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At least 55 records · Page 3

Electron-impact excitation data for W 2+ in support of tungsten spectroscopy and re-deposition measurements for magnetically-confined plasmas

Abstract To better understand plasma wall interactions involving tungsten, accurate atomic structure and electron-impact driven collisional processes for near-neutral ion stages of tungsten are required. Complementing existing work on neutral and singly ionised tungsten, atomic structure and collisional calculations for W 2+ electron-impact excitation have been completed. These excitation calculations are an important component of S/XB coefficients for near-neutral charge states, which may be used to spectroscopically infer re-deposition of tungsten at the plasma-solid boundary of fusion relevant devices. With W 2+ in particular having emission lines that can be observed at ultraviolet (UV) wavelengths, while higher charge states of tungsten are unlikely to have lines possible to observe outside of the vacuum UV range. The atomic structure was generated using the General-purpose Relativistic Atomic Structure Package (GRASP 0 ), implementing the Multi-configuration Dirac Fock approach. This structure was the basis for a subsequent Dirac R -matrix electron-impact excitation calculation to provide Maxwellian averaged rate coefficients. A synthetic spectrum was generated from this data using a collisional-radiative model to predict the strongest W III spectral lines and these lines were compared to emission from the Compact Toroidal Hybrid (CTH) plasma device. Several of the strongest W III lines are observed in CTH and agree well with the modelled line wavelengths and intensities, a table of these lines is provided that could be observed in other devices.

McCann, M. (ORCID:0000000215321240)

Elucidation of a Metastable p(2 × 1) O Atom Adlayer Structure on Cu(111)

Cu-based catalysts are ubiquitous in many industrial reactions, including methanol synthesis. Under partially oxidizing conditions, Cu catalysts can have dynamic surface structures that greatly influence their reactivities. Therefore, elucidating the surface structures that are present on Cu, and looking for metastable structures, aids in the long term goal of understanding and controlling their catalytic behavior. Thin-film copper oxides such as the “29” and “44” structures have been described at length in the literature, but precursors to these thin-film oxides can be challenging to study because they exist only under certain conditions. Using a combination of experimental and computational surface science techniques, we discovered, modeled, and quantified a previously unreported O atom adlayer structure on Cu(111) with a p(2 × 1) unit cell. Here, we used scanning tunneling microscopy to visualize the striped 2 × 1 structure and density functional theory (DFT) structure optimizations to identify the thermodynamically most favorable positions of Cu and O atoms in a p(2 × 1) unit cell. Using X-ray photoelectron spectroscopy and temperature-programmed desorption, we determined the stoichiometry of the structure to be 2:1 for surface Cu atoms to O adatoms, the same stoichiometry as that modeled by DFT. This work reports a new metastable structure formed on Cu(111) at the very initial stages of oxidation and is therefore worth considering in models of catalytically relevant redox processes at Cu surfaces.

36 MATERIALS SCIENCE

Insights into Native Single-Atom Electrocatalyst Site Structures

Single-atom electrocatalysts consisting of metal atoms embedded in a carbon matrix are promising next-generation catalysts for green hydrogen production and utilization, CO2 reduction, low-temperature CO oxidation, ammonia production, plastic decomposition, and electrochemical energy storage. The origins of activity and stability for the single-atom sites are still debatable, however, because of constrained insights into their local structure resulting from idealized models and experiments derived from a large number of individual sites. Insights into structural variations around single atomic sites are therefore critical for the continued development of these next-generation catalysts. While electron microscopy commonly provides atomic-scale information about these materials, the beam sensitivity of individual sites makes structural determination by conventional low-voltage (60 keV) techniques challenging. Here, we introduce ultralow-voltage electron ptychography, performed at 30 keV, that enables determination of the lattice structure around individual metal sites in a well-defined single-atom electrocatalyst system while essentially eliminating knock-on structural modifications. Pairing these atomic-scale, site-specific measurements with computational methods will broaden our understanding of the activity and stability of these materials, which will accelerate the development of the next generation of catalysts.

