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Abstract Here we provide a database comprising electronic band structures of 9,004 layered intercalation compounds, where atoms are intercalated into a host layered compound with different intercalant atoms, along with 468 structures related to the layered host compounds. Additionally, we provide properties derived from the electronic states such as band gap as well as stability-related properties like formation energies. Direct comparison of the band structures before and after intercalation is generally challenging due to changes in their space group and k-path. However, in this study, we developed new k-paths consistent with the host materials, allowing for the direct comparison of band structures before and after intercalation. This enables direct and quantitative discussion of the band structure changes induced by the intercalations and provides a valuable database for intercalant-driven band engineering. Layered intercalation compounds are widely used in many fields, including superconductivity and energy applications, and understanding of electronic structures is necessary. The feature of our database holds promises for the development of layered compounds with enhanced functionalities through database utilization.

Abstract The mechanisms underlying the influence of the surface chemistry of inorganic materials on polymer structures and fracture behaviours near adhesive interfaces are not fully understood. This study demonstrates the first clear and direct evidence that molecular surface segregation and cross-linking of epoxy resin are driven by intermolecular forces at the inorganic surfaces alone, which can be linked directly to adhesive failure mechanisms. We prepare adhesive interfaces between epoxy resin and silicon substrates with varying surface chemistries (OH and H terminations) with a smoothness below 1 nm, which have different adhesive strengths by ~13 %. The epoxy resins within sub-nanometre distance from the surfaces with different chemistries exhibit distinct amine-to-epoxy ratios, cross-linked network structures, and adhesion energies. The OH- and H-terminated interfaces exhibit cohesive failure and interfacial delamination, respectively. The substrate surface chemistry impacts the cross-linked structures of the epoxy resins within several nanometres of the interfaces and the adsorption structures of molecules at the interfaces, which result in different fracture behaviours and adhesive strengths.

Abstract Thermodynamically metastable glasses that can contain metastable species are important functional materials. X-ray absorption near-edge structure (XANES) spectroscopy is an effective technique for determining the valence states of cations, especially for the doping element in phosphors. Herein, we first confirm the valence change of silver cations from monovalent to trivalent in aluminophosphate glasses by X-ray irradiation using a combination of Ag L3-edge XANES, electron spin resonance, and simulated XANES spectra based on first-principles calculations. The absorption edge of the experimental and simulated XANES spectra demonstrate the spectral features of Ag(III), confirming that AgO exists as Ag(I)Ag(III)O2. A part of Ag(I) changes to Ag(III) by X-ray irradiation, and the generation of Ag(III) is saturated after high irradiation doses, in good agreement with conventional radiophotoluminescence (RPL) behaviour. The structural modelling based on a combination of quantum beam analysis suggests that the local coordination of Ag cations is similar to that of Ag(III), which is confirmed by density functional theory calculations. This demonstration of Ag(III) in glass overturns the conventional understanding of the RPL mechanism of silver cations, redefining the science of silver-related materials.

Large data sets are essential for building deep learning models. However, generating large datasets with higher theoretical levels and larger computational models remains difficult due to the high cost of first-principles calculation. Here, we propose a lightweight and highly accurate machine learning approach using pre-trained Graph Neural Networks (GNNs) for industrially important but difficult to scale models. The proposed method was applied to a small dataset of graphene surface systems containing surface defects, and achieved comparable accuracy with six orders of magnitude and faster learning than when the GNN was trained from scratch.

Measurement(s) electron energy loss spectroscopy Technology Type(s) density functional theory calculation Factor Type(s) organic molecules • carbon sites in a organic molecule

