Abstract: In this study, the interaction between cells and micron-sized paramagnetic iron oxide (MPIO) particles was investigated by characterizing MPIO in their original state, and after cellular uptake in vitro as well as in vivo. Moreover, MPIO in the olfactory bulb were studied 9months after injection. Using various imaging techniques, cell-MPIO interactions were investigated with increasing spatial resolution. Live cell confocal microscopy demonstrated that MPIO co-localize with lysosomes after in vitro cellular uptake. In more detail, a membrane surrounding the MPIO was observed by high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM). Following MPIO uptake in vivo, the same cell-MPIO interaction was observed by HAADF-STEM in the subventricular zone at 1week and in the olfactory bulb at 9months after MPIO injection. These findings provide proof for the current hypothesis that MPIO are internalized by the cell through endocytosis. The results also show MPIO are not biodegradable, even after 9months in the brain. Moreover, they show the possibility of HAADF-STEM generating information on the labeled cell as well as on the MPIO. In summary, the methodology presented here provides a systematic route to investigate the interaction between cells and nanoparticles from the micrometer level down to the nanometer level and beyond. Copyright (c) 2014 John Wiley Sons, Ltd.

Abstract: Getting the picture: The investigation of 100 year old chrome yellow paint by transmission electron microscopy and spectroscopy has led to the identification of four types of coreshell particles. This nanoscale investigation has allowed a mechanism to be proposed for the darkening of some bright yellow colors in Van Gogh's paintings (e.g. in Falling leaves (Les Alyscamps), 1888).

Abstract: Earth-abundant and eco-friendly manganese oxides are promising platforms for the oxygen evolution reaction (OER) in water electrolysis. Herein, a versatile and potentially scalable route to gold-decorated manganese oxide-based OER electrocatalysts is reported. In particular, MnxOy(MnO2, Mn2O3) host matrices are grown on conductive glasses by plasma assisted-chemical vapor deposition (PA-CVD), and subsequently functionalized with gold nanoparticles (guest) as OER activators by radio frequency (RF)-sputtering. The final selective obtainment of MnO2- or Mn2O3-based systems is then enabled by annealing under oxidizing or inert atmosphere, respectively. A detailed material characterization evidences the formation of high-purity Mn(x)O(y)dendritic nanostructures with an open morphology and an efficient guest dispersion into the host matrices. The tailoring of Mn(x)O(y)phase composition and host-guest interactions has a remarkable influence on OER activity yielding, for the best performing Au/Mn(2)O(3)system, a current density of approximate to 5 mA cm(-2)at 1.65 V versus the reversible hydrogen electrode (RHE) and an overpotential close to 300 mV at 1 mA cm(-2). Such results, comparing favorably with literature data on manganese oxide-based materials, highlight the importance of compositional control, as well as of surface and interface engineering, to develop low-cost and efficient anode nanocatalysts for water splitting applications.

Abstract: The electronic phase behavior and functionality of interfaces and surfaces in complex materials are strongly correlated to chemical composition profiles, stoichiometry and intermixing. Here a novel analysis scheme for resonant X-ray reflectivity maps is introduced to determine such profiles, which is element specific and non-destructive, and which exhibits atomic-layer resolution and a probing depth of hundreds of nanometers.

Abstract: Ferroelectric domain formation is an essential feature in ferroelectric thin films. These domains and domain walls can be manipulated depending on the growth conditions. In rhombohedral BiFeO3 thin films, the ordering of the domains and the presence of specific types of domain walls play a crucial role in attaining unique ferroelectric and magnetic properties. In this study, controlled ordering of domains in BiFeO3 film is presented, as well as a controlled selectivity between two types of domain walls is presented, i.e., 71° and 109°, by modifying the substrate termination. The experiments on two different substrates, namely SrTiO3 and TbScO3, strongly indicate that the domain selectivity is determined by the growth kinetics of the initial BiFeO3 layers.

