Abstract: Despite the natural abundance and promising properties of Si, there are few examples of crystalline Si-based catalysts. Here, the authors report an epitaxial growth method to construct Co single atoms on Si for light driven CO2 reduction to syngas. Improving the dispersion of active sites simultaneous with the efficient harvest of photons is a key priority for photocatalysis. Crystalline silicon is abundant on Earth and has a suitable bandgap. However, silicon-based photocatalysts combined with metal elements has proved challenging due to silicon's rigid crystal structure and high formation energy. Here we report a solid-state chemistry that produces crystalline silicon with well-dispersed Co atoms. Isolated Co sites in silicon are obtained through the in-situ formation of CoSi2 intermediate nanodomains that function as seeds, leading to the production of Co-incorporating silicon nanocrystals at the CoSi2/Si epitaxial interface. As a result, cobalt-on-silicon single-atom catalysts achieve an external quantum efficiency of 10% for CO2-to-syngas conversion, with CO and H-2 yields of 4.7 mol g((Co))(-1) and 4.4 mol g((Co))(-1), respectively. Moreover, the H-2/CO ratio is tunable between 0.8 and 2. This photocatalyst also achieves a corresponding turnover number of 2 x 10(4) for visible-light-driven CO2 reduction over 6 h, which is over ten times higher than previously reported single-atom photocatalysts.

Abstract: Sample holders for transmission electron microscopy (TEM) based on micro-electro-mechanical systems (MEMS) have recently become popular for investigating the behavior of nanomaterials under in situ or environmental conditions. The accuracy and reproducibility of these in situ holders are essential to ensure the reliability of experimental results. In addition, the uniformity of an applied temperature trigger across the MEMS chip is a crucial parameter. In this work, it is measured the temperature homogeneity of MEMS-based heating sample supports by locally analyzing the dynamics of heat-induced alloying of Au@Ag nanoparticles located in different regions of the support through quantitative fast high-angle annular dark-field scanning TEM tomography. These results demonstrate the superior temperature homogeneity of a microheater design based on a heating element shaped as a circular spiral with a width decreasing outwards compared to a double spiral-shaped designed microheater. The proposed approach to measure the local temperature homogeneity based on the thermal properties of bimetallic nanoparticles will support the future development of MEMS-based heating supports with improved thermal properties and in situ studies where high precision in the temperature at a certain position is required. This schematic delineates an approach to quantifying potential localized temperature deviation within a nanochip. Employing two comparable nanoparticles as thermal probes in discrete nanochip regions, the alloying kinetics of these nanoparticles are monitorable using in situ quantitative high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) tomography, thus enabling the precise estimation of local temperature deviations.image

Abstract: A series of gold-ruthenium bimetallic catalysts of increasing Au:Ru molar ratios supported on a Ce0.62Zr0.38O2 mixed oxide are prepared and their structural and chemical features characterized by a combination of macroscopic and atomic-scale techniques based on scanning transmission electron microscopy. The influence of the temperature of the final reduction treatment used as activation step (350-700 degrees C range) is also investigated. The preparation method used allows catalysts to be successfully prepared where a major fraction of the metal nanoparticles is in the size range below 5 nm. The structural complexities characteristic of this type of catalysts are evidenced, as well as the capabilities and limitations of both the macroscopic and microscopic techniques in the characterization of the system of metal nanoparticles. A positive influence of the addition of Ru on both the resistance against sintering and the catalytic performance of the starting supported Au catalyst is evidenced.

Abstract: Bifunctionality is a key feature of many industrial catalysts, supported metal clusters and particles in particular, and the development of such catalysts for the CO2 reduction reaction (CO2RR) to hydrocarbons and alcohols is gaining traction in light of recent advancements in the field. Carbon-supported Cu nanoparticles are suitable candidates for integration in the state-of-the-art reaction interfaces, and here, we propose, synthesize, and evaluate a bifunctional Ni–N-doped-C-supported Cu electrocatalyst, in which the support possesses active sites for selective CO2 conversion to CO and Cu nanoparticles catalyze either the direct CO2 or CO reduction to hydrocarbons. In this work, we introduce the scientific rationale behind the concept, its applicability, and the challenges with regard to the catalyst. From the practical aspect, the deposition of Cu nanoparticles onto carbon black and Ni–N–C supports via an ammonia-driven deposition precipitation method is reported and explored in more detail using X-ray diffraction, thermogravimetric analysis, and hydrogen temperature-programmed reduction. High-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and energy-dispersive X-ray spectroscopy (EDXS) give further evidence of the presence of Cu-containing nanoparticles on the Ni–N–C supports while revealing an additional relationship between the nanoparticle’s composition and the electrode’s electrocatalytic performance. Compared to the benchmark carbon black-supported Cu catalysts, Ni–N–C-supported Cu delivers up to a 2-fold increase in the partial C2H4 current density at −1.05 VRHE (C1/C2 = 0.67) and a concomitant 10-fold increase of the CO partial current density. The enhanced ethylene production metrics, obtained by virtue of the higher intrinsic activity of the Ni–N–C support, point out toward a synergistic action between the two catalytic functionalities.