Abstract Aberration-corrected scanning transmission electron microscopy (STEM) is widely used for atomic-level imaging of materials but severely requires damage-free and thin samples (lamellae). So far, the preparation of the high-quality lamella from a bulk largely depends on manual processes by a skilled operator. This limits the throughput and repeatability of aberration-corrected STEM experiments. Here, inspired by the recent successes of “robot scientists”, we demonstrate robotic fabrication of high-quality lamellae by focused-ion-beam (FIB) with automation software. First, we show that the robotic FIB can prepare lamellae with a high success rate, where the FIB system automatically controls rough-milling, lift-out, and final-thinning processes. Then, we systematically optimized the FIB parameters of the final-thinning process for single crystal Si. The optimized Si lamellae were evaluated by aberration-corrected STEM, showing atomic-level images with 55 pm resolution and quantitative repeatability of the spatial resolution and lamella thickness. We also demonstrate robotic fabrication of high-quality lamellae of SrTiO3 and sapphire, suggesting that the robotic FIB system may be applicable for a wide range of materials. The throughput of the robotic fabrication was typically an hour per lamella. Our robotic FIB will pave the way for the operator-free, high-throughput, and repeatable fabrication of the high-quality lamellae for aberration-corrected STEM.

Topological materials such as topological insulators and Weyl/Dirac semimetals possess topologically protected surface states giving birth to various unique phenomena and functionaries. To investigate the surface transport phenomena toward possible application to electric devices, nano- and submicron-scale structures of topological Dirac semimetals are of particular interest since they can be grown by an economical chemical vapor deposition (CVD) method. However, quantum oscillations associated with the topological surface states have not been well explored in nano or submicron wires despite a most fundamental transport signature of the surface state. Here, we successfully observe quantum oscillations resulting from the surface states in magnetoresistance measurements for submicron wires of Dirac semimetal Cd_{3}As_{2} grown by a CVD method. The oscillation frequencies and phases suggest that the surface quantum oscillations originate from closed orbits located on each surface constructed from the Fermi arcs. Our results will stimulate further research on quantum transport phenomena in topological wires.

Artificial neural networks are applied to quantify the properties of organic molecules by introducing a new descriptor, a core‐loss spectrum, which is typically observed experimentally using electron or X‐ray spectroscopy. Using the calculated C K‐edge core‐loss spectra of organic molecules as the descriptor, the neural network models quantitatively predict both intensive and extensive properties, such as the gap between highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) (HOMO–LUMO gap) and internal energy. The prediction accuracy estimated by the mean absolute errors for the HOMO–LUMO gap and internal energy is 0.205 and 97.3 eV, respectively, which are comparable with those of previously reported chemical descriptors. This study indicates that the neural network approach using the core‐loss spectra as the descriptor has the potential to deconvolute the abundant information available in core‐loss spectra for both prediction and experimental characterization of many physical properties. The study shows the practical potential of machine‐learning‐based material property measurements taking advantage of experimental core‐loss spectra, which can be measured with high sensitivity, high spatial resolution, and high temporal resolution.

With the influence of progress in the materials informatics, development of fundamental database has been attracting growing interest. The bonding between atoms is essential component of all kinds of materials and govern their structure, stability, and properties. When we try to understand a material by breaking it down into microscopic components, bonding of diatomic system is the most fundamental. In the field of spectroscopy, diatomic molecular spectroscopy data has been studied well, and the diatomic molecular spectroscopy database [1] has been constructed recently. Concerning electronic structure, however, there is no easily accessible database of diatomic system.In order to develop a database of diatomic systems, it is important to consider adequate interaction. In addition to covalent bonding, van der Waals (vdW) interaction is also known to play an essential role especially in describing weak bonding systems such as noble gas dimers, atomic or molecular absorption, and layered materials. Thus, vdW interaction must be considered to develop database of diatomic systems so that it can be used for general purposes. One of its theoretical implementations is vdW density functional (vdW-DF) method [2], which has been developed within the framework of density functional theory 3 (DFT) and has been showing its effectiveness as general-purpose method.In this data article, we provide a vdW-DF-based calculation dataset focusing on diatomic systems. All diatomic systems containing atoms from H (Z = 1) to Ra (Z = 88) were considered, and stable structures and properties of more than 2,900 stable diatomic systems has been calculated correctly. This cyclopedic dataset of diatomic systems with consideration of vdW interaction can be useful building blocks for understanding, describing, and predicting interaction of atoms.

