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: Depth sectioning in high angular annular dark field scanning transmission electron microscopy is considered a candidate for three-dimensional characterization on the atomic scale. However at present the depth resolution is still far from the atomic level, due to strong limitations in the opening angle of the beam. In this paper we introduce a new, parameter based tomographic reconstruction algorithm that allows to make maximal use of the prior knowledge about the constituent atom types and the microscope settings, so as to retrieve the atomic positions and push the resolution to the atomic level in all three dimensions.

Abstract: We report an innovative method to explore the optimal experimental settings to detect light atoms from scanning transmission electron microscopy (STEM) images. Since light elements play a key role in many technologically important materials, such as lithium-battery devices or hydrogen storage applications, much effort has been made to optimize the STEM technique in order to detect light elements. Therefore, classical performance criteria, such as contrast or signal-to-noise ratio, are often discussed hereby aiming at improvements of the direct visual interpretability. However, when images are interpreted quantitatively, one needs an alternative criterion, which we derive based on statistical detection theory. Using realistic simulations of technologically important materials, we demonstrate the benefits of the proposed method and compare the results with existing approaches.

Abstract: Understanding nanostructures down to the atomic level is the key to optimizing the design of advancedmaterials with revolutionary novel properties. This requires characterization methods capable of quantifying the three-dimensional (3D) atomic structure with the highest possible precision. A successful approach to reach this goal is to count the number of atoms in each atomic column from 2D annular dark field scanning transmission electron microscopy images. To count atoms with single atom sensitivity, a minimum electron dose has been shown to be necessary, while on the other hand beam damage, induced by the high energy electrons, puts a limit on the tolerable dose. An important challenge is therefore to develop experimental strategies to optimize the electron dose by balancing atom-counting fidelity vs the risk of knock-on damage. To achieve this goal, a statistical framework combined with physics-based modeling of the dose-dependent processes is here proposed and experimentally verified. This model enables an investigator to theoretically predict, in advance of an experimental measurement, the optimal electron dose resulting in an unambiguous quantification of nanostructures in their native state with the highest attainable precision.

Abstract: Anti-phase boundaries (APBs) in an ordered CoPt alloy are planar defects which disturb the ordered structure in their vicinity and decrease the magnetic properties. However, it has not yet been clarified to what extend the APBs disturb the ordering. In this study, high-resolution HAADF-STEM images are statistically analysed based on the image intensities estimated by the statistical parameter estimation theory. In the procedure, averaging intensities, fitting the intensity profiles to specific functions, and assessment based on a statistical test are performed. As a result, the APBs in the stable CoPt are found to be characterised by two atomic planes, and a contrast transition range as well as the centre of an inclined APB is determined. These results show that the APBs are quite sharp and therefore may have no notable effect on the net magnetic properties due to their small volume fraction. (C) 2015 Elsevier B.V. All rights reserved.

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: In thispaperweinvestigatewhichprobesizemaximizesthethroughputwhenmeasuringtheradiusof nanoparticlesinhighangleannulardarkfieldscanningtransmissionelectronmicroscopy(HAADFSTEM). The sizeandthecorrespondingcurrentoftheelectronprobedeterminetheprecisionoftheestimateofa particlesradius.Maximizingthroughputmeansthatamaximumnumberofparticlesshouldbeimaged withinagiventimeframe,sothataprespecifiedprecisionisattained.WeshowthatBayesianstatistical experimentaldesignisaveryusefulapproachtodeterminetheoptimalprobesizeusingacertainamount of priorknowledgeaboutthesample.Thedependenceoftheoptimalprobesizeonthedetectorgeometry and thediameter,variabilityandatomicnumberoftheparticlesisinvestigated.Anexpressionforthe optimalprobesizeintheabsenceofanykindofpriorknowledgeaboutthespecimenisderivedaswell.