Zachman, Michael [ORNL] (ORCID:0000000319101357)

Time-resolved Brownian tomography of single nanocrystals in liquid during oxidative etching

Colloidal nanocrystals inherently undergo structural changes during chemical reactions. The robust structure-property relationships, originating from their nanoscale dimensions, underscore the significance of comprehending the dynamic structural behavior of nanocrystals in reactive chemical media. Moreover, the complexity and heterogeneity inherent in their atomic structures require tracking of structural transitions in individual nanocrystals at three-dimensional (3D) atomic resolution. In this study, we introduce the method of time-resolved Brownian tomography to investigate the temporal evolution of the 3D atomic structures of individual nanocrystals in solution. The methodology is applied to examine the atomic-level structural transformations of Pt nanocrystals during oxidative etching. The time-resolved 3D atomic maps reveal the structural evolution of dissolving Pt nanocrystals, transitioning from a crystalline to a disordered structure. Our study demonstrates the emergence of a phase at the nanometer length scale that has received less attention in bulk thermodynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Atomic-scale identification of active sites of oxygen reduction nanocatalysts

Heterogeneous nanocatalysts play a crucial role in both the chemical and energy industries. Despite substantial advancements in theoretical, computational and experimental studies, identifying their active sites remains a major challenge. Here we utilize atomic electron tomography to determine the three-dimensional atomic structure of PtNi and Mo-doped PtNi nanocatalysts for the electrochemical oxygen reduction reaction. We then employ the experimental atomic structures as input to first-principles-trained machine learning to identify the active sites of the nanocatalysts. Through the analysis of the structure–activity relationships, we formulate an equation termed the local environment descriptor, which balances the strain and ligand effects to provide physical and chemical insights into active sites in the oxygen reduction reaction. The ability to determine the three-dimensional atomic structure and chemical composition of realistic nanoparticles, combined with machine learning, could transform our fundamental understanding of the active sites of catalysts and guide the rational design of optimal nanocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Atomic-Scale Structure and Non-Stoichiometry of Meteoritic Hibonite: A Transmission Electron Microscope Study

Hibonite (CaAl_12O_19) is a common refractory mineral in Ca-Al-rich inclusions (CAIs) in primitive meteorites. Transmission electron microscope (TEM) studies have identified enigmatic planar defects in different occurrences of hibonite in the Allende meteorite that give rise to strong streaking along c* in electron diffraction patterns. Atomic resolution high-angle annular dark-field (HAADF) imaging and energy-dispersive X-ray (EDX) analyses were used to determine the nature and origin of these planar features. HAADF images of hibonite grains reveal lamellar intergrowths of common 1.6 nm spacing, and less commonly 2.0 and 2.5 nm spacings, interspersed in stoichiometric hibonite showing 1.1 nm (002) spacing. Stoichiometric hibonite consists of alternating Ca-containing (“R”) and spinel-structured (“S”) blocks stacked in a sequence RS. In contrast, the 1.6 nm layers result from a doubled S block such that the stacking sequence is RSS, while in the widest defect observed, the stacking sequence is RSSSS. These intergrowths are epitaxial and have coherent, low-strain boundaries with the host hibonite Meteoritic hibonite shows common Ti and Mg substitution for Al in its structure. Atomic-resolution EDX maps of hibonite grains in the Allende CAI confirm the preferred site occupancy of Mg on tetragonal M3 sites in S blocks and of Ti on trigonal bipyramidal M2 and octahedral M4 sites in R blocks. Mg is highly concentrated, but Ti is absent in the planar defects where wider S blocks show Al-rich compositions compared to stoichiometric MgAl_2O_4 spinel. Therefore, Mg likely played the major role in the formation and metastability of planar defects in hibonite. Electron energy loss spectroscopy data from the Ti L_2,3 edge show the presence of mixed Ti oxidation states with ~ 15–20% of Ti as Ti^(3+) in hibonite, suggesting a direct substitution of Ti^(3+) ↔ Al^(3+) in hibonite. The remaining ~ 80–85% of Ti is present as Ti^(4+) and corresponding EDX analyses are consistent with the well-known coupled substitution 2Al^(3+) ↔ Ti^(4+) + Mg^(2+) being the major mechanism for Ti and Mg substitution in hibonite. The formation of planar defects in hibonite occurred during high-temperature nebular condensation or melting/crystallization processes. The occurrence of non-stoichiometric hibonite in the Allende CAI deviates from the mineral formation sequence predicted from equilibrium condensation models. Overall, our atomic resolution TEM observations signify non-equilibrium, kinetic-controlled crystal growth during the high-temperature formation of refractory solids in the early solar nebula.

hibonite

Electron Microscopy Approaches to Unraveling the Structure of Amorphous Materials

