Overcharging is expected to be one of the solutions to overcome the current energy density limitation of lithium‐ion battery cathodes, which will support the rapid growth of the battery market. However, high‐voltage charging often poses a major safety threat including fatal incendiary incidents, limiting further application. Numerous researches are dedicated to the disadvantages of the overcharging process; nonetheless, the urgent demand for addressing failure mechanisms is still unfulfilled. Herein, it is revealed that overcharging induces phase heterogeneity into layered and cobalt oxide phases, and consequent “twin‐like deformation” in lithium cobalt oxide. The interplay between the uncommon cobalt(III) oxide and the deformation is investigated by revealing the atomistic formation mechanism. Most importantly, abnormal cracking is discovered in the vicinity of the cobalt oxide where structural instability induces substantial contraction. In addition, surface degradation is widely observed in the crack boundary inside the particle. As unintentional overcharging can occur due to local imbalance in state‐of‐charge in severe operating conditions such as fast charging, the issues on overcharging should be emphasized to large extent and this study provides fundamental knowledge of overcharge by elucidating the crack development mechanism of layered cathodes, which is expected to broaden the horizon into high voltage operation.
Understanding the chemical states of individual surface atoms and their arrangements is essential for addressing several current issues such as catalysis, energy stroage/ conversion, and environmental protection. Here, we exploit a profile imaging technique to understand the correlation between surface atomic structures and the oxygen evolution reaction (OER) in Mn 3 O 4 nanoparticles. We image surface structures of Mn 3 O 4 nanoparticles and observe surface reconstructions in the ( 110) and ( 101) planes. Mn 3+ ions at the surface, which are commonly considered as the active sites in OER, disappear from the reconstructed planes, whereas Mn 3+ ions are still exposed at the edges of nanoparticles. Our observations suggest that surface reconstructions can deactivate low-index surfaces of Mn oxides in OER. These structural and chemical observations are further validated by density functional theory calculations. This work shows why atomic-scale characterization of surface structures is crucial for a molecular-level understanding of a chemical reaction in oxide nanoparticles.S urface chemistry and reactions are fundamental to the properties of various functional materials, including solid catalysts, supercapacitors, and sensors. 1 At the molecular level, surface atoms interact differently with surrounding molecules depending on their local atomic arrangements, such as facet, step, edge, and corner atoms, and surface defects, causing considerable variations in the chemical environment. 2 Furthermore, surface relaxation and reconstruction also significantly alter chemical reactions at the surface because of modified electronic structures. Together, surface atomic arrangements and surface reconstructions constitute what is broadly defined as surface structures. Because of the complexity of surface structures, atomic-level characterization is essential for a molecular-level understanding of surface chemical reactions. For example, identification of the active sites among various surface atoms in catalysis can lead to direct advances in catalyst design. 3 While a variety of advanced surface characterization techniques have been developed and employed to obtain information associated with chemical reactions at specific surface sites, most techniques have their own restrictions for the surface types that can be studied, and accurate measurement of atomic and electronic structures with high precision remains difficult in nanostructured materials. 4 Surface profile imaging 5,6 by transmission electron microscopy (TEM), particularly scanning transmission electron microscopy (STEM) in combination with electron energy loss spectroscopy (EELS), is a novel technique for the analysis of nanoparticle surfaces. The high-angle annular dark-field (HAADF) mode in STEM allows individual atomic columns to be located, and EELS provides information on the electronic and chemical states simultaneously. Recently, the capability of this technique has improved significantly due to the dramatic advances in aberration correction. Surfaces of the ...
Amorphous materials have been used in a range of electronic and photonic applications, and the need for quantitative analytical techniques on their local structural information is growing. We present a comprehensive analysis of the atomic and electronic structures of an amorphous material, amorphous carbon (a-C), with scanning transmission electron microscopy (STEM)-derived techniques, four-dimensional STEM (4D-STEM), and STEM-electron energy loss spectroscopy (STEM-EELS). Each diffraction pattern of an a-C layer stack acquired via 4D-STEM is transformed into a reduced density function (RDF) and a radial variance profile (RVP) to retrieve the information on the atomic structures. Importantly, a machine-learning approach (preferably cluster analysis) separates distinct features in the EELS and RDF datasets; it also describes the spatial distributions of these features in the scanned regions. Consequently, we showed that the differences in the sp2/ sp3 ratio and the involvement of additional elements led to changes in the bond length. Furthermore, we identified the dominant types of medium-range ordering structures (diamond-like or graphite-like nano-crystals) by correlations among the EELS, RDF, and RVP data. The information obtained via STEM-EELS and 4D-STEM can be strongly correlated, leading to the comprehensive characterization of the a-C layer stack for a nanometer-scale area. This process can be used to investigate any amorphous material, thereby yielding comprehensive information regarding the origins of notable properties.
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