Quantitative 3D Characterization of Functionally Relevant Parameters in Heavy-Oxide-Supported 4d Metal Nanocatalysts.

Accurate 3D nanometrology of catalysts with small nanometer-sized particles of light 3d or 4d metals supported on high-atomic-number oxides is crucial for understanding their functionality. However, performing quantitative 3D electron tomography analysis on systems involving metals like Pd, Ru, or Rh supported on heavy oxides (e.g., CeO2) poses significant challenges. The low atomic number (Z) of the metal complicates discrimination, especially for very small nanoparticles (1-3 nm). Conventional reconstruction methods successful for catalysts with 5d metals (e.g., Au, Pt, or Ir) fail to detect 4d metal particles in electron tomography reconstructions, as their contrasts cannot be effectively separated from those of the underlying support crystallites. To address this complex 3D characterization challenge, we have developed a full deep learning (DL) pipeline that combines multiple neural networks, each one optimized for a specific image-processing task. In particular, single-image super-resolution (SR) techniques are used to intelligently denoise and enhance the quality of the tomographic tilt series. U-net generative adversarial network algorithms are employed for image restoration and correcting alignment-related artifacts in the tilt series. Finally, semantic segmentation, utilizing a U-net-based convolutional neural network, splits the 3D volumes into their components (metal and support). This approach enables the visualization of subnanometer-sized 4d metal particles and allows for the quantitative extraction of catalytically relevant structural information, such as particle size, sphericity, and truncation, from compressed sensing electron tomography volume reconstructions. We demonstrate the potential of this approach by characterizing nanoparticles of a metal widely used in catalysis, Pd (Z = 46), supported on CeO2, a very high density (7.22 g/cm3) oxide involving a quite high-atomic-number element, Ce (Z = 58).

Dual enlargement of gold nanoparticles: from mechanism to scanometric detection of pathogenic bacteria.

A mechanism of dual enlargement of gold nanoparticles (AuNPs) comprising two steps is described. In the first step, the AuNPs are enlarged by depositing Au atoms on their crystalline faces. In this process, the particles are not only enlarged but they are also observed to multiply: new Au nuclei are formed by the budding and division of the enlarged particles. In the second step, a silver enhancement is subsequently performed by the deposition of silver atoms on the enlarged and newly formed AuNPs to generate bimetallic Au@Ag core-shell structures. The dual nanocatalysis greatly enhances the electron density of the nanostructures, leading to a stronger intensity for colorimetric discrimination as well as better sensitivity for quantitative measurement. Based on this, a simple scanometric assay for the on-slide detection of the food-born pathogen Campylobacter jejuni is developed. After capturing the target bacteria, gold-tagged immunoprobes are added to create a signal on a solid substrate. The signal is then amplified by the dual enlargement process, resulting in a strong color intensity that can easily be recognized by the unaided eye, or measured by an inexpensive flatbed scanner. In this paper, dual nanocatalysis is reported for the first time. It provides a valuable mechanistic insight into the development of a simple and cost-effective detection format.

Resolving the structure of active sites on platinum catalytic nanoparticles.

Accurate understanding of the structure of active sites is fundamentally important in predicting catalytic properties of heterogeneous nanocatalysts. We present an accurate determination of both experimental and theoretical atomic structures of surface monatomic steps on industrial platinum nanoparticles. This comparison reveals that the edges of nanoparticles can significantly alter the atomic positions of monatomic steps in their proximity, which can lead to substantial deviations in the catalytic properties compared with the extended surfaces.

A single slice approach for simulating two-beam electron diffraction of nanocrystals.

A simple computational method that can be used to simulate TEM image contrast of an electron beam diffracted by a crystal under two-beam dynamical scattering conditions is presented. The approach based on slicing the shape factor is valid for a general crystal morphology, with and without crystalline defects, avoids the column approximation, and provides the complex exit wave at the focal and the image planes also under weak-beam conditions. The approach is particularly efficient for large crystals and the 3D model required for the calculations can be measured experimentally using electron tomography. The method is applied to show that the shape of a diffracted spot can be affected by shifts, broadening and secondary maxima of appreciable intensity, even for a perfect crystal. The methodology is extended for the case of electron precession diffraction, and to show how can be used to improve nanometrology from diffraction patterns. The method is used also to perform simulations of simple models of crystalline defects. The accuracy of the method is demonstrated through examples of experimental and simulated dark-field images of MgO and ZrO2 nanocrystals and thin layers of CeO2.

High-resolution TEM and the application of direct and indirect aberration correction.

Aberration correction leads to a substantial improvement in the directly interpretable resolution of transmission electron microscopes. Correction of the aberrations has been achieved electron-optically through a hexapole-based corrector and also indirectly by computational analysis of a focal or tilt series of images. These direct and indirect methods are complementary, and a combination of the two offers further advantages. Materials characterization has benefitted from the reduced delocalization and higher resolution in the corrected images. It is now possible, for example, to locate atomic columns at surfaces to higher accuracy and reliability. This article describes the JEM-2200FS in Oxford, which is equipped with correctors for both the image-forming and probe-forming lenses. Examples of the use of this instrument in the characterization of nanocrystalline catalysts are given together with initial results combining direct and indirect methods. The double corrector configuration enables direct imaging of the corrected probe, and a potential confocal imaging mode is described. Finally, modifications to a second generation instrument are outlined.