Control of structure at the atomic level can precisely and effectively tune catalytic properties of materials, enabling enhancement in both activity and durability. We synthesized a highly active and durable class of electrocatalysts by exploiting the structural evolution of platinum-nickel (Pt-Ni) bimetallic nanocrystals. The starting material, crystalline PtNi3 polyhedra, transforms in solution by interior erosion into Pt3Ni nanoframes with surfaces that offer three-dimensional molecular accessibility. The edges of the Pt-rich PtNi3 polyhedra are maintained in the final Pt3Ni nanoframes. Both the interior and exterior catalytic surfaces of this open-framework structure are composed of the nanosegregated Pt-skin structure, which exhibits enhanced oxygen reduction reaction (ORR) activity. The Pt3Ni nanoframe catalysts achieved a factor of 36 enhancement in mass activity and a factor of 22 enhancement in specific activity, respectively, for this reaction (relative to state-of-the-art platinum-carbon catalysts) during prolonged exposure to reaction conditions.

The accumulation and extrusion of Ca 2+ in the pre-and postsynaptic compartments play a critical role in initiating plastic changes in biological synapses. To emulate this fundamental process in electronic devices, we developed diffusive Ag-in-oxide memristors with a temporal response during and after stimulation similar to that of the synaptic Ca 2+ dynamics. In situ high-resolution transmission electron microscopy and nanoparticle dynamics simulations both demonstrate that Ag atoms disperse under electrical bias and regroup spontaneously under zero bias because of interfacial energy 2 minimization, closely resembling synaptic influx and extrusion of Ca 2+ , respectively.The diffusive memristor and its dynamics enable a direct emulation of both short-and long-term plasticity of biological synapses and represent a major advancement in hardware implementation of neuromorphic functionalities.CMOS circuits have been employed to mimic synaptic Ca 2+ dynamics, but three-terminal devices bear limited resemblance to bio-counterparts at the mechanism level and require significant numbers and complex circuits to simulate synaptic behavior [1][2][3] . A substantial reduction in footprint, complexity and energy consumption can be achieved by building a two-terminal circuit element, such as a memristor directly incorporating Ca 2+ -like dynamics.Various types of memristors based on ionic drift (drift-type memristor) 4-8 have recently been utilized for this purpose in neuromorphic architectures [9][10][11][12][13][14][15] . Although qualitative synaptic functionality has been demonstrated, the fast switching and non-volatility of drift memristors optimized for memory applications do not faithfully replicate the nature of plasticity. Similar issues also exist in MOS-based memristor emulators [16][17][18] , although they are capable of simulating a variety of synaptic functions including spike-timing-dependent plasticity (STDP). Recently, Lu's group adopted second-order drift memristors to approximate the Ca 2+ dynamics of chemical synapses by utilizing thermal dissipation 19 or mobility decay 20 , which successfully demonstrated STDP with non-overlapping spikes and other synaptic functions, representing a significant step towards bio-realistic synaptic devices. This approach features repeatability and simplicity, but the significant differences of the dynamical response from actual synapses limit the fidelity and variety of desired synaptic functions. A device with similar physical behavior as the biological Ca 2+ dynamics would enable improved emulation of synaptic function and broad applications to neuromorphic computing. Here we report such an emulator, which is a memristor based on metal atom 3 diffusion and spontaneous nanoparticle formation, as determined by in situ high-resolution transmission electron microscopy (HRTEM) and nanoparticle dynamics simulations. The dynamical properties of the diffusive memristors were confirmed to be functionally equivalent to Ca 2+ in bio-synapses, and their operating characteri...

Earth-abundant first-row (3d) transition metal-based catalysts have been developed for the oxygen-evolution reaction (OER); however, they operate at overpotentials substantially above thermodynamic requirements. Density functional theory suggested that non-3d high-valency metals such as tungsten can modulate 3d metal oxides, providing near-optimal adsorption energies for OER intermediates. We developed a room-temperature synthesis to produce gelled oxyhydroxides materials with an atomically homogeneous metal distribution. These gelled FeCoW oxyhydroxides exhibit the lowest overpotential (191 millivolts) reported at 10 milliamperes per square centimeter in alkaline electrolyte. The catalyst shows no evidence of degradation after more than 500 hours of operation. X-ray absorption and computational studies reveal a synergistic interplay between tungsten, iron, and cobalt in producing a favorable local coordination environment and electronic structure that enhance the energetics for OER.

To enhance and optimize nanocatalyst performance and durability for the oxygen reduction reaction in fuel-cell applications, we look beyond Pt-metal disordered alloys and describe a new class of Pt-Co nanocatalysts composed of ordered Pt(3)Co intermetallic cores with a 2-3 atomic-layer-thick platinum shell. These nanocatalysts exhibited over 200% increase in mass activity and over 300% increase in specific activity when compared with the disordered Pt(3)Co alloy nanoparticles as well as Pt/C. So far, this mass activity for the oxygen reduction reaction is the highest among the Pt-Co systems reported in the literature under similar testing conditions. Stability tests showed a minimal loss of activity after 5,000 potential cycles and the ordered core-shell structure was maintained virtually intact, as established by atomic-scale elemental mapping. The high activity and stability are attributed to the Pt-rich shell and the stable intermetallic Pt(3)Co core arrangement. These ordered nanoparticles provide a new direction for catalyst performance optimization for next-generation fuel cells.