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: It is very challenging to measure the chemical composition of hetero nanostructures in a reliable and quantitative manner. Here, we propose a novel and straightforward approach that can be used to quantify energy dispersive X-ray spectra acquired in a transmission electron microscope. Our method is based on a combination of electron tomography and the so-called zeta-factor technique. We will demonstrate the reliability of our approach as well as its applicability by investigating Au-Ag and Au-Pt hetero nanostructures. Given its simplicity, we expect that the method could become a new standard in the field of chemical characterization using electron microscopy. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: Zeogrids and Zeotiles are hierarchical materials built from assembled MFI zeolite precursor units. Permanent secondary porosity in these materials is obtained through self assembly of nanoparticles encountered in MFI zeolite synthesis in the presence of supramolecular templates. Hereon, the aggregated species are termed nanoslabs. Zeogrids are layered materials with lateral spacings between nanoslabs creating galleries qualifying as supermicropores. Zeotiles present a diversity of tridimensional nanoslab assemblies with mesopores. Zeotile-1, -4 and -6 are hexagonal mesostructures. Zeotile-1 has triangular and hexagonal channels; Zeotile-4 has hexagonal channels interconnected via slits. Zeotile-2 has a cubic structure with gyroid type mesoporosity. The behavior of Zeogrids and Zeotiles in adsorption, membrane and chromatographic separation and catalysis has been characterized and compared with zeolites and mesoporous materials derived from unstructured silica sources. Shape selectivity was detected via adsorption of n- and iso-alkanes. The mesoporosity of Zeotiles can be exploited in chromatographic separation of biomolecules. Zeotiles present attractive separation properties relevant to CO2 sequestration. Because of its facile synthesis procedure without hydrothermal steps Zeogrid is convenient for membrane synthesis. The performance of Zeogrid membrane in gas separation, nanofiltration and pervaporation is reported. In the Beckmann rearrangement of cyclohexanone oxime Zeogrids and Zeotiles display a catalytic activity characteristic of silicalite-1 zeolites. Introduction of acidity and redox catalytic activity can be achieved via incorporation of Al and Ti atoms in the nanoslabs during synthesis. Zeogrids are active in hydrocracking, catalytic cracking, alkylation and epoxidation reactions. Zeogrids and Zeotiles often behave differently from ordered mesoporous materials as well as from zeolites and present a valuable extension of the family of hierarchical silicate based materials.

Abstract: Affordable silver-polymer core-shell nanoparticles are prepared using the layer-by-layer (LbL) technique. The metallic silver core is encapsulated with an ultra-thin protective shell that prevents oxidation and clustering without compromising the plasmonic properties. The core-shell nanoparticles retain their plasmonic near field enhancement effect, as studied from finite element numerical simulations. Control over the shell thickness up to the sub-nanometer level is there for key. The particles are used to prepare a plasmonic Ag-TiO2 photocatalyst of which the gas phase photocatalytic activity is monitored over a period of four months. The described system outperforms pristine TiO2 and retains its plasmonic enhancement in contrast to TiO2 modified with bare silver nanoparticles. With this an important step is made toward the development of long-term stable plasmonic (photocatalytic) applications.

Abstract: A three-dimensional (3D) chemical characterization of nanomaterials can be obtained using tomography based on high angle annular dark field (HAADF) scanning transmission electron microscopy (STEM) or energy dispersive X-ray spectroscopy (EDS) STEM. These two complementary techniques have both advantages and disadvantages. The Z-contrast images have good image quality but lack robustness in the compositional analysis, while the elemental maps give more element-specific information, but at a low signal-to-noise ratio and a longer exposure time. Our aim is to combine these two types of complementary information in one single tomographic reconstruction process. Therefore, an imaging model is proposed combining both HAADF-STEM
and EDS-STEM. Based on this model, the elemental distributions can be reconstructed using both types of information simultaneously during the reconstruction process. The performance of the new technique is evaluated using simulated data and real experimental data. The results demonstrate that combining two imaging modalities leads to tomographic reconstructions with suppressed noise and enhanced contrast.

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: Large efforts have been made trying to understand the origin of the high catalytic activity of dealloyed nanoporous gold as a green catalyst for the selective promotion of chemical reactions at low temperatures. Residual silver, left in the sample after dealloying of a gold-silver alloy, has been shown to have a strong influence on the activity of the catalyst. But the question of how the silver is distributed within the porous structure has not finally been answered yet. We show by quantitative energy dispersive X-ray tomography measurements that silver forms clusters that are distributed irregularly, both on the surface and inside the ligaments building up the porous structure. Furthermore, we find that the role of the residual silver is ambiguous. Whereas CO oxidation is supported by more residual silver, methanol oxidation to methyl formate is hindered. Structural characterisation reveals larger ligaments and pores for decreasing residual silver concentration.

