Abstract: The interaction among Au nanoparticles, their surface ligands and the solvent critically influences the properties of nanoparticles. Despite employing spectroscopic and scattering techniques to investigate their ensemble structure, a comprehensive understanding at the nanoscale remains elusive. Electron microscopy enables characterization of the local structure and composition but is limited by insufficient contrast, electron beam sensitivity and ultra-high vacuum, which prevent the investigation of dynamic aspects. Here we show that, by exploiting high-quality graphene liquid cells, we can overcome these limitations and investigate the structure of the ligand shell around the Au nanoparticles, as well as the ligand-Au interface in a liquid environment. Using this graphene liquid cell, we visualize the anisotropy, composition and dynamics of ligand distribution at the Au nanorod surface. Our results indicate a micellar model for the surfactant organisation. This work opens up a reliable and direct visualization of ligand distribution around colloidal nanoparticles.

Abstract: Introduction. Commensal Neisseria spp. are highly prevalent in the oropharynx as part of the healthy microbiome. N. meningitidis can colonise the oropharynx too from where it can cause invasive meningococcal disease. To identify N. meningitidis, clinical microbiology laboratories often rely on Matrix Assisted Laser Desorption/Ionisation Time of Flight Mass Spectrometry (MALDI-TOF MS).
Hypothesis/Gap statement. N. meningitidis may be misidentified by MALDI-TOF MS.
Aim. To conduct genomic surveillance of oropharyngeal Neisseria spp. in order to: (i) verify MALDI-TOF MS species identification, and (ii) characterize commensal Neisseria spp. genomes.
Methodology. We analysed whole genome sequence (WGS) data from 119 Neisseria spp. isolates from a surveillance programme for oropharyngeal Neisseria spp. in Belgium. Different species identification methods were compared: (i) MALDI-TOF MS, (ii) Ribosomal Multilocus Sequence Typing (rMLST) and (iii) rplF gene species identification. WGS data were used to further characterize Neisseria species found with supplementary analyses of Neisseria cinerea genomes.
Results. Based on genomic species identification, isolates from the oropharyngeal Neisseria surveilence study were composed of the following species: N. meningitidis (n=23), N. subflava (n=61), N. mucosa (n=15), N. oralis (n=8), N. cinerea (n=5), N. elongata (n=3), N. lactamica (n=2), N. bacilliformis (n=1) and N. polysaccharea (n=1). Of these 119 isolates, four isolates identified as N. meningitidis (n=3) and N. subflava (n=1) by MALDI-TOF MS, were determined to be N. polysaccharea (n=1), N. cinerea (n=2) and N. mucosa (n=1) by rMLST. Phylogenetic analyses revealed that N. cinerea isolates from the general population (n=3, cluster one) were distinct from those obtained from men who have sex with men (MSM, n=2, cluster two). The latter contained genomes misidentified as N. meningitidis using MALDI-TOF MS. These two N. cinerea clusters persisted after the inclusion of published N. cinerea WGS (n=42). Both N. cinerea clusters were further defined through pangenome and Average Nucleotide Identity (ANI) analyses.
Conclusion. This study provides insights into the importance of genomic genus-wide Neisseria surveillance studies to improve the characterization and identification of the Neisseria genus.

Abstract: The Bayesian genetic algorithm (BGA) is a powerful tool to reconstruct the 3D structure of mono-atomic single-crystalline metallic nanoparticles imaged using annular dark field scanning transmission electron microscopy. The number of atoms in a projected atomic column in the image is used as input to obtain an accurate and atomically precise reconstruction of the nanoparticle, taking prior knowledge and the finite precision of atom counting into account. However, as the number of parameters required to describe a nanoparticle with atomic detail rises quickly with the size of the studied particle, the computational costs of the BGA rise to prohibitively expensive levels. In this study, we investigate these computational costs and propose methods and control parameters for efficient application of the algorithm to nanoparticles of at least up to 10 nm in size.