Abstract: Control of localized metal-organic framework (MOF) thin film formation is a challenge. Zeolitic imidazolate frameworks (ZIFs) are an important sub-class of MOFs based on transition metals and imidazolate linkers. Continuous coatings of intergrown ZIF crystals require high rates of heterogeneous nucleation. In this work, substrates coated with zinc oxide layers are used, obtained by atomic layer deposition (ALD) or by magnetron sputtering, to provide the Zn2+ ions required for nucleation and localized growth of ZIF-8 films ([Zn(mim)(2)]; Hmim = 2-methylimidazolate). The obtained ZIF-8 films reveal the expected microporosity, as deduced from methanol adsorption studies using an environmentally controlled quartz crystal microbalance (QCM) and comparison with bulk ZIF-8 reference data. The concept is transferable to other MOFs, and is applied to the formation of [Al(OH)(1,4-ndc)](n) (ndc = naphtalenedicarboxylate) thin films derived from Al2O3 nanolayers.

Abstract: Perovskite oxide heteroepitaxy receives much attention because of the possibility to combine the diverse functionalities of perovskite oxide building blocks. A general boundary condition for the epitaxy is the presence of polar discontinuities at heterointerfaces. These polar discontinuities result in reconstructions, often creating new functionalities at the interface. However, for a significant number of materials these reconstructions are unwanted as they alter the intrinsic materials properties at the interface. Therefore, a strategy to eliminate this reconstruction of the polar discontinuity at the interfaces is required. We show that the use of compositional interface engineering can prevent the reconstruction at the La0.67Sr0.33MnO3/SrTiO3 (LSMO/STO) interface. The polar discontinuity at this interface can be removed by the insertion of a single La0.33Sr0.67O layer, resulting in improved interface magnetization and electrical conductivity.

Abstract: Microtwin sequences in Ni66Al34 martensite plates of different size were investigated by electron microscopy. Although mostly irregular sequences were observed an average twin width w can be determined which increases with twin length L following the expected relation w ~ sqrt(L). High resolution electron microscopy was used to study the twin branching close to the plate boundaries and an atomic model for the branching of a microtwin and the changes in twin thickness is suggested

Abstract: We have evaluated the resistance of carbon nanotubes (CNTs) grown at a CMOS-compatible temperature using a realistic integration scheme. The structural analysis of the CNTs by transmission electron microscopy (TEM) showed that the degree of graphitization decreased significantly when the growth temperature was decreased from 540 to 400 °C. The CNTs were integrated to form 150-nm-diameter vertical interconnects between a TiN layer and Cu metal trenches on 200 mm full wafers. Wafers with CNTs grown at low temperature were found to have a lower single-contact resistance than those produced at high temperatures. Thickness measurements showed that the low contact resistance is a result of small contact height. This height dependence is masking the impact of CNT graphitization quality on resistance. When benchmarking our results with data from the literature, a relationship between resistivity and growth temperature cannot be found for CNT-based vertical interconnects.

Abstract: Inelastic excitation as exploited in Electron Energy Loss Spectroscopy (EELS) contains a rich source of information that is revealed in the scattering process. To accurately quantify core-loss EELS, it is common practice to fit the observed spectrum with scattering cross-sections calculated using experimental parameters and a Generalized Oscillator Strength (GOS) database [1].   The GOS is computed using Fermi’s Golden Rule and orbitals of bound and excited states. Previously, the GOS was based on Hartree-Fock solutions [2], but more recently Density Functional Theory (DFT) has been used [3]. In this work, we have chosen to use the Dirac equation to incorporate relativistic effects and have performed calculations using Flexible Atomic Code (FAC) [4]. This repository contains a tabulated GOS database based on Dirac solutions for computing double differential cross-sections under experimental conditions.   We hope the Dirac-based GOS database can benefit the EELS community for both academic use and industry integration.   Database Details: – Covers all elements (Z: 1-108) and all edges – Large energy range: 0.01 – 4000 eV – Large momentum range: 0.05 -50 Å-1 – Fine log sampling: 128 points for energy and 256 points for momentum – Data format: GOSH [3]   Calculation Details: – Single atoms only; solid-state effects are not considered – Unoccupied states before continuum states of ionization are not considered; no fine structure – Plane Wave Born Approximation – Frozen Core Approximation is employed; electrostatic potential remains unchanged for orthogonal states when – core-shell electron is excited – Self-consistent Dirac–Fock–Slater iteration is used for Dirac calculations; Local Density Approximation is assumed for electron exchange interactions; continuum states are normalized against asymptotic form at large distances – Both large and small component contributions of Dirac solutions are included in GOS – Final state contributions are included until the contribution of the previous three states falls below 0.1%. A convergence log is provided for reference.   Version 1.1 release note: – Update to be consistent with GOSH data format [3], all the edges are now within a single hdf5 file. A notable change in particular, the sampling in momentum is in 1/m, instead of previously in 1/Å. Great thanks to Gulio Guzzinati for his suggestions and sending conversion script.  Version 1.2 release note: – Add “File Type / File version” information [1] Verbeeck, J., and S. Van Aert. Ultramicroscopy 101.2-4 (2004): 207-224. [2] Leapman, R. D., P. Rez, and D. F. Mayers. The Journal of Chemical Physics 72.2 (1980): 1232-1243. [3] Segger, L, Guzzinati, G, & Kohl, H. Zenodo (2023). doi:10.5281/zenodo.7645765 [4] Gu, M. F. Canadian Journal of Physics 86(5) (2008): 675-689.

