Understanding electric-field-induced phase transitions is crucial for optimizing the ferroelectric and antiferroelectric properties of hafnium zirconium oxide (Hf0.5Zr0.5O2, HZO) thin films. Here, we use in situ transmission electron microscopy (TEM) to uncover the nanoscale mechanism of field-induced phase evolution in ultrathin HZO films at the morphotropic phase boundary (MPB), directly visualizing oxygen vacancy migration and its correlation with the transformation from the nonpolar tetragonal to polar orthorhombic phase. Our in situ TEM setup applied sub-100 μs bipolar voltage pulses, mimicking real device operation while allowing the detection of the subtle changes induced by such short pulses. Unsupervised machine learning analysis of electron energy-loss spectroscopy spectrum images (EELS-SIs) revealed distinct spectral features associated with local structural evolution, with quantitative results confirming oxygen-deficient regions aligned with orthorhombic phase formation. Unlike conventional TEM studies confined to a few nanoscale domains, this approach enables film-scale interpretation of phase evolution, capturing broader trends beyond isolated observations. Concurrent oxygen content changes in the TiN electrode further indicate active vacancy exchange between HZO and TiN under bias. These findings directly link oxygen vacancy dynamics to polarization switching, offering critical guidance for stabilizing ferroelectric phases and advancing next-generation memory and logic devices.

Self-assembled metal nanoparticles exsolved from host oxides have gained prominence in catalysis and electrochemistry owing to their exceptional activity and stability. Understanding the relation between dopant transport and exsolution is important, as the transport mechanism of dopants toward the surface of the host oxide directly influences exsolution sites, density, and dispersion, ultimately determining catalytic functionality. However, the pathways for dopant transport and their interactions with internal defects during exsolution remain unclear due to the complexity of defects hidden in the bulk. Here, we reveal the exsolution pathway mediated by dislocation evolution within a host oxide perovskite. By employing in situ Bragg coherent X-ray diffraction imaging and transmission electron microscopy, we show that dislocations nucleate in the bulk interior and propagate to the surface during the reduction of Ru-doped BaCe0.85Y0.1Ru0.05O3-δ. Moreover, we verify that the Ru dopant is specifically correlated with the formation of mixed dislocations, which act as mobile vehicles that dynamically carry Ru defects to the surface in tandem with dislocation propagation. These findings advance our understanding of dislocation dynamics and support the development of exsolved metal nanoparticles for next-generation catalysts.

Solid-state emitters have exhibited external quantum yields (EQYs) below 65%, with no system combining unity photoluminescence quantum yield (PLQY) and commercially viable stability. These limitations are most pronounced in colloidal perovskite nanocrystals (PeNCs), given their soft ionic lattices and labile surfaces. We introduce a hierarchical shell (HS) structure comprising interbonded PbSO4-SiO2-polymer multilayers that simultaneously locks and stabilizes soft lattices and labile interfaces. HS-CsPbBr3 PeNC films exhibit T90 (10% PLQY loss) = 3211 hours under accelerated 60°C, 90% relative humidity (RH) and T90 = 12,000 hours under blue-light exposure. HS strategy generalizes across PeNC compositions-including mixed-halide, mixed-cation, iodide, and hybrid PeNCs-and enables MAPbBr3 with extended T90 = 3900 hours (60°C, 90% RH) and T90 = 27,234 hours (blue light). Moreover, HS-MAPbBr3 films with 100.0% PLQY eliminate self-absorption losses and achieve an EQY of 91.4%, approaching the theoretical maximum. The HS barrier also prevents lead leakage for safety of large-area, high-resolution displays and bio-optoelectronics.

Self-assembled metal nanoparticles exsolved from host oxides have gained prominence in catalysis and electrochemistry owing to their exceptional activity and stability 1–3 . Understanding the relation between dopant transport and exsolution is important, as the transport mechanism of dopants toward the surface of the host oxide directly influences exsolution sites, density, and dispersion, ultimately determining catalytic functionality 4–6 . However, the pathways for dopant transport and their interaction with internal defects during exsolution remain unclear because of the complexity of defects hidden in bulk. Here, we reveal the exsolution pathway mediated by dislocation evolution within a host oxide perovskite. By employing in situ Bragg coherent X-ray diffraction imaging and transmission electron microscopy, we show that dislocations nucleate in the bulk interior and propagate to the surface during the reduction of Ru-doped in BaCe 0.85 Y 0.1 Ru 0.05 O 3-δ . Moreover, we verify that the Ru dopant is specifically correlated with the formation of mixed dislocations, which then provide transport pathways for the exsolution of Ru nanoparticles. These findings advance our understanding of dislocation dynamics and support the development of exsolved metal nanoparticles for next-generation catalysts 7,8 .

Abstract Amorphous, non‐stoichiometric gallium oxide (a‐GaOx, x < 1.5) is a promising material for many electronic devices, such as resistive switching memories, neuromorphic circuits and photodetectors. So far, all respective measurements are interpreted with the explicit or implicit assumption of n‐type band transport above the conduction band mobility edge. In this study, the experimental and theoretical results consistently show for the first time that for an O/Ga ratio x of 0.8 to 1.0 the dominating electron transport mechanism is, however, variable‐range hopping (VRH) between localized states, even at room temperature and above. The measured conductivity exhibits the characteristic exponential temperature dependence on T−1/4, in remarkable agreement with Mott's iconic law for VRH. Localized states near the Fermi level are confirmed by photoelectron spectroscopy and density of states (DOS) calculations. The experimental conductivity data is reproduced quantitatively by kinetic Monte Carlo (KMC) simulations of the VRH mechanism, based on the ab‐initio DOS. High electric field strengths F cause elevated electron temperatures and an exponential increase of the conductivity with F1/2. Novel results concerning surface oxidation, magnetoresistance, Hall effect, thermopower and electron diffusion are also reported. The findings lead to a new understanding of a‐GaOx devices, also with regard to metal|a‐GaOx Schottky barriers.

