Iron-incorporated nickel-based materials show promise as catalysts for the oxygen evolution reaction (OER) halfreaction of water electrolysis. Nickel has also exhibited high catalytic activity for methanol oxidation, particularly when in the form of a bimetallic catalyst. In this work, bimetallic iron−nickel nanoparticles were synthesized using a multistep procedure in water under ambient conditions. When compared to monometallic iron and nickel nanoparticles, Fe−Ni nanoparticles show enhanced catalytic activity for both OER and methanol oxidation under alkaline conditions. At 1 mA/cm 2 , the overpotential for monometallic iron and nickel nanoparticles was 421 and 476 mV, respectively, while the bimetallic Fe−Ni nanoparticles had a greatly reduced overpotential of 256 mV. At 10 mA/cm 2 , bimetallic Fe−Ni nanoparticles had an overpotential of 311 mV. Spectroscopy characterization suggests that the primary phase of nickel in Fe−Ni nanoparticles is the more disordered alpha phase of nickel hydroxide.

Bimetallic nanoparticles are of immense scientific and technological interest given the synergistic properties observed when two different metallic species are mixed at the nanoscale. This is particularly prevalent in catalysis, where bimetallic nanoparticles often exhibit improved catalytic activity and durability over their monometallic counterparts. Yet despite intense research efforts, little is understood regarding how to optimize bimetallic surface composition and structure synthetically using rational design principles. Recently, it has been demonstrated that peptide-enabled routes for nanoparticle synthesis result in materials with sequence-dependent catalytic properties, providing an opportunity for rational design through sequence manipulation. In this study, bimetallic PdAu nanoparticles are synthesized with a small set of peptides containing known Pd and Au binding motifs. The resulting nanoparticles were extensively characterized using high-resolution scanning transmission electron microscopy, X-ray absorption spectroscopy, and high-energy X-ray diffraction coupled to atomic pair distribution function analysis. Structural information obtained from synchrotron radiation methods was then used to generate model nanoparticle configurations using reverse Monte Carlo simulations, which illustrate sequence dependence in both surface structure and surface composition. Replica exchange with solute tempering molecular dynamics simulations were also used to predict the modes of peptide binding on monometallic surfaces, indicating that different sequences bind to the metal interfaces via different mechanisms. As a testbed reaction, electrocatalytic methanol oxidation experiments were performed, wherein differences in catalytic activity are clearly observed in materials with identical bimetallic composition. Taken together, this study indicates that peptides could be used to arrive at bimetallic surfaces with enhanced catalytic properties, which could be leveraged for rational bimetallic nanoparticle design using peptide-enabled approaches.

The objective of this investigation was to develop a surface complexation modeling approach to account for proton and metal (Cd, Pb) binding onto many-layered graphene oxide (MLGO) across a range of pH and ionic strength conditions. MLGO particles exhibit large buffering capacities between pH 3 and pH 10 and the buffering behavior is only nominally influenced by ionic strength. In contrast, batch metal sorption experiments illustrate that the striking capacity of MLGO to sorb metals substantially diminishes with increases in ionic strength. X-ray absorption spectroscopy measurements were used to establish reaction stoichiometries and indicate that both Cd and Pb associate with single sites on the MLGO surface. The difference in sorption behaviors for protons and metals is best modeled using a 4site non-electrostatic surface complexation model that accounts for ionic strength effects as a competition between Na from the background electrolyte and Cd/Pb for available MLGO sorption sites. Using this approach, titration data are used to constrain the site concentrations and pK a values for MLGO binding sites. The pK a values (±1σ) are calculated as 4.55 (± 0.91), 6.52 (± 0.49), 8.48 (± 0.21), and 9.98 (± 0.21). We then use these parameters and the metal sorption data to determine thermodynamic stability constants for each important Cd-and Pb-MLGO surface complex. The site concentrations and equilibrium constants provided herein are critical for developing and testing remediation strategies for specific water chemistries.

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