Catalytic reduction with Pd has emerged as a promising technology to remove a suite of contaminants from drinking water, such as oxyanions, disinfection byproducts, and halogenated pollutants, but low activity is a major challenge for application. To address this challenge, we synthesized a set of shape-and size-controlled Pd nanoparticles and evaluated the activity of three probe contaminants (i.e., nitrite, N-nitrosodimethylamine (NDMA), and diatrizoate) as a function of facet type (e.g., ( 100), ( 110), ( 111)), ratios of low-to high-coordination sites, and ratios of surface sites to total Pd (i.e., dispersion). Reduction results for an initial contaminant concentration of 100 μM show that initial turnover frequency (TOF 0 ) for nitrite increases 4.7-fold with increasing percent of (100) surface Pd sites (from 0% to 95.3%), whereas the TOF 0 for NDMA and for diatrizoate increases 4.5-and 3.6-fold, respectively, with an increasing percent of terrace surface Pd sites (from 79.8% to 95.3%). Results for an initial nitrite concentration of 2 mM show that TOF 0 is the same for all shape-and size-controlled Pd nanoparticles. Trends for TOF 0 were supported by results showing that all catalysts but one were stable in shape and size up to 12 days; for the exception, iodide liberation in diatrizoate reduction appeared to be responsible for a shape change of 4 nm octahedral Pd nanoparticles. Density functional theory (DFT) simulations for the free energy change of hydrogen (H 2 ), nitrite, and nitric oxide (NO) adsorption and a two-site model based on the Langmuir−Hinshelwood mechanism suggest that competition of adsorbates for different Pd sites can explain the TOF 0 results. Our study shows for the first time that catalytic reduction activity for waterborne contaminant removal varies with the Pd shape and size, and it suggests that Pd catalysts can be tailored for optimal performance to treat a variety of contaminants for drinking water.
Azo dyes are widespread pollutants and potential cocontaminants for nitrate; we evaluated their effect on catalytic reduction of a suite of oxyanions, diatrizoate, and N-nitrosodimethylamine (NDMA). The azo dye methyl orange significantly enhanced (less than or equal to a factor of 5.24) the catalytic reduction kinetics of nitrate, nitrite, bromate, perchlorate, chlorate, and diatrizoate with several different Pd-based catalysts; NDMA reduction was not enhanced. Nitrate was selected as a probe contaminant, and a variety of azo dyes (methyl orange, methyl red, fast yellow AB, metanil yellow, acid orange 7, congo red, eriochrome black T, acid red 27, acid yellow 11, and acid yellow 17) were evaluated for their ability to enhance reduction. Hydrogenation energies of azo dyes were calculated using density functional theory and a volcano relationship between hydrogenation energies and reduction rate enhancement was observed. A kinetic model based on Brønsted-Evans-Polanyi (BEP) theory matched the volcano relationship and suggests sorbed azo dyes enhance reduction kinetics through hydrogen atom shuttling between reduced azo dyes (i.e., hydrazo dyes) and oxyanions or diatrizoate. This is the first research that has identified this synergetic effect, and it has implications for designing more efficient catalysts and reducing Pd costs in water treatment systems.
We report experiments and simulations to understand the factors that control chromium (Cr(3+)) electrodeposition from ionic liquid solutions. Speciation, conductivities and diffusivities in mixtures of trivalent chromium chloride, water and choline chloride (CrCl3/xH2O/yChCl) were computed from molecular dynamics simulations and compared to measured ultraviolet-visible spectra, conductivities from electrical impedance spectroscopy, and cyclic voltammograms. Computed changes in Cr(3+) first solvation shell and conductivity with solution composition qualitatively agree with experimental observations. The Cr(3+) first solvation shell contains predominantly H2O and Cl(-) and the proportion of the two ligands changes with the relative bulk concentrations of each. Conductivities and diffusivities are observed to be functions of these composition variables. Variations in observed reduction current are primarily determined by dynamical properties and are less influenced by speciation.
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