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We have previously shown that Pt–Ni alloy nano-octahedra with {111} facets exhibit outstanding electrochemical performance in the oxygen reduction reaction (ORR) in acidic media when their surfaces are finely tailored at the atomic level. In this investigation, we further refine the surface structure of Pt2.2Ni octahedral nanocatalysts to improve ORR performance in a 0.1 M KOH solution using diverse surface manipulation techniques. Through systematic analysis using electrochemical CO stripping, cyclic voltammetry, and X-ray photoelectron spectroscopy, we examined the surfaces of Pt2.2Ni octahedral nanocatalysts pretreated with various methods, including etching in acetic acid or perchloric acid, and subsequent electrochemical activation in an alkaline solution or an acidic solution. Among these treatments, those involving acidic media, particularly electrochemical cycling in acidic electrolytes, demonstrated significantly enhanced ORR activity in 0.1 M KOH. The latter exhibited a mass activity of 2.95 A/mgpt and a specific activity of 8.71 mA/cm2 at 0.90 V, surpassing state-of-the-art Pt/C by 12-fold and 34-fold, respectively. Furthermore, this identified nanocatalyst displayed robust stability, with negligible activity decay observed after 10,000 cycles. This study suggests that the improved ORR activity can be attributed to the Pt-rich surfaces with well-preserved {111} lattices on the surface-modified Pt–Ni nano-octahedra. 

Despite the critical role of sintering phenomena in constraining the long-term durability of nano-sized particles, a clear understanding of nanoparticle sintering has remained elusive due to the challenges in atomically tracking the neck initiation and discerning different mechanisms. Through the integration of in-situ transmission electron microscopy and atomistic modeling, this study uncovers the atomic dynamics governing the neck initiation of Pt-Fe nanoparticles via a surface self-diffusion process, allowing for coalescence without significant particle movement. Real-time imaging reveals that thermally activated surface morphology changes in individual nanoparticles induce significant surface self-diffusion. The kinetic entrapment of self-diffusing atoms in the gaps between closely spaced nanoparticles leads to the nucleation and growth of atomic layers for neck formation. This surface self-diffusion-driven sintering process is activated at a relatively lower temperature compared to the classic Ostwald ripening and particle migration and coalescence processes. The fundamental insights have practical implications for manipulating the morphology, size distribution, and stability of nanostructures by leveraging surface self-diffusion processes. 

Abstract To achieve environmentally benign energy conversion with the carbon neutrality target via electrochemical reactions, the innovation of electrocatalysts plays a vital role in the enablement of renewable resources. Nowadays, Pt-based nanocrystals (NCs) have been identified as one class of the most promising candidates to efficiently catalyze both the half-reactions in hydrogen- and hydrocarbon-based fuel cells. Here, we thoroughly discuss the key achievement in developing shape-controlled Pt and Pt-based NCs, and their electrochemical applications in fuel cells. We begin with a mechanistic discussion on how the morphology can be precisely controlled in a colloidal system, followed by highlighting the advanced development of shape-controlled Pt, Pt-alloy, Pt-based core@shell NCs, Pt-based nanocages, and Pt-based intermetallic compounds. We then select some case studies on models of typical reactions (oxygen reduction reaction at the cathode and small molecular oxidation reaction at the anode) that are enhanced by the shape-controlled Pt-based nanocatalysts. Finally, we provide an outlook on the potential challenges of shape-controlled nanocatalysts and envision their perspective with suggestions. "Image missing" 

This study outlines the preparation and characterization of a unique superlattice composed of indium oxide (In2O3) vertex-truncated nano-octahedra, along with an exploration of its response to high-pressure conditions. Transmission electron microscopy and scanning transmission electron microscopy were employed to determine the average circumradius (15.2 nm) of these vertex-truncated building blocks and their planar superstructure. The resilience and response of the superlattice to pressure variations, peaking at 18.01 GPa, were examined by using synchrotron-based Wide-Angle X-ray Scattering (WAXS) and Small-Angle X-ray Scattering (SAXS) techniques. The WAXS data revealed no phase transitions, reinforcing the stability of the 2D superlattice comprised of random layers in alignment with a p31m planar symmetry as discerned by SAXS. Notably, the SAXS data also unveiled a pressure-induced, irreversible translation of octahedra and ligand interaction occurring within the random layer. Through our examination of these pressure-sensitive behaviors, we identified a distinctive translation model inherent to octahedra and observed modulation in the superlattice cell parameter induced by pressure. This research signifies a noteworthy advancement in deciphering the intricate behaviors of 2D superlattices under high pressure. 

Abstract Among the multi-metallic nanocatalysts, Pt-based alloy nanocrystals (NCs) have demonstrated promising performance in fuel cells and water electrolyzers. Herein, we demonstrate a facile colloidal synthesis of monodisperse trimetallic Pt–Fe–Ni alloy NCs through a co-reduction of metal precursors. The as-synthesized ternary NCs exhibit superior mass and specific activities toward oxygen reduction reaction (ORR), which are ∼2.8 and 5.6 times as high as those of the benchmark Pt/C catalyst, respectively. The ORR activity of the carbon-supported Pt–Fe–Ni nanocatalyst is persistently retained after the durability test. Owing to the incorporation of Fe and Ni atoms into the Pt lattice, the as-prepared trimetallic Pt-alloy electrocatalyst also manifestly enhances the electrochemical activity and durability toward the oxygen evolution reaction with a reduced overpotential when compared with that of the benchmark Pt/C (△ η = 0.20 V, at 10 mA cm −2 ). This synthetic strategy paves the way for improving the reactivity for a broad range of electrocatalytic applications. 

In-memory computing represents an effective method for modeling complex physical systems that are typically challenging for conventional computing architectures but has been hindered by issues such as reading noise and writing variability that restrict scalability, accuracy, and precision in high-performance computations. We propose and demonstrate a circuit architecture and programming protocol that converts the analog computing result to digital at the last step and enables low-precision analog devices to perform high-precision computing. We use a weighted sum of multiple devices to represent one number, in which subsequently programmed devices are used to compensate for preceding programming errors. With a memristor system-on-chip, we experimentally demonstrate high-precision solutions for multiple scientific computing tasks while maintaining a substantial power efficiency advantage over conventional digital approaches.