Controlling the phase separation phenomenon can enhance the properties of glass materials, such as transparency and strength. However, the initial and intermediate stages of phase separation of amorphous glass are yet to be understood completely. In this study, we performed an in situ observation on glass through scanning transmission electron microscopy, which possesses a high spatial resolution and chemical sensitivity. We visualized the phase-separated structure in the initial and intermediate stages of phase separation and observed a local and rapid change in the phase-separated structures and the formation of regions with advanced and delayed degrees of phase separation. The results were compared with the phase-field simulation and it was concluded that the characteristic change of the phase-separated structures is attributable to the multimetastability of the amorphous phase.

Bisphosphonates (BPs) have been widely, efficiently, and safely used for the treatment of various bone-related diseases such as osteoporosis. However, concerns about jaw osteonecrosis associated with oral treatment (medication-related osteonecrosis of the jaw [MRONJ]) have been increasing. Although many risk factors for MRONJ have been elucidated, its precise etiology and methods of prevention remain unknown. In this study, we have applied various elemental analysis methods for MRONJ specimens (e.g., X-ray fluorescence with synchrotron radiation [SR-XRF], particle-induced X-ray emission [PIXE], X-ray absorption fine structure [XAFS]) in order to reveal the accumulation and chemical state of trace bone minerals. In four MRONJ sequestra, the characteristic localization of copper (Cu) was observed by SR-XRF. Using micro-PIXE analysis, Cu looked to be localized near the edge of the trabecular bone. The chemical state of the accumulated Cu was estimated using XAFS and the possibility of a Cu–BP complex formation was assumed. Thus, in this study we argue for the feasibility of the trace element analysis to evaluate the potential pathophysiological mechanism of MRONJ.

X-ray absorption near edge structure (XANES) analysis is an element-specific method for proving electronic state mostly in the field of applied physics, such as battery and catalysis reactions, where the valence change plays an important role. In particular, many results have been reported for the analysis of positive electrode materials of Li-ion batteries, where multiple transition materials contribute to the reactions. However, XANES analysis has been limited to identifying the valence state simply in comparison with reference materials. When the shape of XANES spectra shows complicated changes, we were not able to identify the valence states or estimate the valence quantitatively, resulting in insufficient reaction analysis. To overcome such issues, we propose a valence state evaluation method using K- and L-edge XANES analysis with first-principles simulations. By using this method, we demonstrated that the complicated reaction mechanism of Li(Ni1/3Co1/3Mn1/3)O2 can be successfully analyzed for distinguishing each contribution of Ni, Co, Mn, and O to the redox reactions during charge operation. In addition to the XANES analysis, we applied resonant photoelectron spectroscopy (RPES) and diffraction anomalous fine structure spectroscopy (DAFS) with first-principles calculations to the reaction analysis of Co and Mn, which shows no or very little contribution to the redox. The combination of RPES and first-principles calculations successfully enables us to confirm the contribution of Co at high potential regions by electively observing Co 3d orbitals. Through the DAFS analysis, we deeply analyzed the spectral features of Mn K-edges and concluded that the observed spectral shape change for Mn does not originate from the valence change but from the change in distribution of wave functions around Mn upon Li extraction. [ABSTRACT FROM AUTHOR]

Density functional theory calculations with a correction of the long-range dispersion force, namely, the van der Waals (vdW) force, are performed for SiC polytypes. The lattice parameters are in good agreement with those obtained from the experiments. Furthermore, the stability of the polytypes in the experiments, which show 3C-SiC as the most stable, is reproduced by the present calculations. The effects of the vdW force on the electronic structure and the stability of polytypes are discussed. We observe that the vdW interaction is more sensitive to the cubic site than the hexagonal site. Thus, the influence of the vdW force increases with decreasing the hexagonality of the polytype, which results in the confirmation that the most stable polytype is 3C-SiC. [ABSTRACT FROM AUTHOR]