Characterizing the spatial distribution of the electromagnetic fields of a plasmonic nanoparticle is crucial for exploiting its strong light-matter interaction for optoelectronic and catalytic applications. However, observing the near-fields in three dimensions with a high spatial resolution is still challenging. To realize efficient three-dimensional (3D) nanoscale mapping of the plasmonic fields of nanoparticles with complex shapes, this work established autoencoder-embedded electron energy loss spectroscopy (EELS) tomography. A 432-symmetric chiral gold nanoparticle, a nanoparticle with a high optical dissymmetry factor, was analyzed to relate its geometrical features to its exotic optical properties. Our deep-learning-based feature extraction method discriminated plasmons with different energies in the EEL spectra of the nanoparticle in which signals from multiple plasmons were intermixed; this component was key for acceptable 3D visualization of each plasmonic field separately using EELS tomography. With this methodology, the electric field of the plasmon that induces far-field circular dichroism was observed in 3D. The field linked to this chiroptical property was strong along the swirling edges of the particle, as predicted by a numerical calculation. This study provides insight into the correlation between structural and optical chiralities through direct 3D observation of the plasmonic fields. Furthermore, the strategy of implementing an autoencoder for EELS tomography can be generalized to achieve competent 3D analysis of other features, including the optical properties of the dielectrics and chemical states.

Abstract We report on the electrical characteristics of field-effect transistors (FETs) and Schottky diodes based on In2Te3 grown on hexagonal boron nitride (h-BN) substrates utilizing molecular beam epitaxy (MBE). A two-step growth method was used to increase surface coverage and large grain sizes for high-quality In2Te3. Scanning transmission electron microscopy (STEM) imaging revealed an atomically clean and abrupt interface between the In2Te3 and h-BN substrates. Compared with the previously reported In2Te3 FETs, the MBE-grown In2Te3 FETs exhibited superior electrical properties, including a mobility of 6.07 cm2 V−1 s−1, a subthreshold swing close to 6 V dec−1, and an impressive on/off ratio of approximately 105. Furthermore, the Ti/In2Te3 Schottky diodes exhibit a low saturation current of 0.4 nA, an ideality factor of 26.7, and a Schottky barrier height of 0.68 eV.

An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

The water oxidation reaction, the most important reaction for hydrogen production and other sustainable chemistry, is efficiently catalyzed by the Mn4CaO5 cluster in biological photosystem II. However, synthetic Mn-based heterogeneous electrocatalysts exhibit inferior catalytic activity at neutral pH under mild conditions. Symmetry-broken Mn atoms and their cooperative mechanism through efficient oxidative charge accumulation in biological clusters are important lessons but synthesis strategies for heterogeneous electrocatalysts have not been successfully developed. Here, we report a crystallographically distorted Mn-oxide nanocatalyst, in which Ir atoms break the space group symmetry from I41/amd to P1. Tetrahedral Mn(II) in spinel is partially replaced by Ir, surprisingly resulting in an unprecedented crystal structure. We analyzed the distorted crystal structure of manganese oxide using TEM and investigated how the charge accumulation of Mn atoms is facilitated by the presence of a small amount of Ir.

Boron-doped amorphous carbon (a-C) films have been investigated as a hardmask material for improving semiconductor integration, deposited using direct current (DC) magnetron sputtering with varying boron concentrations. Increased boron doping concentration in a-C led to a higher etch resistance but also resulted in the gradation of etch resistivity in the depth direction of the film, as confirmed by a continuous dry etching process. Scanning transmission electron microscopy electron energy loss spectroscopy showed an increase in the sp3 ratio of the film owing to boron doping as well as gradation in the B K edge region of a film doped with a high concentration of boron. This is because the high reactivity between boron and oxygen results in the reaction of residual oxygen in the chamber with boron. Time-of-flight secondary ion mass spectrometry was used to evaluate the penetration resistance to fluorine ions in the dielectric etchant. The results confirmed that B-O bonding resulted in relatively low fluorine resistance. Boron bonded with carbon can significantly improve the dry etch performance; however, bonding with oxygen needs to be effectively controlled to realize desirable film properties. Overall, this study demonstrates the potential of boron-doped a-C films as a hardmask material for the semiconductor industry.

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.

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 Mn3O4 nanoparticles. We image surface structures of Mn3O4 nanoparticles and observe surface reconstructions in the (110) and (101) planes. Mn3+ ions at the surface, which are commonly considered as the active sites in OER, disappear from the reconstructed planes, whereas Mn3+ 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.

A novel combination of machine learning algorithms is proposed for the differentiation of distinct spectra in a large electron energy loss spectroscopy spectrum image (EELS-SI) dataset. For clustering of the EEL spectra including similar fine structures in an efficient space, linear and nonlinear dimensionality reduction methods are used to project the EEL spectra onto a low-dimensional space. Then, a density-based clustering algorithm is applied to distinguish the meaningful data clusters. By applying this strategy to various experimental EELS-SI datasets, differentiation of several groups of EEL spectra representing specific fine structures was achieved. It is possible to investigate particular fine structures by averaging all of the spectra in each cluster. Also, the spatial distributions of each cluster in the scanning regions can be observed, which enables investigation of the locations of different fine structures in materials. This method does not require any prior knowledge, i.e., it is a data-driven analysis; therefore, it can be applied to any hyperspectral image.