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The electrochemical ammonia oxidation to dinitrogen as a means for energy and environmental applications is a key technology toward the realization of a sustainable nitrogen cycle. The state-of-the-art metal catalysts including Pt and its bimetallics with Ir show promising activity, albeit suffering from high overpotentials for appreciable current densities and the soaring price of precious metals. Herein, the immense design space of ternary Pt alloy nanostructures is explored by graph neural networks trained on ab initio data for concurrently predicting site reactivity, surface stability, and catalyst synthesizability descriptors. Among a few Ir-free candidates that emerge from the active learning workflow, Pt₃Ru-M (M: Fe, Co, or Ni) alloys were successfully synthesized and experimentally verified to be more active toward ammonia oxidation than Pt, Pt₃Ir, and Pt₃Ru. More importantly, feature attribution analyses using the machine-learned representation of site motifs provide fundamental insights into chemical bonding at metal surfaces and shed light on design strategies for high-performance catalytic systems beyond thed-band center metric of binding sites.

 

The electrochemical nitrate reduction reaction (NO₃RR) to ammonia is an essential step toward restoring the globally disrupted nitrogen cycle. In search of highly efficient electrocatalysts, tailoring catalytic sites with ligand and strain effects in random alloys is a common approach but remains limited due to the ubiquitous energy-scaling relations. With interpretable machine learning, we unravel a mechanism of breaking adsorption-energy scaling relations through the site-specific Pauli repulsion interactions of the metald-states with adsorbate frontier orbitals. The non-scaling behavior can be realized on (100)-type sites of ordered B2 intermetallics, in which the orbital overlap between the hollow *N and subsurface metal atoms is significant while the bridge-bidentate *NO₃is not directly affected. Among those intermetallics predicted, we synthesize monodisperse ordered B2 CuPd nanocubes that demonstrate high performance for NO₃RR to ammonia with a Faradaic efficiency of 92.5% at −0.5 V_RHEand a yield rate of 6.25 mol h⁻¹g⁻¹at −0.6 V_RHE. This study provides machine-learned design rules besides thed-band center metrics, paving the path toward data-driven discovery of catalytic materials beyond linear scaling limitations.

 

Low-temperature direct ammonia fuel cells (DAFCs) use carbon-neutral ammonia as a fuel, which has attracted increasing attention recently due to ammonia's low source-to-tank energy cost, easy transport and storage, and wide availability. However, current DAFC technologies are greatly limited by the kinetically sluggish ammonia oxidation reaction (AOR) at the anode. Herein, we report an AOR catalyst, in which ternary PtIrZn nanoparticles with an average size of 2.3 ± 0.2 nm were highly dispersed on a binary composite support comprising cerium oxide (CeO 2 ) and zeolitic imidazolate framework-8 (ZIF-8)-derived carbon (PtIrZn/CeO 2 -ZIF-8) through a sonochemical-assisted synthesis method. The PtIrZn alloy, with the aid of abundant OH ad provided by CeO 2 and uniform particle dispersibility contributed by porous ZIF-8 carbon (surface area: ∼600 m 2 g −1 ), has shown highly efficient catalytic activity for the AOR in alkaline media, superior to that of commercial PtIr/C. The rotating disk electrode (RDE) results indicate a lower onset potential (0.35 vs. 0.43 V), relative to the reversible hydrogen electrode at room temperature, and a decreased activation energy (∼36.7 vs. 50.8 kJ mol −1 ) relative to the PtIr/C catalyst. Notably, the PtIrZn/CeO 2 -ZIF-8 catalyst was assembled with a high-performance hydroxide anion-exchange membrane to fabricate an alkaline DAFC, reaching a peak power density of 91 mW cm −2 . Unlike in aqueous electrolytes, supports play a critical role in improving uniform ionomer distribution and mass transport in the anode. PtIrZn nanoparticles on silicon dioxide (SiO 2 ) integrated with carboxyl-functionalized carbon nanotubes (CNT–COOH) were further studied as the anode in a DAFC. A significantly enhanced peak power density of 314 mW cm −2 was achieved. Density functional theory calculations elucidated that Zn atoms in the PtIr alloy can reduce the theoretical limiting potential of *NH 2 dehydrogenation to *NH by ∼0.1 V, which can be attributed to a Zn-modulated upshift of the Pt–Ir d-band that facilitates the N–H bond breakage.