High-entropy materials (HEMs) represent an emerging class of materials presenting significant opportunities and substantial challenges in energy catalysis, garnering increasing attention and interest. In this review, we summarize the recent advancements in key aspects of HEM research, including synthesis methodologies, characterization techniques, theoretical and computational simulations, and the application of artificial intelligence (AI) technology across these domains. By integrating knowledge and experience from these diverse perspectives, this review aims to provide fundamental understanding and in-depth insights to the scientific community and build bridges between different research areas. Specifically, we highlight the pivotal role of AI in accelerating the discovery and optimization of HEMs, from guiding the design of novel synthetic routes to advanced characterization, and enhancing the efficiency of computational simulations. Furthermore, by highlighting the intersections between catalysis, materials science, computational techniques, and AI, this review encourages interdisciplinary collaboration and innovation. It underscores the importance of combining expertise from different fields to tackle the huge challenges associated with HEMs, fostering a collaborative research ecosystem that is essential for breakthroughs in this emerging field. Looking ahead, we anticipate that the integration of AI-driven approaches will pave the way for innovation in scientific research and beyond.
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