Determining atomic structures in crystalline materials—where atoms are arranged in rigid, periodic lattices—has been highly successful using probes such as electrons, X-rays, and neutrons. In contrast, amorphous materials, despite their ubiquity and technological importance, remain far more challenging to characterize with comparable accuracy and precision. This review highlights existing, emerging, and potential (scanning) transmission electron microscopy ((S)TEM) techniques for probing short- and medium-range order in amorphous materials. Approaches ranging from high-resolution (S)TEM imaging and selected electron diffraction pattern to four-dimensional STEM (4D-STEM) based pair distribution function, fluctuation electron microscopy, tomography, ptychography, and spectroscopic methods are discussed, emphasizing their ability to provide complementary insights across multiple length scales—from sub-angstrom local environments to nanometer-scale correlations. Here, we further explore the promise of multimodal and correlative strategies, as well as the growing role of machine learning and physics-informed AI in enabling real-time, quantitative interpretation of complex structural signatures. Together, these advances point toward a future where electron microscopy not only reveals the hidden order in amorphous systems but also establishes robust structure–property relationships, paving the way for materials innovation in disordered matter.

77 NANOSCIENCE AND NANOTECHNOLOGY

Atomic-scale structure of ZrO 2 : Formation of metastable polymorphs

Metastable phases can exist within local minima in the potential energy landscape when they are kinetically “trapped” by various processing routes, such as thermal treatment, grain size reduction, chemical doping, interfacial stress, or irradiation. Despite the importance of metastable materials for many technological applications, little is known about the underlying structural mechanisms of the stabilization process and atomic-scale nature of the resulting defective metastable phase. Investigating ion-irradiated and nanocrystalline zirconia with neutron total scattering experiments, we show that metastable tetragonal ZrO 2 consists of an underlying structure of ferroelastic, orthorhombic nanoscale domains stabilized by a network of domain walls. The apparent long-range tetragonal structure that can be recovered to ambient conditions is only the configurational ensemble average of the underlying orthorhombic domains. This structural heterogeneity with a distinct short-range order is more broadly applicable to other nonequilibrium materials and provides insight into the synthesis and recovery of functional metastable phases with unique physical and chemical properties.

74 ATOMIC AND MOLECULAR PHYSICS

Atomic-resolution structural and spectroscopic evidence for the synthetic realization of two-dimensional copper boride

Since the first realization of borophene on Ag(111), two-dimensional (2D) boron nanomaterials have attracted substantial interest because of their polymorphic diversity and potential for hosting solid-state quantum phenomena. Here, we use atomic-resolution scanning tunneling microscopy (STM) and field-emission resonance (FER) spectroscopy to elucidate the structure and properties of atomically thin boron phases grown on Cu(111). Specifically, FER spectroscopy reveals charge transfer and electronic states that strongly differ from the decoupled borophene phases observed on silver, suggesting that the deposition of boron on copper results in strong covalent bonding characteristic of a 2D copper boride. This conclusion is reinforced by detailed STM characterization of line defects that are consistent with density functional theory calculations for atomically thin Cu8B14. This evidence for 2D copper boride is likely to motivate future synthetic efforts aimed at expanding the relatively unexplored family of atomically thin metal boride materials.

Science & Technology - Other Topics

Atomic-Scale Behavior of Radiation-Resistant ZnO under High-Energy Electron Bombardment

Understanding the atomic structure and defect characteristics of ZnO thin films is crucial for optimizing their electronic properties and performance in advanced applications. Here, we investigate the atomic structure and defect characteristics of atomic layer deposition (ALD)-grown ZnO thin films by using aberration-corrected scanning transmission electron microscopy (STEM). Atomic-resolution imaging identifies prevalent stacking faults, dipole disorder, and various grain boundary types, which are believed to influence the electronic properties of ZnO. Additionally, real-time electron beam exposure experiments demonstrate structural transformations, including crystal growth and surface rearrangements. These findings provide insights into the growth mechanisms of ALD ZnO under high-energy electron irradiation conditions, an important finding for the use of polycrystalline ZnO wide bandgap semiconductors in space-like conditions. In conclusion, our results underscore the capability of STEM in directly visualizing and quantifying atomic-scale defects and beam-induced transformations in radiation-resistant ZnO.

