ARCADE: A New Paradigm for a Fully Automated and Interpretable Design of Complex Catalysts

The rational design of high-performance catalysts is pivotal for modern industry but is often hindered by the time-consuming nature of trial-and-error methods. While computational and data-driven approaches have accelerated materials discovery, significant challenges remain, especially for complex systems like multielement nanoparticles. These challenges include immense computational costs, difficulties in modeling stability and heterogeneous active sites, and a lack of interpretability in "black-box" AI models. To address these multifaceted challenges, we introduce ARCADE (Automated Rational CAtalyst DEsign), a generalizable and transferable framework for the automated and interpretable design of complex catalysts. Our framework integrates a high-throughput workflow that synergizes realistic structure generation, active-site screening, state-of-the-art pH-dependent microkinetic modeling, and short-range order (SRO) guided interpretability, establishing an end-to-end design pipeline that leverages public databases. Using the challenging design of multielement nanoparticle catalysts for CO2 reduction reaction (CO₂RR) as a representative system, we demonstrate that ARCADE can systematically navigate the design process, from evaluating material stability to identifying site-specific activity and selectivity. Our results show that this methodology substantially accelerate the development cycle for complex catalysts, confirming its feasibility and broad applicability. Crucially, this work establishes a new, fully integrated paradigm for the rational design and discovery of complex materials for challenging chemical reactions.