A new lithium-niobate (LiNbO3)-type polar compound, namely, ZnPbO3 (a-5.41605(7) Å and c=14.33151(3) Å ), with closed-shell ions only was synthesized under high pressure and high temperature (8 GPa and 1273 K). A point-charge-model calculation based on atomic positions refined by Rietveld analysis of synchrotron X-ray diffraction data gave an electrical ionic polarization of 77 lC/cm2 along the hexagonal c-axis. Detailed structural analysis indicated that the contribution of Pb4+ in ZnPbO3 to the polarization was almost twice as large as that of Sn4+ in ZnSnO3. Transport measurement showed metallic behavior of ZnPbO3 from room temperature to low temperature despite the fact that both cations are closed-shell ions. [ABSTRACT FROM AUTHOR]

Understanding structures and spatial distributions of molecules in liquid phases is crucial for the control of liquid properties and to develop efficient liquid-phase processes. Here, real-space mapping of molecular distributions in a liquid was performed. Specifically, the ionic liquid 1-Ethyl-3-methylimidazolium bis(trifluoromethanesulfonyl) imide (C2mimTFSI) was imaged using atomic-resolution scanning transmission electron microscopy. Simulations revealed network-like bright regions in the images that were attributed to the TFSI- anion, with minimal contributions from the C2mim+ cation. Simple visualization of the TFSI- distribution in the liquid sample was achieved by binarizing the experimental image. [ABSTRACT FROM AUTHOR]

The electron energy loss near edge structures (ELNES) appearing in an electron energy loss spectrum obtained through transmission electron microscopy (TEM) have the potential to unravel atomic and electronic structures with sub-nano meter resolution. For this reason, TEM-ELNES has become one of the most powerful analytical methods in materials research. On the other hand, theoretical calculations are indispensable in interpreting the ELNES spectrum. Here, the basics and applications of one-particle, two-particle and multi-particle ELNES calculations are reviewed. A key point for the ELNES calculation is the proper introduction of the core-hole effect. Some applications of one-particle ELNES calculations to huge systems of more than 1000 atoms, and complex systems, such as liquids, are reported. In the two-particle calculations, the importance of the correct treatment of the excitonic interaction is demonstrated in calculating the low-energy ELNES, for example at the Li-K edge. In addition, an unusually strong excitonic interactions in the O-K edge of perovskite oxides is identified. The multi-particle calculations are necessary to reproduce the multiplet structures appearing at the transition metal L2,3-edges and rare-earth M4,5-edges. Applications to dilute magnetic semiconductors and Li-ion battery materials are presented. Furthermore, beyond the 'conventional' ELNES calculations, theoretical calculations of electron/X-ray magnetic circular dichroism (MCD) and the vibrational information in ELNES, are reported. [ABSTRACT FROM AUTHOR]

We investigated the migration energy and vacancy formation energy of La and Sr ions at a LaAlO3/SrTiO3 heterointerface using first-principles calculations. Our study reveal that the migration energies at the p-type interface are lower than those at the n-type interface, and the formation energies of Sr and La vacancies are relatively high when we assume a reduction atmosphere and insulator conditions. To explain the experimental evidence that intermixing is preferentially taking place at the n-type interface, considering the Fermi energy is critical. We find that the presence of electron carriers plays an important role in the intermixing behaviors at the LaAlO3/SrTiO3 heterointerface. [ABSTRACT FROM AUTHOR]

We report an effective approach for estimating the dynamic behaviour of molecules in liquid from their core-loss spectra by combining molecular dynamics simulations and first-principles band-structure calculations. The carbon K-edge of the technologically important methanol was calculated, and the experimental spectra were well reproduced using the presented calculation method, which effectively included multiple-molecule interactions. Several peaks arose from the methanol molecules with different C-O bonding modes, and the splitting of those peaks was sensitively altered by the magnitude of the dynamic behaviour of molecules. These findings allow for estimation of the dynamic behaviour of molecules in liquids using core-loss spectroscopy, and the method offers the potential to identify the dynamic behaviour of the molecules in liquids with high spatial resolution, temporal resolution, and sensitivity. [ABSTRACT FROM AUTHOR]