Defects

Combining Theory and Experiment to Map the Atomic-Level Structure–Energy Pathways of Adsorbate-Mediated Phase Changes in a Cooperatively Flexible Metal–Organic Framework

An important subclass of metal–organic frameworks (MOFs) exhibits cooperative flexibility, wherein individual crystallites undergo global structural phase changes in response to external stimuli. Where cooperative flexibility results in reversible changes between crystalline states of distinct accessible porosity, these frameworks can exhibit rare yet desirable behaviors that cannot be explained by local dynamics alone. Yet, the chemical and structural origins of cooperative flexibility and how frameworks undergo these reversible phase changes at the atomic level remain poorly understood. Deliberate design for specific applications is therefore exceedingly difficult, and there is great impetus to develop a fundamental understanding of this phenomenon. Here, an effective and widely accessible computational approach is developed, which is designed to provide microscopic resolution via direct comparison to experimental data along the desorption-guided pathway. The strategy is applied to explain the desorption-induced phase change in an experimentally well-characterized framework, CdIF-13 (sod-Cd(benzimidazolate)2), where experiment alone was unable to resolve the atomistically detailed phase change landscape. Our findings reveal that the cooperative phase change pathways are adsorbate dependent with thermodynamics of intermediate structural states dictated by a nuanced interplay of ligand orientation, skeletal symmetry, and modes of surface adsorption. The results reveal that this isotropically flexible framework is “chaperoned” through a complex energy landscape by specific adsorbates, revealed by the reported computational approach with atomic-level insight and validated by experimentally determined structures. Thus, this work facilitates both understanding and future design of flexible materials for applications in gas storage, transport, delivery, and separation technologies.

03 NATURAL GAS

Substrate Effects on Electronic Properties of Atomic Chains

When the device size is reduced down to 0.07 micrometers, the number of dopant atoms in the channel will no longer be macroscopic, typically less than a hundred. A spatial distribution of these dopant atoms will fluctuate statistically from device to device even in identically designed devices, and this places a serious limitation for integration. It is, however, impractical to control dopant positions within atomic dimension. One fundamental solution to this problem is to create electronics with atomically precise, but preferably simple structures. Atomic chains, precise structures of adatoms created on an atomically regulated surface, are candidates for constituent components in future electronics. All the adatoms will be placed at designated positions on the substrate, and all the device structures will be precise, free from any deviations. It was predicted using the tight-binding calculation with universal parameters that silicon chains were metallic and magnesium chains were semiconducting regardless of the lattice spacing, and a possible doping method was also proposed. In these treatments, the substrate was assumed to serve as a non-interacting template holding the adatoms without a formation of chemical bonding with substrate atoms. However, this scheme may not be easy to implement experimentally. Adatoms will have to be fixed with a van der Waals force on the substrate, but the force is generally weak and an extremely low temperature environment has to be prepared to suppress their unwanted thermal displacement. It may be logical to seek a scheme to allow the adatoms to form chemical bonding with the substrate atoms and secure their positions. The substrate effects are studied in detail.

Yamada, Toshishige

Deciphering the Solvation Structure of Aqueous ZnCl 2 Solutions from X-ray Absorption Spectra Using the Interpretable Graph Neural Network

Machine learning (ML) provides powerful pathways for predicting spectroscopic observables from atomic structures, but its broader impact depends on making model predictions interpretable in terms of physical and chemical principles. Here, we introduce a physics-guided graph neural network (GNN) model that predicts Zn K-edge X-ray spectroscopy (XAS) spectra of aqueous ZnCl 2 solutions. Training data are generated from ab initio XAS calculations on molecular dynamics snapshots obtained using a machine learning interatomic potential. The GNN reproduces experimental spectra across concentrations from dilute (<0.1 m) to highly concentrated (30 m, “water-in-salt”) regimes and scales efficiently to large, disordered liquid systems beyond the reach of conventional ab initio approaches. Gradient-based attribution analysis reveals that the model learns physically meaningful structure-spectrum relationships. Ligand-specific attributions reflect orbital hybridization patterns and the origin of the excitations derived from the density functional theory. Bond-length attributions recover spectral shifts consistent with multiple-scattering theory. Finally, this work bridges data-driven prediction with electronic-structure theory, establishing a general paradigm for interpretable ML that links atomic structure, electronic structure, and spectroscopic observables.

