First-principles, data-guided screening and catalyst design: Unveiling energetic trade-offs in ammonia decomposition

Abstract

Ammonia decomposition is a promising route for CO₂-free hydrogen production, but the development of efficient and cost-effective catalysts remains a challenge. Here, we employed a dual approach combining computational screening and free energy analysis to identify optimal catalysts, which were then validated experimentally. Pearson correlation coefficient analysis revealed a volcano-type relationship between NH₃ dissociation energy (E_diss,NH3) and N₂ adsorption energy (E_ad,N2), highlighting Ru as the most effective monometallic catalyst. Reactor tests using supported Ru, Rh, Ir, Ni, and Co catalysts confirmed these predictions, with Ru exhibiting the highest NH₃ conversion and a strong correlation between turnover frequency, activation energy (E_a), and electronic descriptors. Using this validated approach, we extended our analysis to bimetallic systems, identifying Ru-Ni alloys, as a promising alternative with balanced NH₃ activation and N₂ desorption. These findings demonstrate the effectiveness of combining computational and experimental methods to design high-performance NH₃ decomposition catalysts. Further refinement of Ru-Ni alloy synthesis and structural control could enhance catalytic activity, supporting scalable hydrogen production.