Statistical distribution of single atoms and clusters of supported Au catalyst analyzed by global high-resolution HAADF-STEM observation with morphological image-processing operation

Yamamoto, Yuta; Arai, Shigeo; Esaki, Akihiko; Ohyama, Junya; Satsuma, Atsushi; Tanaka, Nobuo

doi:10.1093/jmicro/dfu001

Cited by 18 publications

(7 citation statements)

References 21 publications

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“…) even at the atomic level for very small clusters (Yamamoto et al . ) or on probabilistic models (Fisker et al . ) can give reliable results.…”

Section: Introductionmentioning

confidence: 99%

“…Most of the time, the measured NPs are dispersed on a homogeneous background (Fisker et al 2000;Eustis et al 2005;Li & Zuo 2005;Cervera Gontard et al 2006;Karlsson et al 2006). In this case, common automatic segmentation methods based on the global grey level of images (Cervera Gontard et al 2006), morphological image-processing operations (Eustis et al 2005) even at the atomic level for very small clusters (Yamamoto et al 2014) or on probabilistic models (Fisker et al 2000) can give reliable results. But when the systems or micrographs are more complex, such as near-coalescence or overlapping NPs (Li et al 2007;Park et al 2013;Muneesawang & Sirisathitkul 2015) or small size NPs imaged in high resolution TEM (HRTEM) on a carbon film, where the background ground affected by the defocusing conditions affects the measurements (Pyrz & Buttrey 2008), dedicated algorithms or measurement methods must be used.…”

Section: Introductionmentioning

confidence: 99%

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HAADF‐STEM characterization and simulation of nanoparticle distributions in an inhomogeneous matrix

Liu

Épicier

Lefkir

et al. 2017

Journal of Microscopy

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Measuring with a high accuracy the size distribution of small metallic nanoparticles loaded in a mesoporous metal oxide matrix is of particular interest for many studies related to new generations of interesting metamaterials. Transmission electron microscopy (TEM) is a powerful tool to determine the nature and morphology of very small particles, but their reliable and automatic identification in an inhomogeneous environment where the nanoparticle/background contrast locally varies is not straightforward. Here, we present how a quantitative analysis of high-angle annular dark field scanning TEM (HAADF STEM) images, accounting for the chemical sensitivity of the technique, can improve the accuracy of semiautomatic segmentation methods based on morphological processing to calculate size histograms. The paper also provides an estimate of the reliability of this method through the analysis of numerically synthesized images. The latter are based on the simulation of HAADF STEM projections of a volume filled with titania, pores and silver particles, whose morphological features, such as dimensions, shapes and densities are evaluated from experimental measurements of real samples. The results obtained with synthesized images prove the performances of the quantitative analysis to suppress nonsilver nanoparticles from the statistics and allow to infer empirical rules to determine imaging parameters that ensure a good reliability of histograms.

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“…) even at the atomic level for very small clusters (Yamamoto et al . ) or on probabilistic models (Fisker et al . ) can give reliable results.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

HAADF‐STEM characterization and simulation of nanoparticle distributions in an inhomogeneous matrix

Liu

Épicier

Lefkir

et al. 2017

Journal of Microscopy

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“…35 This microscopic perspective can induce bias (unintentional or intentional) in both image selection and species analysis. 36 The ability to extract accurate coordinates of metal centers in SACs comprises a crucial step toward bulk statistics, permitting the extraction of materials descriptors that provide information about the metal dispersion uniformity with a far superior significance to estimations based on manual analysis.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

Automated Image Analysis for Single-Atom Detection in Catalytic Materials by Transmission Electron Microscopy

et al. 2022

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Single-atom catalytic sites may have existed in all supported transition metal catalysts since their first application. Yet, interest in the design of single-atom heterogeneous catalysts (SACs) only really grew when advances in transmission electron microscopy (TEM) permitted direct confirmation of metal site isolation. While atomic-resolution imaging remains a central characterization tool, poor statistical significance, reproducibility, and interoperability limit its scope for deriving robust characteristics about these frontier catalytic materials. Here, we introduce a customized deep-learning method for automated atom detection in image analysis, a rate-limiting step toward high-throughput TEM. Platinum atoms stabilized on a functionalized carbon support with a challenging irregular three-dimensional morphology serve as a practically relevant test system with promising scope in thermo-and electrochemical applications. The model detects over 20,000 atomic positions for the statistical analysis of important properties for establishing structure−performance relations over nanostructured catalysts, like the surface density, proximity, clustering extent, and dispersion uniformity of supported metal species. Good performance obtained on direct application of the model to an iron SAC based on carbon nitride demonstrates its generalizability for single-atom detection on carbon-related materials. The approach establishes a route to integrate artificial intelligence into routine TEM workflows. It accelerates image processing times by orders of magnitude and reduces human bias by providing an uncertainty analysis that is not readily quantifiable in manual atom identification, improving standardization and scalability.

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“…With aberration correction, imaging of Au clusters at the atomic resolution is now possible. [ 230 ] Information that can be obtained from TEM and STEM imaging includes particle size, shape, lattice fringe, crystallographic structure, defects, and grain boundaries.…”

Section: Characterization Of Au Clustersmentioning

confidence: 99%

A Review of State of the Art in Phosphine Ligated Gold Clusters and Application in Catalysis

et al. 2022

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Atomically precise gold clusters are highly desirable due to their well-defined structure which allows the study of structure-property relationships. In addition, they have potential in technological applications such as nanoscale catalysis. The structural, chemical, electronic, and optical properties of ligated gold clusters are strongly defined by the metal-ligand interaction and type of ligands. This critical feature renders gold-phosphine clusters unique and distinct from other ligand-protected gold clusters. The use of multidentate phosphines enables preparation of varying core sizes and exotic structures beyond regular polyhedrons. Weak gold-phosphorous (Au-P) bonding is advantageous for ligand exchange and removal for specific applications, such as catalysis, without agglomeration. The aim of this review is to provide a unified view of gold-phosphine clusters and to present an in-depth discussion on recent advances and key developments for these clusters. This review features the unique chemistry, structural, electronic, and optical properties of gold-phosphine clusters. Advanced characterization techniques, including synchrotron-based spectroscopy, have unraveled substantial effects of Au-P interaction on the composition-, structure-, and size-dependent properties. State-of-the-art theoretical calculations that reveal insights into experimental findings are also discussed. Finally, a discussion of the application of gold-phosphine clusters in catalysis is presented.

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Statistical distribution of single atoms and clusters of supported Au catalyst analyzed by global high-resolution HAADF-STEM observation with morphological image-processing operation

Cited by 18 publications

References 21 publications

HAADF‐STEM characterization and simulation of nanoparticle distributions in an inhomogeneous matrix

HAADF‐STEM characterization and simulation of nanoparticle distributions in an inhomogeneous matrix

Automated Image Analysis for Single-Atom Detection in Catalytic Materials by Transmission Electron Microscopy

A Review of State of the Art in Phosphine Ligated Gold Clusters and Application in Catalysis

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