25 ENERGY STORAGE

Exploring Structural Anisotropy in Amorphous Tb-Co via Changes in Medium-Range Ordering

Amorphous thin films grown by magnetron co-sputtering exhibit changes in atomic structure with varying growth and annealing temperatures. Structural variations influence the bulk properties of the films. Scanning nanodiffraction performed in a transmission electron microscope (TEM) is applied to amorphous Tb 17 Co 83 (a-Tb-Co) films deposited over a range of temperatures to measure relative changes in medium-range ordering (MRO). These measurements reveal an increase in MRO with higher growth temperatures and a decrease in MRO with higher annealing temperatures. The trend in MRO indicates a relationship between the growth conditions and local atomic ordering. By tilting select films, the TEM measures variations in the local atomic structure as a function of orientation within the films. The findings support claims that preferential ordering along the growth direction results from temperature-mediated adatom configurations during deposition, and that oriented MRO correlates with increased structural anisotropy, explaining the strong growth-induced perpendicular magnetic anisotropy found in rare earth–transition metal films. Beyond magnetic films, we propose the tilted FEM workflow as a method of extracting anisotropic structural information in a variety of amorphous materials with directionally dependent bulk properties, such as films with inherent bonding asymmetry grown by physical vapor deposition.

36 MATERIALS SCIENCE

Elucidation of Local Ordering and Atomic-Scale Structure in Polymer-Derived SiOC

Silicon oxycarbide (SiOC) is a versatile ceramic material with tunable microstructure and compositions that can be modulated through precursor chemistry and processing conditions. Though there are several noteworthy uses of SiOC across a range of application spaces, the difficulties in elucidating the short- to medium-range order within these materials have limited the maturation of strategies to precisely control SiC x O 4–x compositions for user-tailored applications. In this contribution, we implement a range of synchrotron scattering and spectroscopy methods coupled with stochastic modeling techniques to elucidate changes in local chemistry and structure associated with the pyrolysis of a commercially available SiOC polymer precursor. Stochastic modeling approaches provide valuable insights into decoupling local Si–O and Si–C environments while confirming predominate heterogeneous phases in materials. Using pyrolysis temperatures between 250 to 800 °C results in a heterogeneous material predominately composed of SiOC and amorphous SiO 2 domains. At 1100 °C, redistribution of Si–C pairs in the SiOC network and Si–O from the SiO 2 domains create a more ordered SiOC phase with local cubic SiC-like ordering. In addition, residual carbon leads to a detectable carbon phases at 1100 °C that persist at higher temperatures. These efforts address the difficulties of obtaining atomic-scale insights into the local structure and nanoscale heterogeneities in SiOC, providing pathways toward establishing structure–property relationships for future materials development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Longitudinal structure in atomic oxygen concentrations observed with WINDII on UARS

WINDII, the Wind Imaging Interferometer on the Upper Atmosphere Research Satellite, began atmospheric observations on September 28, 1991 and since then has been collecting data on winds, temperatures and emissions rates from atomic, molecular and ionized oxygen species, as well as hydroxyl. The validation of winds and temperatures is not yet complete, and scientific interpretation has barely begun, but the dominant characteristic of these data so far is the remarkable structure in the emission rate from the excited species produced by the recombination of atomic oxygen. The latitudinal and temporal variability has been noted before by many others. In this preliminary report on WINDII results we draw attention to the dramatic longitudinal variations of planetary wave character in atomic oxygen concentration, as reflected in the OI 557.7 nm emission, and to similar variations seen in the Meine1 hydroxyl band emission.

Shepherd, G. G.

A robust synthetic data generation framework for machine learning in high-resolution transmission electron microscopy (HRTEM)

Machine learning techniques are attractive options for developing highly-accurate analysis tools for nanomaterials characterization, including high-resolution transmission electron microscopy (HRTEM). However, successfully implementing such machine learning tools can be difficult due to the challenges in procuring sufficiently large, high-quality training datasets from experiments. In this work, we introduce Construction Zone, a Python package for rapid generation of complex nanoscale atomic structures which enables fast, systematic sampling of realistic nanomaterial structures and can be used as a random structure generator for large, diverse synthetic datasets. Using Construction Zone, we develop an end-to-end machine learning workflow for training neural network models to analyze experimental atomic resolution HRTEM images on the task of nanoparticle image segmentation purely with simulated databases. Further, we study the data curation process to understand how various aspects of the curated simulated data—including simulation fidelity, the distribution of atomic structures, and the distribution of imaging conditions—affect model performance across three benchmark experimental HRTEM image datasets. Using our workflow, we are able to achieve state-of-the-art segmentation performance on these experimental benchmarks and, further, we discuss robust strategies for consistently achieving high performance with machine learning in experimental settings using purely synthetic data. Construction Zone and its documentation are available at https://github.com/lerandc/construction_zone.

36 MATERIALS SCIENCE