Predictive Uncovering of Next-gen protonic Ceramics for Hydrogen and ammonia electrolysis

Rationale / Needs to be addressed: Most hydrogen (H2) and ammonia (NH3) are pro-duced from fossil feedstock. To scale green routes, electrolysers must have longer life-time and decreased cost. Operating below 500 °C lowers thermo-mechanical stress and allows cheaper steels and seals, improving durability and reducing costs. Objectives: Use machine learning (ML), atomistic modelling and experimental screening to identify new proton-conducting electrolytes for under 500 °C operation, scale powder syn-thesis, fabricate 5×5 cm cells, and validate them for H2, and proof-of-concept direct NH3 production. Potential Applications: On-site green H2 for industry, modular NH3 for fertilizer and fuel, and flexible Power-to-X using renewables and waste heat. Impact and potential benefits: Electrolysers at 350–500 °C can lower CAPEX, simplify balance-of-plant, and extend lifetime. Open ML/modelling will speed materials discov-ery and support EU climate targets, CO2 cuts, and energy security.