Electrochemical reduction of nitrate to ammonia (NH3) converts an environmental pollutant to a critical nutrient. However, current electrochemical nitrate reduction operations based on monometallic and bimetallic catalysts are limited in NH3 selectivity and catalyst stability, especially in acidic environments. Meanwhile, catalysts with dispersed active sites generally exhibit a higher atomic utilization and distinct activity. Herein, we report a multielement alloy nanoparticle catalyst with dispersed Ru (Ru-MEA) with other synergistic components (Cu, Pd, Pt). Density functional theory elucidated the synergy effect of Ru-MEA than Ru, where a better reactivity (NH3 partial current density of −50.8 mA cm−2) and high NH3 faradaic efficiency (93.5%) is achieved in industrially relevant acidic wastewater. In addition, the Ru- MEA catalyst showed good stability (e.g., 19.0% decay in FENH3 in three hours). This work provides a potential systematic and efficient catalyst discovery process that integrates a data-guided catalyst design and novel catalyst synthesis for a range of applications.
(a) Schematic diagram of the traditional nitrogen conversion cycle consisting of nitrification, denitrification, and N2 fixation (greyed), and the reported direct electrocatalytic NO3− reduction (ENR) to NH3 in this work. (b) Design principle of MEA NP (Ru37Pt21Pd22Cu20) catalyst based on a benchmark Ru catalyst, where SSP indicates a solid solution phase.
Characterization of the Ru-MEA NPs: (a) STEM elemental maps for Ru-MEA NPs. (b) HAADF image. (c) Catalysts’ size distribution was generated from the SEM spectrum and the fitted normal distribution (details in Supporting Information). (d) XRD pattern and SAXS data of Ru-MEA with labeled phases corresponding to reference standards of Pd/Pt/RuPt and Cu (italic). XPS core level scan of each component in Ru- MEA NPs: (e) Pt 4f, (f) Pd 3d, (g) Ru 3d5/2, (h) Cu 2p.
(a) Proposed NO3− reduction reaction pathway to NH3 on the RuPtPdCu (111) surface. In the figure, the gray, orange, purple, yellow, blue, red, and white balls represent Pd, Ru, Pt, Cu, N, O, and H atoms, respectively. (b) DFT predicted the adsorption energy as compared to the adsorption energy predicted by the linear regression model, which links the local chemical environment of the surface sites and NH adsorption energy. The inset shows that an NH is adsorbed on a surface site on RuPtPdCu (111) containing the three nearest neighboring metal atoms (i.e., the blue balls marked with “1”) and three second-neighboring metal atoms (i.e., the yellow balls marked with “2”). (c) Predicted free energy evolution for NO3− to NH3 (blue line), NO2− (red line), and N2 (green line). In this figure, the NO3− reduction intermediates highlighted by the blue shadow are dispersed in the electrolyte, and the NO3− reduction intermediates highlighted by the green, orange, and purple shadows are adsorbed on a bridge site, hollow site, and top site on RuPtPdCu (111), respectively.
Key performance comparisons among different catalysts (C control, Ru, and Ru-MEA) in 0.5 M Na2SO4 containing 50 mM NO3−, pH2.5: (a) Linear sweep voltammetry (scan rate 5 mV s−1). (b) FENO2− and FENH3 at −1.13 V vs RHE. (c) NH3 yield (g h−1 cm−2) at −1.13 V vs RHE. Electrocatalytic performance of Ru-MEA in 0.5 M Na2SO4 containing 50 mM NaNO3, pH 2.5 at different applied potentials: (d) FENH3. (e) Selectivity toward NH3 and NO2−. (f) NH3 yield (g h−1 cm−2). Error bars indicate the standard deviation of the FE calculation from at least three independent samples. (g) FENH3 of Ru-MEA catalyst with varying applied potentials and NO3− concentrations (10, 50, and 100 mM NO3−) in moderate acidic media (pH 2.5).
Please read more in our work (Yang et al., 2023).
