Development of low-cost and high-performance oxygen evolution reaction catalysts is keyto implementing polymer electrolyte membrane water electrolyzers for hydrogen production. Iridiumbased oxides are the state-of-the-art acidic oxygen evolution reactio catalysts but still suffer from inadequate activity and stability, and iridium's scarcity motivates the discovery of catalysts with lower iridium loadings. Here we report a mass-selected iridium-tantalum oxide catalyst prepared by a magnetron-based cluster source with considerably reduced noble-metal loadings beyond a commercial IrO2 catalyst. A sensitive electrochemistry/mass-spectrometry instrument coupled with isotope labelling was employed to investigate the oxygen production rate under dynamic operating conditions to account for the occurrence of side reactions and quantify the number of surface active sites. Iridium-tantalum oxide nanoparticles smaller than 2 nm exhibit a mass activity of 1.2 ± 0.5 kA g Ir -1 and a turnover frequency of 2.3 ± 0.9 s -1 at 320 mV overpotential, which are two and four times higher than those of mass-selected IrO2, respectively. Density functional theory calculations reveal that special iridium coordinations and the lowered aqueous decomposition free energy might be responsible for the enhanced performance.Water electrolysis (2H2O → 2H2 + O2) driven by renewable power sources (for example, solar and wind) offers a sustainable strategy to store energy in the form of hydrogen fuel 1,2 . The polymer electrolyte membrane water electrolyzer (PEM-WE) operating in acidic media serves as a promising technology for such energy conversion and is preferable to alkaline conditions for hydrogen production because of its high current density, fast response, stable operation performance and low cross-over under pressurized
Single atom detection is of key importance to solving a wide range of scientific and technological problems. The strong interaction of electrons with matter makes transmission electron microscopy one of the most promising techniques. In particular, aberration correction using scanning transmission electron microscopy has made a significant step forward toward detecting single atoms. However, to overcome radiation damage, related to the use of high-energy electrons, the incoming electron dose should be kept low enough. This results in images exhibiting a low signal-to-noise ratio and extremely weak contrast, especially for light-element nanomaterials. To overcome this problem, a combination of physics-based model fitting and the use of a model-order selection method is proposed, enabling one to detect single atoms with high reliability.
Recently, the maximum a posteriori (MAP) probability rule has been proposed as an objective and quantitative method to detect atom columns and even single atoms from high-resolution high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) images. The method combines statistical parameter estimation and model-order selection using a Bayesian framework and has been shown to be especially useful for the analysis of the structure of beam-sensitive nanomaterials. In order to avoid beam damage, images of such materials are usually acquired using a limited incoming electron dose resulting in a low contrast-to-noise ratio (CNR) which makes visual inspection unreliable. This creates a need for an objective and quantitative approach. The present paper describes the methodology of the MAP probability rule, gives its step-by-step derivation and discusses its algorithmic implementation for atom column detection. In addition, simulation results are presented showing that the performance of the MAP probability rule to detect the correct number of atomic columns from HAADF STEM images is superior to that of other model-order selection criteria, including the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). Moreover, the MAP probability rule is used as a tool to evaluate the relation between STEM image quality measures and atom detectability resulting in the introduction of the so-called integrated CNR (ICNR) as a new image quality measure that better correlates with atom detectability than conventional measures such as signal-to-noise ratio (SNR) and CNR.
PhySH: Complex oxides; transition metal oxides; X-ray absorption; X-ray magnetic circular dichroism; thin films; scanning transmission electron microscopy. Abstract We report charge-transfer up to a single electron per interfacial unit cell across non-polar heterointerfaces from the Mott insulator LaTiO 3 to the charge transfer insulator LaCoO 3 . In high-quality bi-and tri-layer systems grown using pulsed laser deposition, soft X-ray absorption, dichroism and STEM-EELS are used to probe the cobalt 3d-electron count and provide an element-specific investigation of the magnetic properties. The experiments prove a deterministically-tunable charge transfer process acting in the LaCoO 3 within three unit cells of the heterointerface, able to generate full conversion to 3d 7 divalent Co, which displays a paramagnetic ground state. The number of LaTiO 3 |LaCoO 3 interfaces, the thickness of an additional 'break' layer between the LaTiO 3 and LaCoO 3 , and the LaCoO 3 film thickness itself in tri-layers provide a trio of sensitive control knobs for the charge transfer process, illustrating the efficacy of O2p-band alignment as a guiding principle for property design in complex oxide heterointerfaces.
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