Abstract: Electron tomography has become a commonly used tool to investigate the three-dimensional (3D) structure of nanomaterials, including colloidal nanoparticle assemblies. However, electron microscopy is typically done under high-vacuum conditions, requiring sample preparation for assemblies obtained by wet colloid chemistry methods. This involves solvent evaporation and deposition on a solid support, which consistently alters the nanoparticle organization. Here, we suggest using electron tomography to study nanoparticle assemblies in their original colloidal liquid environment. To address the challenges related to electron tomography in liquid, we devise a method that combines fast data acquisition in a commercial liquid-cell with a dedicated alignment and reconstruction workflow. We present the advantages of this methodology in accurately characterizing two different systems. 3D reconstructions of assemblies comprising polystyrene-capped Au nanoparticles encapsulated in polymeric shells reveal less compact and more distorted configurations for experiments performed in a liquid medium compared to their dried counterparts. A similar expanded trend can be observed in quantitative analysis of the surface-to-surface distances of self-assembled Au nanorods in water rather than in a vacuum, which agrees with bulk measurements. This study, therefore, emphasizes the importance of developing high-resolution characterization tools that preserve the native environment of colloidal nanostructures.

Abstract: Determining temperature changes at the heating site to accurately control thermal treatments has been a major goal in the field of nanothermometry. In this study, we address the need to effectively monitor local temperature during the application of photothermal therapies, which is essential to prevent uncontrolled heating induced by nanoparticle sensitizers used in such treatments. For this purpose, we developed a synthetic protocol to produce a nanocomposite probe that allows local photothermal heating and simultaneous in situ optical nanothermometry, within the biological transparency windows. The nanocomposite material comprises gold nanorods for light-to-heat conversion and neodymium (Nd3+)-based nanoparticles for local temperature monitoring. An inert spacer made of mesoporous silica provides a core-shell structure and ensures uniform separation between both functionalities to prevent photoluminescence quenching. By using an 808 nm laser as the source for both heating and photoluminescence excitation, we demonstrate a direct correlation between local temperature and near infrared Nd3+ emission intensities, thereby providing precise local temperature monitoring. Different levels of local heating were studied by varying the incident laser power, resulting in a maximum temperature increase of 47 °C detected with the nanothermometers. Albeit presented here as a proof of concept, this concept can be translated to the design of materials for photothermal therapy.

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: Electron tomography is currently a versatile tool to investigate the connection between the structure and properties of nanomaterials. However, a quantitative interpretation of electron tomography results is still far from straightforward. Especially accurate quantification of pore-space is hampered by artifacts introduced in all steps of the processing chain, i.e., acquisition, reconstruction, segmentation and quantification. Furthermore, most common approaches require subjective manual user input. In this paper, the PORES algorithm POre REconstruction and Segmentation is introduced; it is a tailor-made, integral approach, for the reconstruction, segmentation, and quantification of porous nanomaterials. The PORES processing chain starts by calculating a reconstruction with a nanoporous-specific reconstruction algorithm: the Simultaneous Update of Pore Pixels by iterative REconstruction and Simple Segmentation algorithm (SUPPRESS). It classifies the interior region to the pores during reconstruction, while reconstructing the remaining region by reducing the error with respect to the acquired electron microscopy data. The SUPPRESS reconstruction can be directly plugged into the remaining processing chain of the PORES algorithm, resulting in accurate individual pore quantification and full sample pore statistics. The proposed approach was extensively validated on both simulated and experimental data, indicating its ability to generate accurate statistics of nanoporous materials.

Abstract: The field of discrete tomography focuses on the reconstruction of samples that consist of only a few different materials. Ideally, a three-dimensional (3D) reconstruction of such a sample should contain only one grey level for each of the compositions in the sample. By exploiting this property in the reconstruction algorithm, either the quality of the reconstruction can be improved significantly, or the number of required projection images can be reduced. The discrete reconstruction typically contains fewer artifacts and does not have to be segmented, as it already contains one grey level for each composition. Recently, a new algorithm, called discrete algebraic reconstruction technique (DART), has been proposed that can be used effectively on experimental electron tomography datasets. In this paper, we propose discrete tomography as a general reconstruction method for electron tomography in materials science. We describe the basic principles of DART and show that it can be applied successfully to three different types of samples, consisting of embedded ErSi2 nanocrystals, a carbon nanotube grown from a catalyst particle and a single gold nanoparticle, respectively.

Abstract: Accurate segmentation of nanoparticles within various matrix materials is a difficult problem in electron tomography. Due to artifacts related to image series acquisition and reconstruction, global thresholding of reconstructions computed by established algorithms, such as weighted backprojection or SIRT, may result in unreliable and subjective segmentations. In this paper, we introduce the Partially Discrete Algebraic Reconstruction Technique (PDART) for computing accurate segmentations of dense nanoparticles of constant composition. The particles are segmented directly by the reconstruction algorithm, while the surrounding regions are reconstructed using continuously varying gray levels. As no properties are assumed for the other compositions of the sample, the technique can be applied to any sample where dense nanoparticles must be segmented, regardless of the surrounding compositions. For both experimental and simulated data, it is shown that PDART yields significantly more accurate segmentations than those obtained by optimal global thresholding of the SIRT reconstruction.

