Abstract
The next-generation of energy devices rely on advanced catalytic materials, especially electrocatalytic nanoparticles (NPs), to achieve the performance and cost required to reshape the energy landscape towards a more sustainable and cleaner future. It has become imperative to maximize the performance of the catalyst, both through improvement of the intrinsic activity of the NP, and by ensuring all particles are performing at the level of their capability. This requires not just a structure-function understanding of the catalytic material, but also an understanding of how the catalyst performance is impacted by its environment (substrate, ligand, etc.). The intrinsic activity and environment of catalytic particles on a support may differ wildly by particle, thus it is essential to build this understanding from a single-entity perspective. To achieve this herein, scanning electrochemical cell microscopy (SECCM) has been used, which is a droplet-based scanning probe technique which can encapsulate single NPs, and apply a voltage to the nanoparticle whilst measuring its resulting current. Using SECCM, single AuNPs have been encapsulated, and their activity for the borohydride oxidation reaction (BOR) is measured. A total of 268 BOR-active locations were probed (178 single particles) and a series of statistical analyses were performed in order to make the following discoveries: (1) a certain percentage of AuNPs display no BOR activity in the SECCM experiment (67.4% of single NPs), (2) visibly-similar particles display wildly varied BOR activities which cannot be explained by particle size, (3) the impact of cluster size (#NP at a single location) on a selection of diagnostic electrochemical parameters can be easily probed with SECCM, (4) exploratory statistical correlation between these parameters can be meaningfully performed with SECCM, and (5) outlying "abnormal" NP responses can be probed on a particle-by-particle basis. Each one of these findings is its own worthwhile study, yet this has been achieved with a single SECCM scan. It is hoped that this research will spur electrochemists and materials scientists to delve deeper into their substantial datasets in order to enhance the structure-function understanding, to bring about the next generation of high-performance electrocatalysts.