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: Even at low temperatures, metal nanoparticles (NPs) possess atomic dynamics that are key for their properties but challenging to elucidate. Recent experimental advances allow obtaining atomic-resolution snapshots of the NPs in realistic regimes, but data acquisition limitations hinder the experimental reconstruction of the atomic dynamics present within them. Molecular simulations have the advantage that these allow directly tracking the motion of atoms over time. However, these typically start from ideal/perfect NP structures and, suffering from sampling limits, provide results that are often dependent on the initial/putative structure and remain purely indicative. Here, by combining state-of-the-art experimental and computational approaches, how it is possible to tackle the limitations of both approaches and resolve the atomistic dynamics present in metal NPs in realistic conditions is demonstrated. Annular dark-field scanning transmission electron microscopy enables the acquisition of ten high-resolution images of an Au NP at intervals of 0.6 s. These are used to reconstruct atomistic 3D models of the real NP used to run ten independent molecular dynamics simulations. Machine learning analyses of the simulation trajectories allow resolving the real-time atomic dynamics present within the NP. This provides a robust combined experimental/computational approach to characterize the structural dynamics of metal NPs in realistic conditions. Experimental and computational techniques are bridged to unveil atomic dynamics in gold nanoparticles (NPs), using annular dark-field scanning transmission electron microscopy and molecular dynamics simulations informed by machine learning. The approach provides unprecedented insights into the real-time structural behaviors of NPs, merging state-of-the-art techniques to accurately characterize their dynamics under realistic conditions. image

Abstract: The reductive amination of benzoic acid and its derivatives would be an effective addition to current synthesis methods for benzylamine. However, with current technology it is very difficult to keep the aromaticity intact when starting from benzoic acid, and salt wastes are often generated in the process. Here, we report a heterogeneous catalytic system for such a reductive amination, requiring solely H-2 and NH3 as the reactants. The Ag/TiO2 or Au/TiO2 catalysts can be used multiple times, and very little noble metal is required, only 0.025 mol % Au. The catalysts are bifunctional: the support catalyzes the dehydration of both the ammonium carboxylate to the amide and of the amide to the nitrile, while the sites at the metal-support interface promote the hydrogenation of the in situ generated nitrile. Yields of up to 92% benzylamine were obtained.

Abstract: Atomic layer deposition (ALD) is a vapor phase technique that is able to deposit uniform, conformal thin films with an excellent thickness control at the atomic scale. 18 nm thick Al2O3 and TiO2 coatings were deposited conformaly and pinhole-free onto micrometer-sized Cu powder, using trimethylaluminum and tetrakis(dimethylamido)titanium(IV), respectively, as a precursor and de-ionized water as a reactant. The capability of the ALD coating to protect the Cu powder against corrosion was investigated. Therefore, the stability of the coatings was studied in solutions with different pH in the range of 0–14, and in situ raman spectroscopy was used to detect the emergence of corrosion products of Cu as an indication that the protective coating starts to fail. Both ALD coatings provide good protection at standard pH values in the range of 5–7. In general, the TiO2 coating shows a better barrier protection against corrosion than the Al2O3 coating. However, for the most extreme pH conditions, pH 0 and pH 14, the TiO2 coating starts also to degrade.

Abstract: Magnetic hyperthermia has the potential to play an important role in cancer therapy and its efficacy relies on the nanomaterials selected. Superparamagnetic iron oxide nanoparticles (SPIONs) are excellent candidates due to the ability of producing enough heat to kill tumor cells by thermal ablation. However, their heating properties depend strongly on crystalline structure and size, which may not be controlled and tuned during the synthetic process; therefore, a postprocessing is needed. We show how thermal annealing can be simultaneously coupled with ligand exchange to stabilize the SPIONs in polar solvents and to modify their crystal structure, which improves hyperthermia behavior. Using high-resolution transmission electron microscopy, X-ray diffraction, Mossbauer spectroscopy, vibrating sample magnetometry, and lock-in thermography, we systematically investigate the impact of size and ligand exchange procedure on crystallinity, their magnetism, and heating ability. We describe a valid and simple approach to optimize SPIONs for hyperthermia by carefully controlling the size, colloidal stability, and crystallinity.