The thermal stability and dielectric and structural properties of ferroelectric Ba1-xCaxTi2O5 (0⩽x ⩽ 0.30) prepared by crystallization from glass are investigated. The Ba1-xCaxTi2O5 compounds with x , 0.10 are thermally stable phases, while those with x ⩾ 0.10 are metastable phases. The ferroelectric transition temperature drastically decreases from 470 to 220°C with increasing x. Crystal structure analyses reveal that one of two possible Ba sites is occupied by Ca in the stable phase region, while Ca-site selectivity is broken in the metastable phase region. The Ca-site selectivity introduces local distortion and makes the crystal lattice unstable. However, the local distortion is suppressed by the occupancy of Ca into both Ba sites. Accordingly, the metastable ferroelectric phase can be obtained beyond the substitution limit of Ca by crystallization from the glassy state. The stabilization mechanism provides possible wide control of the functionality of materials by expanding the composition range. [ABSTRACT FROM AUTHOR]

Titania nanosheets are two-dimensional single crystallites of titanium oxide with a thickness of one titanium or two oxygen atoms, and they show attractive material properties, such as photocatalytic reactions. Since a titania (Ti0.87O2) nanosheet is synthesized by the delamination of a parent layered K0.8Ti1.73Li0.27O4 crystal using a soft chemical procedure, substantial Ti vacancies are expected to be included and affect the material properties. The atomic arrangement of a titania nanosheet with vacancies has not been revealed owing to the difficulties of direct observation. Here, we have directly visualized the atomic arrangement and Ti vacancies of a titania nanosheet using advanced lower-voltage transmission electron microscopy (TEM). Analyses of the results of first-principles calculations and TEM image simulations for various Ti vacancy structure models indicate that two particular oxygen atoms around each Ti vacancy are desorbed, suggesting the sites where atomic reduction first occurs [ABSTRACT FROM AUTHOR]

Determining both cation and oxygen sublattices of grain boundaries is essential to understand the properties of oxides. Here, with scanning transmission electron microscopy, electron energy-loss spectroscopy, and first-principles calculations, both the Ce and oxygen sublattices of a (210)Σ5 CeO2grain boundary were determined. Oxygen vacancies are shown to play a crucial role in the stable grain boundary structure. This finding paves the way for a comprehensive understanding of grain boundaries through the atomic scale determination of atom and defect locations. [ABSTRACT FROM AUTHOR]

Deep neural networks (DNNs) have been used to successfully predict molecular properties calculated based on the Kohn-Sham density functional theory (KS-DFT). Although this prediction is fast and accurate, we believe that a DNN model for KS-DFT must not only predict the properties but also provide the electron density of a molecule. This Letter presents the quantum deep field (QDF), which provides the electron density with an unsupervised but end-to-end physics-informed modeling by learning the atomization energy on a large-scale dataset. QDF performed well at atomization energy prediction, generated valid electron density, and demonstrated extrapolation. [ABSTRACT FROM AUTHOR]

A new lithium-niobate (LiNbO3)-type polar compound, namely, ZnPbO3 (a-5.41605(7) Å and c=14.33151(3) Å ), with closed-shell ions only was synthesized under high pressure and high temperature (8 GPa and 1273 K). A point-charge-model calculation based on atomic positions refined by Rietveld analysis of synchrotron X-ray diffraction data gave an electrical ionic polarization of 77 lC/cm2 along the hexagonal c-axis. Detailed structural analysis indicated that the contribution of Pb4+ in ZnPbO3 to the polarization was almost twice as large as that of Sn4+ in ZnSnO3. Transport measurement showed metallic behavior of ZnPbO3 from room temperature to low temperature despite the fact that both cations are closed-shell ions. [ABSTRACT FROM AUTHOR]

Crystalline interfaces have a tremendous impact on the properties of materials. Determination of the atomic structure of the interface is crucial for a comprehensive understanding of the interface properties. Despite this importance, extensive calculation is necessary to determine even one interface structure. In this study, we apply a technique called kriging, borrowed from geostatistics, to accelerate the determination of the interface structure. The atomic structure of simplified coincidence-site lattice interfaces were determined using the kriging approach. Our approach successfully determined the most stable interface structure with an efficiency almost 2 orders of magnitude better than the traditional “brute force” approach. [ABSTRACT FROM AUTHOR]