Abstract: Hybrid pixel direct electron detectors are gaining popularity in electron microscopy due to their excellent properties. Some commercial cameras based on this technology are relatively affordable which makes them attractive tools for experimentation especially in combination with an SEM setup. To support this, a detector characterization (Modulation Transfer Function, Detective Quantum Efficiency) of an Advacam Minipix and Advacam Advapix detector in the 15–30 keV range was made. In the current work we present images of Point Spread Function, plots of MTF/DQE curves and values of DQE(0) for these detectors. At low beam currents, the silicon detector layer behaviour should be dominant, which could make these findings transferable to any other available detector based on either Medipix2, Timepix or Timepix3 provided the same detector layer is used.

Abstract: Electron energy loss spectroscopy (EELS) is a well established technique in electron microscopy that yields information on the elemental content of a sample in a very direct manner. One of the persisting limitations of EELS is the requirement for manual identification of core-loss edges and their corresponding elements. This can be especially bothersome in spectrum imaging, where a large amount of spectra are recorded when spatially scanning over a sample area. This paper introduces a synthetic dataset with 736,000 labeled EELS spectra, computed from available generalized oscillator strength tables, that represents 107 K, L, M or N core-loss edges and 80 chemical elements. Generic lifetime broadened peaks are used to mimic the fine structure due to band structure effects present in experimental core-loss edges. The proposed dataset is used to train and evaluate a series of neural network architectures, being a multilayer perceptron, a convolutional neural network, a U-Net, a residual neural network, a vision transformer and a compact convolutional transformer. An ensemble of neural networks is used to further increase performance. The ensemble network is used to demonstrate fully automated elemental mapping in a spectrum image, both by directly mapping the predicted elemental content and by using the predicted content as input for a physical model-based mapping.

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: Lanthanide-doped LiYF4 (Ln:YLF) is commonlyused fora broad variety of optical applications, such as lasing, photon upconversionand optical refrigeration. When synthesized as nanocrystals (NCs),this material is also of interest for biological applications andfundamental physical studies. Until now, it was unclear how Ln:YLFNCs grow from their ionic precursors into tetragonal NCs with a well-defined,bipyramidal shape and uniform dopant distribution. Here, we studythe nucleation and growth of ytterbium-doped LiYF4 (Yb:YLF),as a template for general Ln:YLF NC syntheses. We show that the formationof bipyramidal Yb:YLF NCs is a multistep process starting with theformation of amorphous Yb:YLF spheres. Over time, these spheres growvia Ostwald ripening and crystallize, resulting in bipyramidal Yb:YLFNCs. We further show that prolonged heating of the NCs results inthe degradation of the NCs, observed by the presence of large LiFcubes and small, irregular Yb:YLF NCs. Due to the similarity in chemicalnature of all lanthanide ions our work sheds light on the formationstages of Ln:YLF NCs in general.

Abstract: CsPbI3 is a promising perovskite material for photovoltaic applications in its photoactive perovskite or black phase. However, the material degrades to a photovoltaically inactive or yellow phase at room temperature. Various mitigation strategies are currently being developed to increase the lifetime of the black phase, many of which rely on inducing strains in the material that hinder the black-to-yellow phase transition. Physical insight into how these strategies exactly induce strain as well as knowledge of the spatial extent over which these strains impact the material is crucial to optimize these approaches but is still lacking. Herein, we combine machine learning potential-based molecular dynamics simulations with our in silico strain engineering approach to accurately quantify strained large-scale atomic structures on a nanosecond time scale. To this end, we first model the strain fields introduced by atomic substitutions as they form the most elementary strain sources. We demonstrate that the magnitude of the induced strain fields decays exponentially with the distance from the strain source, following a decay rate that is largely independent of the specific substitution. Second, we show that the total strain field induced by multiple strain sources can be predicted to an excellent approximation by summing the strain fields of each individual source. Finally, through a case study, we illustrate how this additive character allows us to explain how complex strain fields, induced by spatially extended strain sources, can be predicted by adequately combining the strain fields caused by local strain sources. Hence, the strain additivity proposed here can be adopted to further our insight into the complex strain behavior in perovskites and to design strain from the atomic level onward to enhance their sought-after phase stability.