Abstract: In vitro experiments provide a solid basis for understanding the interactions between particles and biological systems. An important confounding variable for these studies is the difference between the amount of particles administered and that which reaches the surface of cells. Here, we engineer a hydrogel-based nanoparticle system and combine in situ characterization techniques, 3D-printed cell cultures, and computational modeling to evaluate and study particle cell interactions of advanced particle systems. The framework presented demonstrates how sedimentation and diffusion can explain differences in particle cell association, and provides a means to account for these effects. Finally, using in silico modeling, we predict the proportion of particles that reaches the cell surface using common experimental conditions for a wide range of inorganic and organic micro- and nanoparticles. This work can assist in the understanding and control of sedimentation and diffusion when investigating cellular interactions of engineered particles.

Abstract: Although most state-of-the-art Sn-based electrocatalysts yield promising results in terms of selectivity and catalyst activity, their stability remains insufficient to date. Here, we demonstrate the successful application of the recently developed pomegranate-structured SnO2 (Pom. SnO2) and SnO2@C (Pom. SnO2@C) nanocomposite electrocatalysts for the efficient electrochemical conversion of CO2 to formate. With an initial selectivity of 83 and 86% towards formate and an operating potential of -0.72 V and -0.64 V vs. RHE, respectively, these pomegranate SnO2 electrocatalysts are able to compete with most of the current state-of-the-art Sn-based electrocatalysts in terms of activity and selectivity. Given the importance of electrocatalyst stability, long-term experiments (24 h) were performed and a temporary loss in selectivity for the Pom. SnO2@C electrocatalyst was largely restored to its initial selectivity upon drying and exposure to air. Of all the used (24 h) electrocatalysts, the pomegranate SnO2@C had the highest selectivity over a time period of one hour, reaching an average recovered FE of 85%, while the commercial SnO2 and bare pomegranate SnO2 electrocatalysts reached an average of 79 and 80% FE towards formate, respectively. Furthermore, the pomegranate structure of Pom. SnO2@C was largely preserved due to the presence of the heterogeneous carbon shell, which acts as a protective layer, physically inhibiting particle segregation/pulverisation and agglomeration.

Abstract: Quantitative structure determination is needed in order to study and understand nanomaterials at the atomic scale. Materials characterisation resulting in precise structural information is a crucial point to understand the structure–property relation of materials. Counting the number of atoms and retrieving the 3D atomic structure of nanoparticles plays an important role here. In this paper, an overview will be given of the atom-counting methodology and its applications over the past decade. The procedure to count the number of atoms will be discussed in detail and it will be shown how the performance of the method can be further improved. Furthermore, advances toward mixed element nanostructures, 3D atomic modelling based on the atom-counting results, and quantifying the nanoparticle dynamics will be highlighted.

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: Hyperthermia, as the process of heating a malignant site above 42 °C to trigger cell death, has emerged as an effective and selective cancer therapy strategy. Various modalities of hyperthermia have been proposed, among which magnetic and photothermal hyperthermia are known to benefit from the use of nanomaterials. In this context, we introduce herein a hybrid colloidal nanostructure comprising plasmonic gold nanorods (AuNRs) covered by a silica shell, onto which iron oxide nanoparticles (IONPs) are subsequently grown. The resulting hybrid nanostructures are responsive to both external magnetic fields and near-infrared irradiation. As a result, they can be applied for the targeted magnetic separation of selected cell populations – upon targeting by antibody functionalization – as well as for photothermal heating. Through this combined functionality, the therapeutic effect of photothermal heating can be enhanced. We demonstrate both the fabrication of the hybrid system and its application for targeted photothermal hyperthermia of human glioblastoma cells.

Abstract: Plasma catalysis is a rapidly growing field, often employing a packed-bed dielectric barrier discharge plasma reactor. Such dielectric barrier discharges are complex, especially when a packing material (e.g., a catalyst) is introduced in the discharge volume. Catalysts are known to affect the plasma discharge, though the underlying mechanisms influencing the plasma physics are not fully understood. Moreover, the effect of the catalysts on the plasma discharge and its subsequent effect on the overall performance is often overlooked. In this work, we deliberately design and synthesize catalysts to affect the plasma discharge in different ways. These Ni or Co alumina-based catalysts are used in plasma-catalytic dry reforming of methane and ammonia synthesis. Our work shows that introducing a metal to the dielectric packing can affect the plasma discharge, and that the distribution of the metal is crucial in this regard. Further, the altered discharge can greatly influence the overall performance. In an atmospheric pressure dielectric barrier discharge reactor, this apparently more uniform plasma yields a significantly better performance for ammonia synthesis compared to the more conventional filamentary discharge, while it underperforms in dry reforming of methane. This study stresses the importance of analyzing the plasma discharge in plasma catalysis experiments. We hope this work encourages a more critical view on the plasma discharge characteristics when studying various catalysts in a plasma reactor.