Abstract: In this work, the simultaneous iterative reconstruction technique (SIRT), the total variation minimization (TVM) reconstruction technique and the discrete algebraic reconstruction technique (DART) for electron tomography are compared and the advantages and disadvantages are discussed. Furthermore, we describe how the result of a three dimensional (3D) reconstruction based on TVM can provide objective information that is needed as the input for a DART reconstruction. This approach results in a tomographic reconstruction of which the segmentation is carried out in an objective manner.

Abstract: An efficient procedure and computer program are outlined for fitting numerical X-ray and electron scattering factors with the correct inclusion of all physical constraints. The numerical electron scattering factors have been parameterized using five analytic non-relativistic hydrogen electron scattering factors as basis functions for 103 neutral atoms of the periodic table. The inclusion of the correct physical constraints in the electron scattering factor and its derived quantities allows the use of the new parameterization in different fields. In terms of quality of the fit, the proposed parameterization of the electron scattering factor is one order of magnitude better than the previous analytic fittings.

Abstract: Nano-sized ZnO particles with a narrow size distribution and high crystallinity were prepared from aqueous solutions with high concentrations of Zn2+ containing salts and citric acid in a conventional spray pyrolysis setup. Structure, morphology and size of the produced material were compared to ZnO material produced by simple spray pyrolysis of zinc nitrates in the same experimental setup. Using transmission electron microscopy and electron tomography it has been shown that citric acid-assisted spray pyrolysed material is made up of micron sized secondary particles comprising a shell of lightly agglomerated, monocrystalline primary ZnO nanoparticles with sizes in the 2030 nm range, separable by a simple ultrasonic treatment step.

Abstract: Solution derived La2Zr2O7 films have drawn much attention for potential applications as thermal barriers or low-cost buffer layers for coated conductor technology. Annealing and coating parameters strongly affect the microstructure of La2Zr2O7, but different film processing methods can yield similar microstructural features such as nanovoids and nanometer-sized La2Zr2O7 grains. Nanoporosity is a typical feature found in such films and the implications for the functionality of the films are investigated by a combination of scanning transmission electron microscopy (STEM), electron energy-loss spectroscopy (EELS) and quantitative electron tomography. Chemical solution based La2Zr2O7 films deposited on flexible Ni5 at.%W substrates with a {100}lang001rang biaxial texture were prepared for an in-depth characterization. A sponge-like structure composed of nanometer-sized voids is revealed by high-angle annular dark-field scanning transmission electron microscopy in combination with electron tomography. A three-dimensional quantification of nanovoids in the La2Zr2O7 film is obtained on a local scale. Mostly non-interconnected highly faceted nanovoids compromise more than one-fifth of the investigated sample volume. The diffusion barrier efficiency of a 170 nm thick La2Zr2O7 film is investigated by STEM-EELS, yielding a 1.8 ± 0.2 nm oxide layer beyond which no significant nickel diffusion can be detected and intermixing is observed. This is of particular significance for the functionality of YBa2Cu3O7 − δ coated conductor architectures based on solution derived La2Zr2O7 films as diffusion barriers.

Abstract: In materials science, high angle annular dark field scanning transmission electron microscopy is often used for tomography at the nanometer scale. In this work, it is shown that a thickness dependent, non-linear damping of the recorded intensities occurs. This results in an underestimated intensity in the interior of reconstructions of homogeneous particles, which is known as the cupping artifact. In this paper, this non-linear effect is demonstrated in experimental images taken under common conditions and is reproduced with a numerical simulation. Furthermore, an analytical derivation shows that these non-linearities can be inverted if the imaging is done quantitatively, thus preventing cupping in the reconstruction.

Abstract: This paper is the second part of a two-part paper on direct structure inversion from exit waves. In the first part, a method has been proposed to quantitatively determine structure parameters with atomic resolution such as atom column positions, surface profile and the number of atoms in the atom columns. In this part, the theory will be demonstrated by means of a Au[110] exit wave reconstructed from a set of focal-series images. The procedures to analyze the experimentally reconstructed exit wave in terms of quantitative structure information are described in detail.