Electrochemical carbon dioxide (CO 2 ) reduction is an emerging technology for efficiently recycling CO 2 into fuel, and many studies of this reaction are focused on developing advanced catalysts with high activity, selectivity, and durability. Of these catalysts, oxide-derived metal nanoparticles, which are prepared by reducing a metal oxide, have received considerable attention due to their catalytic properties. However, the mechanism of the nanoparticles' activity enhancement is not well-understood. Recently, it was discovered that the catalytic activity is quantitatively correlated to the surface density of grain boundaries (GBs), implying that GBs are mechanistically important in electrochemical CO 2 reduction. Here, using extensive density functional theory (DFT) calculations modelling the atomistic structure of GBs on the Au (111) surface, we suggest a mechanism of electrochemical CO 2 reduction to CO mediated by GBs; the broken local spatial symmetry near a GB tunes the Au metal-to-adsorbate π-backbonding ability, thereby stabilizing the key COOH intermediate. This stabilization leads to a decrease of ~200 mV in the overpotential and a change in the rate-determining step to the second reduction step, of which are consistent with previous experimental observations. The atomistic and electronic details of the mechanistic role of GBs during electrochemical CO 2 reduction presented in this work demonstrate the structure-activity relationship of atomically disordered metastable structures in catalytic applications.

The electrochemical conversion of nitric oxide (NO) to ammonia (NH3) provides a sustainable route to transform an air pollutant into a value-added chemical. However, the development of NO electroreduction remains hindered by the poor solubility in aqueous electrolytes, requiring the use of concentrated NO. Here, we report a dilute NO reduction using a gas diffusion electrode (GDE) to circumvent the mass transport issue. Through the incorporation of nanoscale zero-valent iron into carbon black on the GDE, 96% NH3 Faradaic efficiency was achieved with 1% NO, and the computational calculations revealed that the Fe catalyzed the breaking of the N–O bond in the H2NO intermediate. The NH3 production rate was accelerated by controlling the concentration of protons in the electrolyte and reached 1239 μmol cm–2 h–1 with 10% NO. Our findings show that the gas-phase electrolysis of dilute NO can offer a practical option for upcycling the waste nitrogen.

Materials design increasingly relies on first-principles calculations for screening important candidates and for understanding quantum mechanisms. Density functional theory (DFT) is by far the most popular first-principles approach due to its efficiency and accuracy.However, to accurately predict structures and thermodynamics, DFT must be paired with a van

Density functional theory (DFT) calculations using sixteen different approaches, fourteen of which were designed to include dispersion interactions [DFT + D and van der Waals (vdW)-DF methods], were performed for a set of sixteen framework compounds with either SiO2 or AlPO4 composition. The compounds include four dense structures (α-quartz, α-cristobalite, and their AlPO4 analogues), eight all-silica zeolites, and four aluminophosphate zeotypes (AlPOs). We analyzed the performance in reproducing the equilibrium structure for all systems, and computed bulk moduli and relative stabilities were compared to experiments for those compounds where experimental data are available. We found that the results obtained with functionals that take into account dispersive interactions are closer to experiments than those obtained with a bare generalized gradient functional. However, the variation among individual methods is considerable, and functionals that perform well for one quantity may give rather large deviations for another. Taking together the whole body of results, it appears that the Perdew-Burke-Ernzerhof functional including a many-body dispersion correction and the rev-vdW-DF2 methods present the best performance for the description of SiO2 and AlPO4 materials.