Abstract: Out-of-equilibrium self-assembly of metal nanoparticles (NPs) has been devised using different
types of strategies and fuels, but the achievement of finite 3D structures with a controlled
morphology through this assembly mode is still rare. Here we used a spherical peptide-gold
superstructure (PAuSS) as a template to control the out-of-equilibrium self-assembly of Au NPs,
obtaining a transient 3D branched Au-nanoshell (BAuNS) stabilized by sodium dodecyl sulphate
(SDS). The BAuNS dismantled upon concentration gradient equilibration over time in the solution,
leading to NPs disassembly. Notably, BAuNS assembly and disassembly favoured temporary
interparticle plasmonic coupling, leading to a remarkable oscillation of their optical properties.

Abstract: Secondary electron emission is an important process that plays a significant role in several plasma‐related applications. As measuring the secondary electron yield experimentally is very challenging, quantitative modelling of this process to obtain reliable yield data is critical as input for higher‐scale simulations. Here, we build upon our previous work combining density functional theory calculations with a model originally developed by Hagstrum to extend its application to metallic surfaces. As plasmonic effects play a much more important role in the secondary electron emission mechanism for metals, we introduce an approach based on Poisson point processes to include both surface and bulk plasmon excitations to the process. The resulting model is able to reproduce the yield spectra of several available experimental results quite well but requires the introduction of global fitting parameters, which describe the strength of the plasmon interactions. Finally, we use an in‐house developed workflow to calculate the electron yield for a list of elemental surfaces spanning the periodic table to produce an extensive data set for the community and compare our results with more simplified approaches from the literature.

Abstract: The dehydrogenation of long-chain alkanes to olefins and alkylaromatics is a challenging endothermic reaction, typically requiring harsh conditions which can lead to low selectivity and coking. More favorable thermodynamics can be achieved by using a hydrogen acceptor, such as ethylene. In this work, the potential of heterogeneous platinum catalysts for the transfer dehydrogenation of long-chain alkanes is investigated, using ethylene as a convenient hydrogen acceptor. Pt/C and Pt–Sn/C catalysts were prepared<italic>via</italic>a simple polyol method and characterized with CO pulse chemisorption, HAADF-STEM, and EDX measurements. Conversion of ethylene was monitored<italic>via</italic>gas-phase FTIR, and distribution of liquid products was analyzed<italic>via</italic>GC-FID, GC-MS, and 1H-NMR. Compared to unpromoted Pt/C, Sn-promoted catalysts show lower initial reaction rates, but better resistance to catalyst deactivation, while increasing selectivity towards alkylaromatics. Both reaction products and ethylene were found to inhibit the reaction significantly. At 250 °C for 22 h, TON up to 28 and 86 mol per mol Pt were obtained for Pt/C and PtSn₂/C, respectively, with olefin selectivities of 94% and 53%. The remaining products were mainly unbranched alkylaromatics. These findings show the potential of simple heterogeneous catalysts in alkane transfer dehydrogenation, for the preparation of valuable olefins and alkylaromatics, or as an essential step in various tandem reactions.

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.

Abstract: 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.

Abstract: Cadmium sulfide (CdS)-based yellow pigments have been used in a number of early 20th century artworks, including The Scream series painted by Edvard Munch. Some of these unique paintings are threatened by the discoloration of these CdS-based yellow oil paints because of the oxidation of the original sulfides to sulfates. The experimental data obtained here prove that moisture and cadmium chloride compounds play a key role in promoting such oxidation. To clarify how these two factors effectively prompt the process, we studied the band alignment between CdS, CdCl2, and Cd-(OH)Cl as well as the radicals center dot OH and H3O center dot by density functional theory (DFT) methods. Our results show that a stack of several layers of Cd-(OH)Cl creates a pocket of positive holes at the Cl-terminated surface and a pocket of electrons at the OH-terminated surface by leading in a difference in ionization energy at both surfaces. The resulting band alignment indicates that Cd-(OH)Cl can indeed play the role of an oxidative catalyst for CdS in a moist environment, thus providing an explanation for the experimental evidence.

