Publication date: 15th December 2025
Controlling the solid-liquid interface and understanding catalyst-electrolyte interactions are central challenges for the rational design of electrocatalysts, particularly for the nitrate reduction reaction (NO3RR) to ammonia under realistic wastewater conditions where diverse coexisting ions strongly impact activity and stability. In this work, a decentralized self‑driving laboratory (SDL) is established between the University of Toronto and ICFO to autonomously explore the combined space of catalyst and electrolyte compositions for NO3RR. The platform integrates in situ catalyst fabrication with programmable compositional gradients, high‑throughput electrochemical screening in electrolytes of controlled multi‑ion composition, and automated analysis of nitrate‑to‑ammonia performance. A Bayesian optimization engine closes the loop by iteratively proposing new catalyst formulations conditioned on the specific electrolyte matrix, enabling the system to self‑optimize catalyst composition for a given wastewater‑relevant environment. This approach provides a general framework to disentangle and exploit catalyst-electrolyte interactions, enabling accelerated optimization of both catalyst composition and electrolyte formulation, and supporting decentralized strategies for electrocatalyst development that can be extended to other electrolyte‑engineered systems.
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