In-Situ Simulation of Jagged Pt Nanowire for Hydrogen Evolution Reaction

Presently, commercial electrolysis cells for hydrogen evolution reaction (HER) use Pt-based catalyst due to its high activity and stability, but the Pt is a major cost driver. One way to lowering the cost is to reduce the amount of Pt used while maintaining high activity. Previously, the jagged Pt nanowire has been synthesized and demonstrated a high specific activity (the catalytic current per unit mass of Pt), an order of magnitude higher than the commercial carbon-supported Pt in alkaline condition. Understanding the kinetic characteristics of the jagged Pt nanowire can potentially help design a better catalyst. However, modeling jagged surface is a great challenge as its surface is non-uniform thus using the conventional density functional theory is too expensive. Here, we implement the state-of-the-art theoretical methodologies to reveal the chemical insights from the jagged Pt nanowire simulation. We combine machine learning, kinetic Monte Carlo, ReaxFF, Brønsted−Evans−Polanyi relation to demonstrate their powerful utility to simulate room temperature structure of the jagged Pt nanowire and reveal novel kinetic insights. We find that two reactions, Volmer and Tafel, are co-rate determining step with different optimal Gibbs free energy of adsorption (∆_rG_ads), resulting in the monometallic bifunctional characteristics: ones selective for Volmer and others selective for Tafel. Another ramification is that the optimal ∆_rG_ads, conventionally believed to be equal to 0, decreases with increasing pH.