Abstract: Determining the three-dimensional (3D) arrangement of atoms in crystalline nanoparticles is important for nanometre-scale device engineering and also for applications involving nanoparticles, such as optoelectronics or catalysis. A nanoparticles physical and chemical properties are controlled by its exact 3D morphology, structure and composition1. Electron tomography enables the recovery of the shape of a nanoparticle from a series of projection images2, 3, 4. Although atomic-resolution electron microscopy has been feasible for nearly four decades, neither electron tomography nor any other experimental technique has yet demonstrated atomic resolution in three dimensions. Here we report the 3D reconstruction of a complex crystalline nanoparticle at atomic resolution. To achieve this, we combined aberration-corrected scanning transmission electron microscopy5, 6, 7, statistical parameter estimation theory8, 9 and discrete tomography10, 11. Unlike conventional electron tomography, only two images of the targeta silver nanoparticle embedded in an aluminium matrixare sufficient for the reconstruction when combined with available knowledge about the particles crystallographic structure. Additional projections confirm the reliability of the result. The results we present help close the gap between the atomic resolution achievable in two-dimensional electron micrographs and the coarser resolution that has hitherto been obtained by conventional electron tomography.

Abstract: Reconstructed exit waves are useful to quantify unknown structure parameters such as the position and composition of the atom columns at atomic scale. Existing techniques provide a complex wave in a flat plane which is close to the plane where the electrons leave the atom columns. However, due to local deviation in the flatness of the exit surface, there will be an offset between the plane of reconstruction and the actual exit of a specific atom column. Using the channelling theory, it has been shown that this defocus offset can in principle be determined atom column-by-atom column. As such, the surface roughness could be quantified at atomic scale. However, the outcome strongly depends on the initial plane of reconstruction especially in a crystalline structure. If this plane is further away from the true exit, the waves of the atom columns become delocalized and interfere mutually which strongly complicates the interpretation of the exit wave in terms of the local structure. In this paper, we will study the delocalization with defocus using the channelling theory in a more systematic way.

Abstract: Starting from the gas phase, small clusters can be produced and deposited with huge flexibility with regard to composition, materials choice and cluster size. Despite many advances in experimental characterization, a detailed morphology of such clusters is still lacking. Here we present an atomic scale observation as well as the dynamical behaviour of ultrasmall germanium clusters. Using quantitative scanning transmission electron microscopy in combination with ab initio calculations, we are able to characterize the transition between different equilibrium geometries of a germanium cluster consisting of less than 25 atoms. Seven-membered rings, trigonal prisms and some smaller subunits are identified as possible building blocks that stabilize the structure.

Abstract: The local structure of Bi4W2/3Mn1/3O8Cl is determined using quantitative transmission electron microscopy. The electron exit wave, which is closely related to the projected crystal potential, is reconstructed and used as a starting point for statistical parameter estimation. This method allows us to refine all atomic positions on a local scale, including those of the light atoms, with a precision in the picometer range. Using this method one is no longer restricted to the information limit of the electron microscope. Our results are in good agreement with x-ray powder diffraction data demonstrating the reliability of the method. Moreover, it will be shown that local effects can be interpreted using this approach.

Abstract: In order to fully exploit structure–property relations of nanomaterials, three-dimensional (3D) characterization at the atomic scale is often required. In recent years, the resolution of electron tomography has reached the atomic scale. However, such tomography typically requires several projection images demanding substantial electron dose. A newly developed alternative circumvents this by counting the number of atoms across a single projection. These atom counts can be used to create an initial atomic model with which an energy minimization can be applied to obtain a relaxed 3D reconstruction of the nanoparticle. Here, we compare, at the atomic scale, this single projection reconstruction approach with tomography and find an excellent agreement. This new approach allows for the characterization of beam-sensitive materials or where the acquisition of a tilt series is impossible. As an example, the utility is illustrated by the 3D atomic scale characterization of a nanodumbbell on an in situ heating holder of limited tilt range.

Abstract: In this paper, it has been investigated how to measure atom column positions as accurately and precisely as possible using a focal series of images. In theory, it is expected that the precision would considerably improve using a maximum likelihood estimator based on the full series of focal images. As such, the theoretical lower bound on the variances of the unknown atom column positions can be attained. However, this approach is numerically demanding. Therefore, maximum likelihood estimation has been compared with the results obtained by fitting a model to a reconstructed exit wave rather than to the full series of focal images. Hence, a real space model-based exit wave reconstruction technique based on the channelling theory is introduced. Simulations show that the reconstructed complex exit wave contains the same amount of information concerning the atom column positions as the full series of focal images. Only for thin samples, which act as weak phase objects, this information can be retrieved from the phase of the reconstructed complex exit wave.