High entropy alloys for advanced electrocatalysis with computational insights and multidisciplinary design strategies

The growing demand for sustainable energy solutions drives the exploration of high-entropy alloys (HEAs) in electrocatalysis. HEAs have emerged as paradigm-shifting electrocatalysts for complex reactions, yet their mechanistic underpinnings remain underexplored. This study establishes a comprehensive computational framework integrating density functional theory (DFT), machine learning (ML), and multiscale simulations to decode the catalytic mechanisms of HEAs and guide their rational design. These insights break the "scaling relationship" bottleneck in conventional catalysts. Future efforts should bridge accuracy-efficiency trade-offs via multiscale modeling and address dynamic interface phenomena to unlock HEA potential in sustainable energy conversion and all kinds of catalytic reaction.