Abstract: 3D characterization of assemblies of nanoparticles is of great importance to determine their structure-property connection. Such investigations become increasingly more challenging when the assemblies become larger and more compact. In this paper, we propose an optimized approach for electron tomography to minimize artefacts related to beam broadening in High Angle Annular Dark-Field Scanning Transmission Electron Microscopy mode. These artefacts are typically present at one side of the reconstructed 3D data set for thick nanoparticle assemblies. To overcome this problem, we propose a procedure in which two tomographic tilt series of the same sample are acquired. After acquiring the first series, the sample is flipped over 180o, and a second tilt series is acquired. By merging the two reconstructions, blurring in the reconstructed volume is minimized. Next, this approach is combined with an advanced three-dimensional reconstruction algorithm yielding quantitative structural information. Here, the approach is applied to a thick and compact assembly of spherical Au nanoparticles, but the methodology can we used to investigate a broad range of samples.

Abstract: KBiNb2O7 was prepared from RbBiNb2O7 by a sequence of cation exchange reactions which first convert RbBiNb2O7 to LiBiNb2O7, before KBiNb2O7 is formed by a further K-for-Li cation exchange. A combination of neutron, synchrotron X-ray and electron diffraction data reveal that KBiNb2O7 adopts a polar, layered, perovskite structure (space group A11m) in which the BiNb2O7 layers are stacked in a (0, ½, z) arrangement, with the K+ cations located in half of the available 10-coordinate interlayer cation sites. The inversion symmetry of the phase is broken by a large displacement of the Bi3+ cations parallel to the y-axis. HAADF-STEM images reveal that KBiNb2O7 exhibits frequent stacking faults which convert the (0. ½, z) layer stacking to (½, 0, z) stacking and vice versa, essentially switching the x- and y-axes of the material. By fitting the complex diffraction peak shape of the SXRD data collected from KBiNb2O7 it is estimated that each layer has approximately an ~11% chance of being defective – a high level which is attributed to the lack of cooperative NbO6 tilting in the material, which limits the lattice strain associated with each fault.

Abstract: Chirality in inorganic nanoparticles and nanostructures has gained increasing scientific interest, because of the possibility to tune their ability to interact differently with left- and right-handed circularly polarized light. In some cases, the optical activity is hypothesized to originate from a chiral morphology of the nanomaterial. However, quantifying the degree of chirality in objects with sizes of tens of nanometers is far from straightforward. Electron tomography offers the possibility to faithfully retrieve the three-dimensional morphology of nanomaterials, but only a qualitative interpretation of the morphology of chiral nanoparticles has been possible so far. We introduce herein a methodology that enables us to quantify the helicity of complex chiral nanomaterials, based on the geometrical properties of a helix. We demonstrate that an analysis at the single particle level can provide significant insights into the origin of chiroptical properties.

Abstract: In this second part of a series we attempt to construct an empirical model that can mimick all experimental observations made regarding the role of an alternative interleaved scan pattern in STEM imaging on the beam damage in a specific zeolite sample. We make use of a 2D diffusion model that describes the dissipation of the deposited beam energy in the sequence of probe positions that are visited during the scan pattern. The diffusion process allows for the concept of trying to ‘outrun’ the beam damage by carefully tuning the dwell time and distance between consecutively visited probe positions. We add a non linear function to include a threshold effect and evaluate the accumulated damage in each part of the image as a function of scan pattern details. Together, these ingredients are able to describe qualitatively all aspects of the experimental data and provide us with a model that could guide a further optimisation towards even lower beam damage without lowering the applied electron dose. We deliberately remain vague on what is diffusing here which avoids introducing too many sample specific details. This provides hope that the model can be applied also in sample classes that were not yet studied in such great detail by adjusting higher level parameters: a sample dependent diffusion constant and damage threshold.

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: Structural analysis of metal clusters confined in nanoporous materials is typically performed by X-ray-driven techniques. Although X-ray analysis has proved its strength in the characterization of metal clusters, it provides averaged structural information. Therefore, we here present an alternative workflow for bringing the characterization of confined metal clusters towards the local scale. This workflow is based on the combination of aberration-corrected transmission electron microscopy (TEM), TEM image simulations, and powder X-ray diffraction (XRD) with advanced statistical techniques. In this manner, we were able to characterize the clustering of Pb atoms in Linde Type A (LTA) zeolites with Pb loadings as low as 5 wt%. Moreover, individual Pb clusters could be directly detected. The proposed methodology thus enables a local-scale characterization of confined metal clusters in zeolites. This is important for further elucidation of the connection between the structure and the physicochemical properties of such systems.

