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Solution-Grown Dendritic Pt-Based Ternary Nanostructures for Enhanced Oxygen Reduction Reaction Functionality.

Gerard M LetebaDavid R G MitchellPieter B J LevecqueCandace I Lang
Published in: Nanomaterials (Basel, Switzerland) (2018)
Nanoalloys with anisotropic morphologies of branched and porous internal structures show great promise in many applications as high performance materials. Reported synthetic approaches for branched alloy nanostructures are, however, limited by the synthesis using a seed-growth process. Here, we demonstrate a conveniently fast and one-pot solution-phase thermal reduction strategy yielding nanoalloys of Pt with various solute feed ratios, exhibiting hyperbranched morphologies and good dispersity. When Pt was alloyed with transition metals (Ni, Co, Fe), we observed well-defined dendritic nanostructures in PtNi, PtCo and Pt(NiCo), but not in PtFe, Pt(FeNi) or Pt(FeCo) due to the steric hindrance of the trivalent Fe(acac)₃ precursor used during synthesis. In the case of Pt-based nanoalloys containing Ni and Co, the dendritic morphological evolution observed was insensitive to large variations in solute concentration. The functionality of these nanoalloys towards the oxygen reduction reaction (ORR); however, was observed to be dependent on the composition, increasing with increasing solute content. Pt₃(NiCo)₂ exhibited superior catalytic activity, affording about a five- and 10-fold enhancement in area-specific and mass-specific catalytic activities, respectively, compared to the standard Pt/C nanocatalyst. This solution-based synthetic route offers a new approach for constructing dendritic Pt-based nanostructures with excellent product yield, monodispersity and high crystallinity.
Keyphrases
  • machine learning
  • deep learning
  • artificial intelligence
  • transition metal