Abstract: Development of low-cost and high-performance oxygen evolution reaction catalysts is key to implementing polymer electrolyte membrane water electrolyzers for hydrogen production. Iridium-based oxides are the state-of-the-art acidic oxygen evolution reactio catalysts but still suffer from inadequate activity and stability, and iridium's scarcity motivates the discovery of catalysts with lower iridium loadings. Here we report a mass-selected iridium-tantalum oxide catalyst prepared by a magnetron-based cluster source with considerably reduced noble-metal loadings beyond a commercial IrO2 catalyst. A sensitive electrochemistry/mass-spectrometry instrument coupled with isotope labelling was employed to investigate the oxygen production rate under dynamic operating conditions to account for the occurrence of side reactions and quantify the number of surface active sites. Iridium-tantalum oxide nanoparticles smaller than 2 nm exhibit a mass activity of 1.2 ± 0.5 kA “g” _“Ir” ^“-1” and a turnover frequency of 2.3 ± 0.9 s-1 at 320 mV overpotential, which are two and four times higher than those of mass-selected IrO2, respectively. Density functional theory calculations reveal that special iridium coordinations and the lowered aqueous decomposition free energy might be responsible for the enhanced performance.

Abstract: Immunoassays exploiting magnetization dynamics of magnetic nanoparticles are highly promising for mix-and-measure, quantitative, and point-of-care diagnostics. However, how single-core magnetic nanoparticles can be employed to reduce particle concentration and concomitantly maximize assay sensitivity is not fully understood. Here, we design monodisperse Néel and Brownian relaxing magnetic nanocubes (MNCs) of different sizes and compositions. We provide insights into how to decouple physical properties of these MNCs to achieve ultrahigh sensitivity. We find that tri-component-based Zn0.06 Co0.80Fe2.14 O4 particles, with out-of-phase to initial magnetic susceptibility χ /χ ratio of 0.47 out of 0.50 for magnetically blocked ideal particles, show the ultrahigh magnetic sensitivity by providing rich magnetic particle spectroscopy (MPS) harmonics spectrum despite bearing lower saturation magnetization than di-component Zn0.1Fe2.9O4 having high saturation magnetization. The Zn0.06Co0.80Fe2.14O4 MNCs, coated with catechol-based polyethylene glycol ligands, measured by our benchtop MPS show three orders of magnitude better particle LOD than that of commercial nanoparticles of comparable size.

Abstract: The effect of thermal treatment and mechanical stress on the structural and photocatalytic properties of eight different (synthetic and commercial) photocatalysts has been thoroughly investigated. Different mesoporous Ti-based materials were prepared via surfactant based synthesis routes (e.g. Pluronic 123, CTMABr = Cetyltrimethylammonium bromide) or via template-free synthesis routes (e.g. trititanate nanotubes). Also, the stabilizing effect of the NaOH/NH4OH post-treatment on the templated mesoporous materials and their photocatalytic activity was investigated. Furthermore, the thermal and mechanical properties of commercially available titanium dioxides such as P25 Evonik® and Millenium PC500® were studied. The various photocatalysts were analyzed with N2-sorption, X-ray diffraction (XRD), high resolution transmission electron microscopy (HR-TEM), differential scanning calorimetry (DSC) and thermal gravimetric analysis (TGA) to obtain information concerning the specific surface area, pore volume, crystal structure, morphology, phase transitions, etc. In general, results show that the NaOH post-treatment leads to an increased control of the crystallization process during calcination resulting in a higher thermal stability, but at the same time diminishes the photocatalytic activity. Mesoporous materials in which pre-synthesized nanoparticles are used as titania source have the best mechanical stability whereas the mechanical stability of the nanotubes is the most limited. At increased temperatures and pressures, the tested commercial titanium dioxides lose their superior photocatalytic activity caused by a decreased accessibility of the active sites. The observed changes in adsorption capacities and photocatalytic activities cannot be assigned to one single phenomenon. In this respect, it shows the need to define a general/standard method to compare different photocatalysts. Furthermore, it is shown that the photocatalytic properties do not necessarily deteriorate under thermal stress, but can be improved due to crystallization, even though the initial material is (partially) destroyed. It is shown that the usefulness of a specific type of photocatalyst strongly depends on the application and the temperature/pressure to which it needs to resist.

