RESUMO
Co-electrolysis of carbon oxides and nitrogen oxides promise to simultaneously help restore the balance of the C and N cycles while producing valuable chemicals such as urea. However, co-electrolysis processes are still largely inefficient and numerous knowledge voids persist. Here, we provide a solid thermodynamic basis for modelling urea production via co-electrolysis. First, we determine the energetics of aqueous urea produced under electrochemical conditions based on experimental data, which enables an accurate assessment of equilibrium potentials and overpotentials. Next, we use density functional theory (DFT) calculations to model various co-electrolysis reactions producing urea. The calculated reaction free energies deviate significantly from experimental values for well-known GGA, meta-GGA and hybrid functionals. These deviations stem from errors in the DFT-calculated energies of molecular reactants and products. In particular, the error for urea is approximately -0.25 ± 0.10 eV. Finally, we show that all these errors introduce large inconsistencies in the calculated free-energy diagrams of urea production via co-electrolysis, such that gas-phase corrections are strongly advised.
RESUMO
Urea is a commonly used nitrogen fertiliser synthesised from ammonia and carbon dioxide using thermal catalysis. This process results in high carbon dioxide emissions associated with the required amounts of ammonia. Electrocatalysis provides an alternative method to urea production with reduced carbon emissions while utilising waste products like nitrate. This manuscript reports on urea synthesis from the electroreduction of nitrate and carbon dioxide using CuOxZnOy electrodes under mild conditions. Catalysts with different ratios of CuO and ZnO, synthesised via flame spray pyrolysis, were explored for the reaction. The results revealed that all the CuOxZnOy electrocatalyst compositions produce urea, but the efficiency strongly depends on the metal ratio composition of the catalysts. The CuO50ZnO50 composition had the best performance in terms of selectivity (41% at -0.8 V vs RHE) and activity (0.27 mA/cm2 at -0.8 V vs RHE) towards urea production. Thus, this material is one of the most efficient electrocatalysts for urea production reported so far. This study systematically evaluates bimetallic catalysts with varying compositions for urea synthesis from carbon dioxide and nitrate.
RESUMO
The complexity of the electrocatalytic reduction of CO to CH4 and C2H4 on copper electrodes prevents a straightforward elucidation of the reaction mechanism and the design of new and better catalysts. Although structural and electrolyte effects have been separately studied, there are no reports on structure-sensitive cation effects on the catalyst's selectivity over a wide potential range. Therefore, we investigated CO reduction on Cu(100), Cu(111), and Cu(polycrystalline) electrodes in 0.1 M alkaline hydroxide electrolytes (LiOH, NaOH, KOH, RbOH, CsOH) between 0 and -1.5 V vs RHE. We used online electrochemical mass spectrometry and high-performance liquid chromatography to determine the product distribution as a function of electrode structure, cation size, and applied potential. First, cation effects are potential dependent, as larger cations increase the selectivity of all electrodes toward ethylene at E > -0.45 V vs RHE, but methane is favored at more negative potentials. Second, cation effects are structure-sensitive, as the onset potential for C2H4 formation depends on the electrode structure and cation size, whereas that for CH4 does not. Fourier Transform infrared spectroscopy (FTIR) and density functional theory help to understand how cations favor ethylene over methane at low overpotentials on Cu(100). The rate-determining step to methane and ethylene formation is CO hydrogenation, which is considerably easier in the presence of alkaline cations for a CO dimer compared to a CO monomer. For Li+ and Na+, the stabilization is such that hydrogenated dimers are observable with FTIR at low overpotentials. Thus, potential-dependent, structure-sensitive cation effects help steer the selectivity toward specific products.