Mechanistic insights into nitrate reduction to ammonia on dynamically reconstructing CuOₓ surfaces
Antonio de Arcos Cañamero a, Thaimy Brito a, Gerard Novell-Leruth a, Rodrigo García-Muelas a
a Iberian Center for Research in Energy Storage - CIIAE FUNDECYT-PCTEx. Polytechnic School of Caceres, Office CIIAE-C6. Av. Universidad s/n, 10003 Cáceres, Spain.
Materials for Sustainable Development Conference (MATSUS)
Proceedings of MATSUS Fall 2024 Conference (MATSUSFall24)
#ModElOp - Modeling Electrochemistry in Operando
Lausanne, Switzerland, 2024 November 12th - 15th
Organizers: Federico Dattila and Kevin Rossi
Invited Speaker, Rodrigo García-Muelas, presentation 224
DOI: https://doi.org/10.29363/nanoge.matsusfall.2024.224
Publication date: 28th August 2024

Ammonia (NH₃) is a crucial feedstock used across many sectors, ranging from the production of fertilizers to fine chemicals, and it is also a promising hydrogen carrier for decarbonizing hard-to-abate sectors. An alternative to its main production route, the Haber-Bosch process, is the electrochemical reduction of nitrate (NO₃⁻), which is a pervasive water pollutant. Cu-based electrodes have demonstrated excellent activity and selectivity towards ammonia, preventing undesired pathways such as dinitrogen (N₂) production. However, the cathodic potentials applied during operation induce significant reconstructions on the electrode, which are exacerbated by nitrate's strong oxidizing nature [1,2], thus adding substantial challenges to their accurate modelling and understanding. In this presentation, I will discuss our advances in elucidating the reaction mechanism of nitrate reduction to ammonia on Cu-based catalysts. To this end, we first mapped the complete reaction network, including key adsorbed intermediates such as nitrite (NO₂*), nitrogen (N*), and hydroxylamine (NH₂OH*). Then, by using ab-initio methods based on Density Functional Theory, we obtained the full energy profile including all intermediates and relevant transition states. These elements were wrapped up into a transient-state microkinetic model to identify the dominant reaction pathways and assess the influence of both the reaction environment (including solvent, pH, and electric potential) and the catalyst's history. This study paves the way for a comprehensive understanding of complex reaction networks and their interactions with the reaction environment.

This work was possible thanks to the generous computing resources provided by the high-performance computing clusters Turgalium (AtomS) and MareNostrum 5 (QHS-2024-2-0034). Turgalium belongs to Extremadura Research Centre for Advanced Technologies (CETA-CIEMAT), funded by the European Regional Development Fund. CETA-CIEMAT belongs to CIEMAT and the Government of Spain. 
Exp 442/2024 Financiado por el Mecanismo de Recuperación y Resiliencia.

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