Abstract: In contrast to perfectly periodic crystals, materials with short-range order produce diffraction patterns that contain both Bragg reflections and diffuse scattering. To understand the influence of short-range order on material properties, current research focuses increasingly on the analysis of diffuse scattering. This article verifies the possibility to refine the short-range order parameters in submicrometre-sized crystals from diffuse scattering in single-crystal electron diffraction data. The approach was demonstrated on Li_1.2Ni_0.13Mn_0.54Co_0.13O₂, which is a state-of-the-art cathode material for lithium-ion batteries. The intensity distribution of the 1D diffuse scattering in the electron diffraction patterns of Li_1.2Ni_0.13Mn_0.54Co_0.13O₂depends on the number of stacking faults and twins in the crystal. A model of the disorder in Li_1.2Ni_0.13Mn_0.54Co_0.13O₂was developed and both the stacking fault probability and the percentage of the different twins in the crystal were refined using an evolutionary algorithm in<italic>DISCUS</italic>. The approach was applied on reciprocal space sections reconstructed from 3D electron diffraction data since they exhibit less dynamical effects compared with in-zone electron diffraction patterns. A good agreement was achieved between the calculated and the experimental intensity distribution of the diffuse scattering. The short-range order parameters in submicrometre-sized crystals can thus successfully be refined from the diffuse scattering in single-crystal electron diffraction data using an evolutionary algorithm in<italic>DISCUS</italic>.

Abstract: This paper investigates the possible benefits for counting atoms of different chemical nature when analysing multiple 2D scanning transmission electron microscopy (STEM) images resulting from independent annular dark field (ADF) detector regimes. To reach this goal, the principles of statistical detection theory are used to quantify the probability of error when determining the number of atoms in atomic columns consisting of multiple types of elements. In order to apply this theory, atom-counting is formulated as a statistical hypothesis test, where each hypothesis corresponds to a specific number of atoms of each atom type in an atomic column. The probability of error, which is limited by the unavoidable presence of electron counting noise, can then be computed from scattering-cross sections extracted from multiple ADF STEM images. Minimisation of the probability of error as a function of the inner and outer angles of a specified number of independent ADF collection regimes results in optimal experimental designs. Based on simulations of spherical Au@Ag and Au@Pt core–shell nanoparticles, we investigate how the combination of two non-overlapping detector regimes helps to improve the probability of error when unscrambling two types of atoms. In particular, the combination of a narrow low angle ADF detector with a detector formed by the remaining annular collection regime is found to be optimal. The benefit is more significant if the atomic number Z difference becomes larger. In
addition, we show the benefit of subdividing the detector regime into three collection areas for heterogeneous nanostructures based on a structure consisting of three types of elements, e.g., a mixture of Au, Ag and Al atoms. Finally, these results are compared with the probability of error resulting when one would ultimately use a pixelated 4D STEM detector and how this could help to further reduce the incident electron dose.

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: A robust and reproducible methodology to prepare stable inorganic nanoparticles with chiral morphology might hold the key to the practical utilization of these materials. We describe herein an optimized chiral growth method to prepare 4-fold twisted gold nanorods, where the amino acid cysteine is used as a dissymmetry inducer. Four tilted ridges were found to develop on the surface of single-crystal nanorods upon repeated reduction of HAuCl4, in the presence of cysteine as the chiral inducer and ascorbic acid as a reducing agent. From detailed electron microscopy analysis of the crystallographic structures, we propose that dissymmetry results from the development of chiral facets in the form of protrusions (tilted ridges) on the initial nanorods, eventually leading to a twisted shape. The role of cysteine is attributed to assisting enantioselective facet evolution, which is supported by density functional theory simulations of the surface energies, modified upon adsorption of the chiral molecule. The development of R-type and S-type chiral structures (small facets, terraces, or kinks) would thus be non-equal, removing the mirror symmetry of the Au NR and in turn resulting in a markedly chiral morphology with high plasmonic optical activity.

Abstract: A high dispersion of the active metal phase of transition metals on oxide supports is important when designing efficient heterogeneous catalysts. Besides nanoparticles, clusters and even single metal atoms can be attractive for a wide range of reactions. However, many industrially relevant catalytic transformations suffer from structure sensitivity, where reducing the size of the metal particles below a certain size substantially lowers catalytic performance. A case in point is the low activity of small cobalt nanoparticles in the hydrogenation of CO and CO2. Here we show how engineering of catalytic sites at the metal–oxide interface in cerium oxide–zirconium dioxide (ceria–zirconia)-supported cobalt can overcome this structure sensitivity. Few-atom cobalt clusters dispersed on 3 nm cobalt(II)-oxide particles stabilized by ceria–zirconia yielded a highly active CO2 methanation catalyst with a specific activity higher than that of larger particles under the same conditions.

Abstract: In this work, the magnetic properties of superparamagnetic iron oxide nanoparticles (SPIONs) submitted to an external magnetic field are studied using a Metropolis algorithm. The influence on the M(B) curves of the size distribution of the nanoparticles, of uniaxial anisotropy, and of dipolar interaction between the cores are examined, as well as the influence of drying the samples under a zero or non-zero magnetic field. It is shown that the anisotropy impacts the shape of the magnetization curves, which then deviate from a pure Langevin behaviour, whereas the dipolar interaction has no influence on the curves at 300 K for small particles (with a radius of 3 nm). The fitting of the magnetization curves of particles with magnetic anisotropy to a Langevin model (including a size distribution of the particles) can then lead to erroneous values of the distribution parameters. The simulation results are qualitatively compared to experimental results obtained for iron oxide nanoparticles (with a 3.21 nm median radius).

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.