Recent Progress in High‐Throughput On‐Chip Synthesis, Screening, and Data‐Driven Optimization: Toward an Electrocatalyst Chip for Catalysis Universe Exploration

Abstract Throughout history, the quest for a “magic crystal ball” to predict the future and uncover the world's greatest innovations has captivated human imagination. For scientists, the dream of a compact chip brimming with data and wisdom is equally tantalizing. Despite the meteoric rise of artificial intelligence, the research paradigm for electrocatalysts has lagged, advancing at a surprisingly sluggish pace. This review aims to promote electrocatalyst informatics and revolutionize high‐performance material discovery by integrating advanced combinatorial on‐chip synthesis, high‐throughput screening, and machine learning‐powered analysis and optimization. The synergistic progress in these fields, envisioning a future where a minimized “electrocatalyst chip” can effortlessly navigate complex chemical spaces within a “data fablab” is critically examined. This innovative paradigm promises to accelerate the discovery of crucial materials, offering tangible solutions to pressing global challenges in energy, environmental sustainability, and technological advancement. This strategy is believed to hold great potential to transform the landscape of catalyst discovery and unleash a new wave of scientific breakthroughs.