Abstract: We present a large dataset containing simulated core-loss electron energy loss spectroscopy (EELS) spectra with the elemental content as ground-truth labels. Additionally we present some neural networks trained on this data for element identification.  The simulated dataset contains zero padded core-loss spectra from 0 to 3072 eV, which represents 107 core-loss edges through all 80 elements from Be up to Bi. The core-loss edges are calculated from the generalised oscillator strength (GOS) database presented by Zhang et al.[1] Generic fine structures using lifetime broadened peaks are used to imitate fine structure due to solid-state effects in experimental spectra. Generic low-loss regions are used to imitate the effect of multiple scattering. Each spectrum contains at least one edge of a given query element and possibly additional edges depending on samples drawn from The Materials Project [2]. The dataset contains for each of the 80 elements: 7000 training spectra, 1500 test spectra, 600 validation spectra and 100 spectra representing only the query element. This results in a total 736 000 labeled spectra. Code on how to  – read the simulated data – transform HDF5 format to TFRecord format – train and evaluate neural networks using the simulated data – use the trained networks for automated element identification is available on GitHub at arnoannys/EELS_ID A full report on the simulation of the dataset and the training and evaluation of the neural networks can be found at:                    Annys, A., Jannis, D. & Verbeeck, J. Deep learning for automated materials characterisation in core-loss electron energy loss spectroscopy. Sci Rep 13, 13724 (2023). https://doi.org/10.1038/s41598-023-40943-7 [1] Zezhong Zhang, Ivan Lobato, Daen Jannis, Johan Verbeeck, Sandra Van Aert, & Peter Nellist. (2023). Generalised oscillator strength for core-shell electron excitation by fast electrons based on Dirac solutions (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7729585 [2] Anubhav Jain, Shyue Ping Ong, Geoffroy Hautier, Wei Chen, William Davidson Richards, Stephen Dacek, Shreyas Cholia, Dan Gunter, David Skinner, Gerbrand Ceder, Kristin A. Persson; Commentary: The Materials Project: A materials genome approach to accelerating materials innovation. APL Mater 1 July 2013; 1 (1): 011002. [https://doi.org/10.1063/1.4812323](https://doi.org/10.1063/1.4812323)

Abstract: We placed crystals of different compounds to explore the possibility of fingerprinting them through EELS. Here are representative datasets of 7 different compounds: b-cyclodextrin hexacarboxy cyclohexane tannin TH-15 peptide TH-27 peptide two different forms of piroxicam The datasets were collected at EMAT, using a monochromated FEI Titan3 TEM, within the scope of an EUSMI request. More information as well as analysis methodologies adopted for the data are detailed in the paper: Das et al. “Reliable Characterization of Organic & Pharmaceutical Compounds with High Resolution Monochromated EEL Spectroscopy”, Polymers 2020, 12(7), 1434.