The Heterogeneity of Turn-over Number in Electrocatalysis

Abstract

Chemical catalysts dominate the multi-billion global revenue of the chemical industry because they accelerate the time it takes a particular reaction to reach equilibrium without altering the equilibrium constant. Electrocatalysis can provide significant benefits compared to other methods, as it has minimal purification and separation costs, is operational at low temperatures and pressures, replaces hazardous and toxic chemical sources with electric current, and can be integrated with renewable energy sources. From a techno-economical point of view, some considerations are critical during a catalyst design: cost, activity, and durability. One useful metric to quantify catalyst durability is turn-over number (TON), which represents the maximum yield of products attainable from a catalytic center. Mathematically speaking, the TON is defined as: TON = ∫0 ∞ TOF(t) dt, where TOF is the turn-over frequency, which is the rate of turn-overs (N) per active site. Currently, without any exception, the TON is given as a fixed number describing the total amount of substrate converted until the catalysts fully degrade. Our approach studies electrocatalytic deactivation processes at the single catalyst level using a technique entitled single-entity electrochemistry for freely diffusing catalysts. The hydrogen evolution reaction (HER) is investigated with platinum nanoparticles as the model catalyst because it deactivates at the nanoscale when the catalytic activity decreases over time. At specific applied potentials, the current measured when a single platinum nanoparticle impacts the electrode creates a transient spike and decay back to the baseline current. TON is quantified by fitting the current decay response and integrating above the fit to find the charge transferred to catalyze the reaction. Our results show that electrocatalyst degradation and TON have a distribution, where some catalysts are more stable than others, and depends on the applied potential and size of the nanoparticles. In order to study how the surface facets of platinum affect the TON, SECCM was coupled with scanning electron microscopy (SEM) to compare the deactivation of a polycrystalline platinum surface in the macro scale with immobilized platinum nanoparticles on a glassy carbon surface. Combining local structural, electrochemical activity, and durability will bridge our fundamental understanding of macro and nanoscale catalyst deactivation processes to assist in the bottom-up approach of material development and design of large-scale industrial electrocatalysts.