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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. 

Current synthesis techniques for metal oxide (MOx)-supported catalysts have certain limitations of undesired target loading, ineffective dispersion of active species over the surface, uncontrolled particle size of active species, and complicated synthesis steps. We developed a one-pot chemical vapor deposition (OP-CVD) methodology; by using which a solid metal precursor forms a vapor in a controlled condition and gets supported over the surrounding matrix. The theoretical stability followed by experimental validation using TGA is crucial for selecting the metal precursors. Three simple steps viz. premixing, dispersion, and rapid fixation by calcination are involved in the catalyst development via the OP-CVD approach. This study solely focused on the synthesis of 3d transition MOx over ceria support. The physicochemical characterizations of the prepared catalysts were performed by XRD, ICP-OES, SEM-EDX, CO pulse chemisorption, XANES, and EXAFS analyses to understand the crystal structure of involved species, target metal loading, dispersion, and particle size and prove the feasibility and viability of OP-CVD. The prepared catalysts were further tested for reverse water gas shift (RWGS) reaction to link their structural information with activity. The RWGS reaction data showed that the CO activity and CO selectivity were metal - and metal precursor-dependent. Higher CO activity of > 0.1 mol/h g-cat was observed for Cu and Co-based catalysts, with CO selectivity of ~100 %. This study provides an opportunity to produce effcient supported catalysts in a convenient way, providing effective catalytic activity. 

Abstract Microbial processes are crucial in producing and oxidizing biological methane (CH₄) in natural wetlands. Therefore, modeling methanogenesis and methanotrophy is advantageous for accurately projecting CH₄cycling. Utilizing the CLM‐Microbe model, which explicitly represents the growth and death of methanogens and methanotrophs, we demonstrate that genome‐enabled model parameterization improves model performance in four natural wetlands. Compared to the default model parameterization against CH₄flux, genomic‐enabled model parameterization added another contain on microbial biomass, notably enhancing the precision of simulated CH₄flux. Specifically, the coefficient of determination (R²) increased from 0.45 to 0.74 for Sanjiang Plain, from 0.78 to 0.89 for Changbai Mountain, and from 0.35 to 0.54 for Sallie's Fen, respectively. A drop inR²was observed for the Dajiuhu nature wetland, primarily caused by scatter data points. Theil's coefficient (U) and model efficiency (ME) confirmed the model performance from default parameterization to genome‐enabled model parameterization. Compared with the model solely calibrated to surface CH₄flux, additional constraints of functional gene data led to better CH₄seasonality; meanwhile, genome‐enabled model parameterization established more robust associations between simulated CH₄production rates and environmental factors. Sensitivity analysis underscored the pivotal role of microbial physiology in governing CH₄flux. This genome‐enabled model parameterization offers a valuable promise to integrate fast‐cumulating genomic data with CH₄models to better understand microbial roles in CH₄in the era of climate change. 

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.