Prospect of Ruthenium for Hydrogen Evolution Reaction in Alkaline Media through In Situ Monitoring

Abstract Ruthenium (Ru)‐based catalysts are highly promising for the hydrogen evolution reaction (HER) in alkaline media. Despite their platinum‐like catalytic activity, a comprehensive and consistent understanding of their behavior under operating conditions remains limited and controversial. Many analytical strategies have been developed based on ex situ properties. However, they fail to reflect the dynamic and reactive environment in which HER occurs. In this perspective, recent advances in in situ and operando characterization techniques are highlighted to enable a more accurate and mechanistic understanding of Ru‐based catalysts under working conditions. By capturing structural evolution, intermediate dynamics, and interfacial reorganization in real time, these methods overcome the limitations of static, ex situ approaches. Based on these insights, we propose a dynamic‐state‐informed design paradigm that bridges the gap between intrinsic catalytic descriptors and real‐time reaction dynamics. This framework emphasizes the integration of static indicators (e.g., hydrogen and hydroxyl binding energies and d ‐band center) with operando‐derived dynamic descriptors that reflect potential‐dependent restructuring and interfacial transformations. By embedding these hybrid descriptors within an iterative feedback loop, supported by predictive modeling and machine learning, this strategy paves the way for adaptive and data‐driven catalyst design tailored to realistic HER environments.