in accident scenarios. The U–O system shows complicated phase relations between single-valence uranium dioxide (UO₂) and different mixed-valence compounds (<italic>e.g.</italic>U₄O₉, U₃O₇and U₃O₈). To try resolving the electronic structure associated with unique atomic positions, a combined application of diffraction and spectroscopic techniques, such as diffraction anomalous fine structure (DAFS), can be considered. Reported here is the application of two newly developed routines for assessing a DAFS data set, with the aim of refining the uranium X-ray dispersion corrections. High-resolution anomalous diffraction data were acquired from polycrystalline powder samples of UO₂(containing tetravalent uranium) and potassium uranate (KUO₃, containing pentavalent uranium) using synchrotron radiation in the vicinity of the U<italic>L</italic>₃edge (17.17 keV). Both routines are based on an iterative refinement of the dispersion corrections, but they differ in either using the intensity of a selection of reflections or doing a full-pattern (Rietveld method) refinement. The uranium dispersion corrections obtained using either method are in excellent agreement with each other, and they show in great detail the chemical shifts and differences in fine structure expected for tetravalent and pentavalent uranium. This approach may open new possibilities for the assessment of other, more complicated, materials such as mixed-valence compounds. Additionally, the DAFS methodology can offer a significant resource optimization because each data set contains both structural (diffraction) and chemical (spectroscopy) information, which can avoid the requirement to use multiple experimental stations at synchrotron sources.

Abstract: A thorough and quantitative understanding of the fate of excitons in covalent–organic frameworks (COFs) after photoexcitation is essential for their augmented optoelectronic and photocatalytic applications via precise structure tuning. The synthesis of a library of COFs having identical chemical backbone with impeded conjugation, but varied morphology and surface topography to study the effect of these physical properties on the photophysics of the materials is herein reported. The variation of crystallite size and surface topography substantified different aggregation pattern in the COFs, which leads to disparities in their photoexcitation and relaxation properties. Depending on aggregation, an inverse correlation between bulk luminescence decay time and exciton binding energy of the materials is perceived. Further transient absorption spectroscopic analysis confirms the presence of highly localized, immobile, Frenkel excitons (of diameter 0.3–0.5 nm) via an absence of annihilation at high density, most likely induced by structural torsion of the COF skeletons, which in turn preferentially relaxes via long‐lived (nanosecond to microsecond) excimer formation (in femtosecond scale) over direct emission. These insights underpin the importance of structural and topological design of COFs for their targeted use in photocatalysis.

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.

Abstract: Ruddlesden-Popper La????Sr2−????MnO4−???? materials are interesting symmetric solid oxide
fuel cell electrodes due to their good redox stability, mixed ionic and electronic conducting behavior and thermal expansion that matches well with common electrolytes. In reducing environments – as at a solid oxide fuel cell anode – the x = 0.5 member, i.e. La0.5Sr1.5MnO4−????, has a much higher total conductivity than compounds with a different La/Sr ratio, although all those compositions have the same K2NiF4-type I4/mmm structure. The origin for this conductivity difference is not yet known in literature. Now, a combination of in-situ and ex-situ 3D electron diffraction, high-resolution imaging, energy-dispersive X-ray analysis and electron energy-loss spectroscopy uncovered clear differences between x=0.25 and x=0.5 in the pristine structure, as well as in the transformations upon high-temperature reduction. In La0.5Sr1.5MnO4−????, Ruddlesden-Popper n=2 layer defects and an amorphous surface layer are present, but not in La0.25Sr1.75MnO4−????. After annealing at 700°C in 5% H2/Ar, La0.25Sr1.75MnO4−???? transforms to a tetragonal 2D incommensurately modulated structure with modulation vectors ⃗????1 = 0.2848(1) · (⃗????* +⃗????*) and ⃗????2 =0.2848(1) · (⃗????* – ⃗????*), whereas La0.5Sr1.5MnO4−???? only partially transforms to an orthorhombic 1D incommensurately modulated structure,
with ⃗???? = 0.318(2) · ⃗????*. Perovskite domains grow at the crystal edge at 700°C in 5%
H2 or vacuum, due to the higher La concentration on the surface compared to the bulk, which leads to a different thermodynamic equilibrium. Since it is known that a lower degree of oxygen vacancy ordering and a higher amount of perovskite blocks enhance oxygen mobility, those differences in defect structure and structural transformation upon reduction, might all contribute to the higher conductivity of La0.5Sr1.5MnO4−???? in solid oxide fuel cell anode conditions compared to other La/Sr ratios.

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.