Abstract: In this report, the possibility of Pt catalytic activity for the dissociation of hydrogen molecules and subsequent hydrogen adsorption on sucrose templated carbon at ambient temperature has been studied. In order to investigate Pt catalytic effect for hydrogen storage solely, 6.8 wt.% Pt-doped (Pt/TC) and pure templated carbon (TC) possessing almost identical specific surface area (SSA) and pore volume (Vp) have been successfully synthesized. Since both Pt/TC and TC shares for their textural properties (e.g. SSA and Vp), any difference of hydrogen adsorption characteristic and storage capacity can be ascribed to the presence of Pt nanoparticles. Both samples are characterized by various techniques such as powder Xray diffraction, ICP-OES, Raman spectroscopy, transmission electron microscopy, cryogenic thermal desorption spectroscopy, low-pressure high-resolution hydrogen and nitrogen BET and high-pressure hydrogen adsorption isotherms in a Sieverts' apparatus. By applying hydrogen and deuterium isotope mixture, cryogenic thermal desorption spectroscopy point to a Pt catalytic activity for the dissociation of hydrogen molecules. Furthermore, the hydrogen adsorption isotherms at RT indicate an enhancement of the initial hydrogen adsorption kinetics in Pt-doped system. However, the hydrogen storage capacity of Pt/TC exhibits a negligible enhancement with a strong hysteresis, suggesting no connection between the spillover effect and a feasible hydrogen storage enhancement. (C) 2013 Elsevier Inc. All rights reserved.

Abstract: The increasing need for precise determination of the atomic arrangement of non-periodic structures in materials design and the control of nanostructures explains the growing interest in quantitative transmission electron microscopy. The aim is to extract precise and accurate numbers for unknown structure parameters including atomic positions, chemical concentrations and atomic numbers. For this purpose, statistical parameter estimation theory has been shown to provide reliable results. In this theory, observations are considered purely as data planes, from which structure parameters have to be determined using a parametric model describing the images. As such, the positions of atom columns can be measured with a precision of the order of a few picometres, even though the resolution of the electron microscope is still one or two orders of magnitude larger. Moreover, small differences in average atomic number, which cannot be distinguished visually, can be quantified using high-angle annular dark-field scanning transmission electron microscopy images. In addition, this theory allows one to measure compositional changes at interfaces, to count atoms with single-atom sensitivity, and to reconstruct atomic structures in three dimensions. This feature article brings the reader up to date, summarizing the underlying theory and highlighting some of the recent applications of quantitative model-based transmisson electron microscopy.

Abstract: The concept of protecting groups, widely used in organic chemistry, has been applied for the synthesis of Au-silica Janus stars, in which gold branches protrude from one half of Au-silica Janus spheres. This configuration opens up new possibilities to apply the plasmonic properties of gold nanostars, as well as a variety of chemical functionalizations on the silica component.

Abstract: Gold nanoparticles are studied extensively due to their unique optical and catalytical properties. Their exact shape determines the properties and thereby the possible applications. Electron tomography is therefore often used to examine the three-dimensional (3D) shape of nanoparticles. However, since the acquisition of the experimental tilt series and the 3D reconstructions are very time consuming, it is difficult to obtain statistical results concerning the 3D shape of nanoparticles. Here, we propose a new approach for electron tomography that is based on artificial neural networks. The use of a new reconstruction approach enables us to reduce the number of projection images with a factor of 5 or more. The decrease in acquisition time of the tilt series and use of an efficient reconstruction algorithm allows us to examine a large amount of nanoparticles in order to retrieve statistical results concerning the 3D shape.

Abstract: Electron tomography is an essential imaging technique for the investigation of morphology and 3D structure of nanomaterials. This method, however, suffers from well-known missing wedge artifacts due to a restricted tilt range, which limits the objectiveness, repeatability and efficiency of quantitative structural analysis. Discrete tomography represents one of the promising reconstruction techniques for materials science, potentially capable of delivering higher fidelity reconstructions by exploiting the prior knowledge of the limited number of material compositions in a specimen. However, the application of discrete tomography to practical datasets remains a difficult task due to the underlying challenging mathematical problem. In practice, it is often hard to obtain consistent reconstructions from experimental datasets. In addition, numerous parameters need to be tuned manually, which can lead to bias and non-repeatability. In this paper, we present the application of a new
iterative reconstruction technique, named TVR-DART, for discrete electron tomography. The technique is capable of consistently delivering reconstructions with significantly reduced missing wedge artifacts for a variety of challenging data and imaging conditions, and can automatically estimate its key parameters. We describe the principles of the technique and apply it to datasets from three different types of samples acquired under diverse imaging modes. By further reducing the available tilt range and number of projections, we show that the
proposed technique can still produce consistent reconstructions with minimized missing wedge artifacts. This new development promises to provide the electron microscopy community with an easy-to-use and robust tool for high-fidelity 3D characterization of nanomaterials.