Effect of Nitrogen Defects on Pt Nanoparticle Dispersion and Stability Studied by Electron Microscopy Paired with Machine Learning Image Processing for Probing Catalyst-Support Interactions

Polymer electrolyte membrane fuel cells are on the rise as a commercial technology, although Pt catalyst utilization and stability remain a challenge. N-doped carbon supports offer the opportunity to improve catalyst-support interactions, but there is limited understanding of the effects of various nitrogen functionalities on nucleation and the stabilization of Pt catalyst nanoparticles (NPs). This work uses a series of N-doped carbons with varying N chemistries and Pt NPs produced via a polyol method to investigate the effects of nitrogen on Pt catalyst that is deposited as externally nucleated and grown NPs. Samples were analyzed using X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) to identify trends related to nitrogen speciation. TEM analysis was employed to investigate effects of nitrogen on nucleation of Pt NPs and their stability when subjected to accelerated stress testing up to 10000 cycles using identical-location TEM setup. Systematic incorporation of high throughput machine-learning-based imaging analysis paired with identical location microscopy uncovered several mechanistic insights relevant to catalysis and fuel cells applications. Within the study's sample set, graphitic-N-rich carbons resulted in better dispersion of Pt NPs. However, these same graphitic-N-rich NC samples demonstrated significant instability, with a high degree of dissolution and some migration that correlated with a higher amount of graphitic N content. It was also found that the pyridinic-rich samples resulted in a mixed degradation mechanism where both migration and dissolution mechanisms were prominent throughout aging. [GRAPHICS]

Automated summary

Polymer electrolyte membrane fuel cells are a promising commercial technology, but there are challenges regarding the utilization and stability of Pt catalysts. This study investigates the effects of nitrogen on the nucleation and stability of Pt catalyst nanoparticles deposited on N-doped carbon supports. Through analysis using XPS and TEM, trends related to nitrogen speciation are identified. The systematic incorporation of high throughput machine-learning-based imaging analysis and identical-location microscopy provides mechanistic insights for catalysis and fuel cells applications.