Aberration-Corrected STEM to Determine the Surface Coverage and Distribution of Immobilized Molecular Complexes

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.