LAUSR

High‐entropy oxides (HEOs) are emerging as a promising material for next‐generation catalysts. However, their versatile compositions and complex atomic arrangements present great challenges in rapid and scale‐up synthesis, identifying the active sites, and unraveling structure‐performance relationships. Herein, an all‐in‐one workflow is developed to synthesize, characterize, understand, and apply HEOs in catalysis, combining high‐throughput synthesis (≈100 g/h in pilot scale), rapid activity testing, and data‐driven screening. The workflow involves synthesis of HEOs via a continuous hydrothermal flow reactor, integrated with rapid thermal processing. Catalytic testing is conducted using a rapid Joule heating system and a machine learning‐based model is used to unveil the synthesis‐structure‐performance relationships. As a proof‐concept, this workflow is demonstrated to continually produce 52 HEOs existing in eight distinct crystal structures, with 16 metal elements. This rapid approach, supplemented by data‐driven analysis to identify the champion samples, represents ≈70% time saving compared to more conventional make‐and‐test methods.