Abstract: The electroreduction of carbon dioxide (eCO2RR) to CO using Ag nanoparticles as an electrocatalyst is promising as an industrial carbon capture and utilization (CCU) technique to mitigate CO2 emissions. Nevertheless, the long-term stability of these Ag nanoparticles has been insufficient despite initial high Faradaic efficiencies and/or partial current densities. To improve the stability, we evaluated an up-scalable and easily tunable synthesis route to deposit low-weight percentages of Ag nanoparticles (NPs) on and into the framework of a nitrogen-doped ordered mesoporous carbon (NOMC) structure. By exploiting this so-called nanoparticle confinement strategy, the nanoparticle mobility under operation is strongly reduced. As a result, particle detachment and agglomeration, two of the most pronounced electrocatalytic degradation mechanisms, are (partially) blocked and catalyst durability is improved. Several synthesis parameters, such as the anchoring agent, the weight percentage of Ag NPs, and the type of carbonaceous support material, were modified in a controlled manner to evaluate their respective impact on the overall electrochemical performance, with a strong emphasis on operational stability. The resulting powders were evaluated through electrochemical and physicochemical characterization methods, including X-ray diffraction (XRD), N2-physisorption, Inductively coupled plasma mass spectrometry (ICP-MS), scanning electron microscopy (SEM), SEM-energy-dispersive X-ray spectroscopy (SEM-EDS), high-angle annular dark field scanning transmission electron microscopy (HAADF-STEM), STEM-EDS, electron tomography, and X-ray photoelectron spectroscopy (XPS). The optimized Ag/soft-NOMC catalysts showed both a promising selectivity (∼80%) and stability compared with commercial Ag NPs while decreasing the loading of the transition metal by more than 50%. The stability of both the 5 and 10 wt % Ag/soft-NOMC catalysts showed considerable improvements by anchoring the Ag NPs on and into a NOMC framework, resulting in a 267% improvement in CO selectivity after 72 h (despite initial losses) compared to commercial Ag NPs. These results demonstrate the promising strategy of anchoring Ag NPs to improve the CO selectivity during prolonged experiments due to the reduced mobility of the Ag NPs and thus enhanced stability.

Abstract: The three-dimensional size, morphology and distribution of Ni4Ti3 precipitates growing in binary Ni-rich Ni-Ti alloys have been investigated via a slice view procedure in a Dual-Beam FIB/SEM system, in order to better stress-free Ni50.8Ti49.2 alloy with all four variants of precipitates and a compressed Ni51Ti49 alloy with aligned precipitates in one family were studied. The Ni4Ti3 precipitates reach a volume fraction of 9.6% in the reconstructed region of the stress-free alloy and 4.3% in the compressed one. In both cases, the mean volume, specific surface area, sphericity and aspect ratio of the precipitates are calculated and the Pair Distribution Functions of the precipitates are obtained. It is shown that most precipitates in the stress-free sample grow larger and have a more lenticular shape, while those in the compressed sample are more cylindrical. Deviations from these ideal shapes reveal internal steps in the stress-free sample and lamellae formation in the compressed one.

Abstract: The properties of a clean superconductor with nanoscale dimensions are governed by quantum confinement of the electrons. This results in a spatially inhomogeneous superconducting condensate and in the formation of new Andreev-type quasiparticle states. These states are mainly located beyond regions where the superconducting condensate is enhanced. A numerical self-consistent solution of the Bogoliubov-de Gennes equations for a cylindrical metallic nanowire shows that these new Andreev-type states decrease the ratio of the energy gap to the critical temperature.

Abstract: The knowledge of the valence electron distribution is essential for understanding the properties of materials. However this information is difficult to obtain from HREM images because it is easily obscured by the large scattering contribution of core electrons and by the strong dynamical scattering process. In order to develop a sensitive method to extract the information of valence electrons, we have used an information transmission approach to describe the electron interaction with the object. The scattered electron wave is decomposed in a set of basic functions, which are the eigen functions of the Hamiltonian of the projected electrostatic object potential. Each basic function behaves as a communication channel that transfers the information of the object with its own transmission characteristic. By properly combining the components of the different channels, it is possible to design a scheme to extract the information of valence electron distribution from a series of exit waves. The method is described theoretically and demonstrated by means of computer simulations.