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Nanomaterial properties and functionalities are influenced by their shape, size, and chemical composition. The importance of these parameters highlights the need for a statistically robust analysis of a large particle population, necessitating automation. This study introduces a neural network‐empowered smart scan technique that achieves a relative increase in speed compared to traditional energy‐dispersive X‐ray spectroscopy (EDX) mapping. The main advantage is that it reduces the required dose, decreasing potential damage to the sample by avoiding unnecessary exposure. It holds potential use in other multimodal scanning transmission electron microscopy or scanning‐based imaging approaches. In the first example, identifying particles in a matrix with a trained neural network reduces the acquisition time by two orders of magnitude. This acceleration enables a statistical compositional analysis of thousands of particles in less than 1 h. Similar improvements are observed for atomic resolution. The discrete positions of atoms identified by the trained network allow for selective EDX sampling at these centers, thereby identifying the atomic species of the column with much‐reduced sampling. Consequently, a lower sampling dose is required, enabling mapping of more delicate materials with high lateral resolution and at a high statistical confidence interval. Even though manual training is still required, this approach greatly benefits repetitive quality control tasks. [ABSTRACT FROM AUTHOR]

YFeO3 thin films are a recent addition to the family of multiferroic orthoferrites where YFe antisite defects and strain have been shown to introduce polar displacements while retaining magnetic properties. Complete control of the multiferroic properties, however, necessitates knowledge of the defects present and their potential role in modifying behavior. Here, the structure and chemistry of antiphase boundaries in Y‐rich multiferroic YFeO3 thin films are reported using aberration corrected scanning transmission electron microscopy combined with atomic resolution energy dispersive X‐ray spectroscopy. It is found that FeY antisites, which are not stable in the Y‐rich film bulk, periodically arrange along antiphase boundaries due to changes in the local structural environment. Using density functional theory, it is shown that the antiphase boundaries are polar and bi‐stable, where the presence of FeY antisites significantly decreases the switching barrier. These results highlight how planar defects, such as antiphase boundaries, can stabilize point defects that would otherwise not be expected to form within the structure. [ABSTRACT FROM AUTHOR]

In recent years, potassium sodium niobate (K0.5Na0.5NbO3, KNN) has become popular and promising among perovskite lead-free piezoceramic systems. In this study, the chemical stability of KNN powders in aqueous medium was investigated as a function of pH, time, and powder surface area. To better understand the dissolution behavior of the complex KNN stoichiometry, subconstituents such as potassium niobate ( KNbO3, KN) and sodium niobate (NaNbO3, NN) were investigated separately first. Results showed that all of the cations in the structure underwent dissolution in different values. Indicating that KNN undergoes incongruent dissolution in aqueous medium, the dissolution of A site cations was higher at lower pH while the dissolution of B site cations increased at higher initial pH. The order of released cation concentrations ( CA1 = K > CA2 = Na > CB = Nb) fits with inverse relationship of cation field strength ( FS) order, B = Nb5+ FS > A2 = Na+ FS>A1 = K+ FS, at pH 4, 7 and 10 for NN, KN, and KNN. Calculated diffuse layer thickness from the ICP data confirmed to outer amorphous layer in TEM image. Also, the ratio of normalized cation concentration versus surface area of powders showed that incongruent dissolution kinetic was driven by the diffusion step. [ABSTRACT FROM AUTHOR]

We present the first copper iridium binary metal oxide with the chemical formula Cu2IrO3. The material is synthesized from the parent compound Na2IrO3 by a topotactic reaction where sodium is exchanged with copper under mild conditions. Cu2IrO3 has the same monoclinic space group (C2/c) as Na2IrO3 with a layered honeycomb structure. The parent compound Na2IrO3 is proposed to be relevant to the Kitaev spin liquid on the basis of having Ir4+ with an effective spin of 1/2 on a honeycomb lattice. Remarkably, whereas Na2IrO3 shows a long-range magnetic order at 15 K and fails to become a true spin liquid, Cu2IrO3 remains disordered until 2.7 K, at which point a short-range order develops. Rietveld analysis shows less distortions in the honeycomb structure of Cu2IrO3 with bond angles closer to 120° compared to Na2IrO3. Thus, the weak short-range magnetism combined with the nearly ideal honeycomb structure places Cu2IrO3 closer to a Kitaev spin liquid than its predecessors. [ABSTRACT FROM AUTHOR]

We present the first copper iridium binary metal oxide with the chemical formula Cu 2 IrO 3 . The material is synthesized from the parent compound Na 2 IrO 3 by a topotactic reaction where sodium is exchanged with copper under mild conditions. Cu 2 IrO 3 has the same monoclinic space group (C2/c) as Na 2 IrO 3 with a layered honeycomb structure. The parent compound Na 2 IrO 3 is proposed to be relevant to the Kitaev spin liquid on the basis of having Ir 4+ with an effective spin of 1/2 on a honeycomb lattice. Remarkably, whereas Na 2 IrO 3 shows a long-range magnetic order at 15 K and fails to become a true spin liquid, Cu 2 IrO 3 remains disordered until 2.7 K, at which point a short-range order develops. Rietveld analysis shows less distortions in the honeycomb structure of Cu 2 IrO 3 with bond angles closer to 120° compared to Na 2 IrO 3 . Thus, the weak short-range magnetism combined with the nearly ideal honeycomb structure places Cu 2 IrO 3 closer to a Kitaev spin liquid than its predecessors.