Abstract
The surface immobilization of molecular catalysts is attractive because it combines the benefits of homogeneous and heterogeneous catalysis. However, determining the surface coverage and the distribution of a molecular catalyst on a solid support is often challenging, inhibiting our ability to control catalytic performance. Here, we demonstrate that scanning transmission electron microscopy can image the location of the metal center in surface-attached transition metal complexes with atomic resolution. Using a machine learning model, we can analyze many images to determine surface coverage and distribution in a non-destructive manner. This allows us to establish how changes to the molecular catalyst affect surface coverage and distribution. Our work describes a new method to characterize surface-attached catalysts, which is likely general to many systems.
Supplementary materials
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Supplementary information
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Supplementary information including Supplementary Notes, Supplementary Figures, Supplementary Tables, and Captions for Supplementary Movies
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Supplementary Movie 1
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Drift corrected image sequence of 6 consecutive images of the Re-Bubpy captured by HAADF-STEM.
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Supplementary Movie 2
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Drift corrected image sequence of 10 consecutive images of the Re-Phen captured by HAADF-STEM.
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Supplementary Movie 3
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Drift corrected image sequence of 10 consecutive images of the backfilled Re-Bubpy captured by HAADF-STEM
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Supplementary Movie 4
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Drift corrected image sequence of 10 consecutive images of the backfilled Re-Phen captured by HAADF-STEM
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Supplementary Movie 5
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Drift corrected image sequence of 10 consecutive images of the Re-Bu2bpy captured by HAADF-STEM
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Supplementary Movie 6
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Drift corrected image sequence of 10 consecutive images of the Re-Nonbpy captured by HAADF-STEM
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Supplementary Movie 7
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Drift corrected image sequence of 10 consecutive images of the Re-Etbpy captured by HAADF-STEM
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Supplementary Movie 8
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Drift corrected image sequence of 10 consecutive images of the Re-Etbpy captured by HAADF-STEM at cryogenic temperature
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Supplementary Movie 9
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Explanation for the K function calculated from three different point patterns in the case of dispersed, random, and clustered points
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