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909 records · Page 3

In-Situ Scanning Electron Microscope Experiments for Microscale Mechanical Testing and Validated Modeling of Fiber Reinforced Thermoplastics

A novel, in-situ, scanning electron microscope (SEM) mechanical testing capability for materials at the microscale which provides experimental validation to a machine learning (ML) toolset for full-field validation of physics-based micromechanics models is being developed by researchers at NASA Glenn Research Center. These are enabling technologies for the integration of multiscale digital twins for materials into system level models which will result in the improved performance, material discovery, reduced production cost and time, rapid characterization, and prognostic structural health monitoring (SHM) for materials and structures for extreme environments in support of NASA space exploration missions. In order to bridge the material structure-to-system gap for digital twins, physics-based models must be experimentally validated at multiple length scales. Seminal microscale experiments, conducted at the Air Force Research Laboratory (AFRL), were limited to transverse compression of single-layer, unidirectional thermoset polymer matrix composite (PMC) micropillar specimens [1]. The early phases of the current project followed those initial results and setup to reproduce the compression testing of PMC material on the custom-built piezoelectric actuated micromechanical testing rig built by MicroTesting Solutions LLC. In this work, samples of thermoplastic PMC material were first machined into 3 mm cubes, and then further machining and final milling was done using a Focused Ion Beam (FIB). The initial experiment was done on a pillar roughly 20 µm x 20 µm x 40 µm tall. Additional pillars were milled with final sizes ranging from 20 µm x 20 µm x 40 µm tall to 40 µm x 40 µm x 65 µm tall. A speckle pattern for in-situ full-field measurements using Digital Image Correlation (DIC) was applied with platinum, which was coated on the surface, and then the FIB was used to mill away some of the coating to produce an irregular pattern of Pt on the pillar surface. The samples were loaded into the custom testing rig and placed into the SEM and loaded under compression until failure. Images were collected in the SEM during testing. Post-processing of the images was conducted using DIC to obtain full-field displacement and strain measurements elucidating the role of the matrix as well as fiber-fiber interaction at the microscale within the composite subjected to compression loading well into the non-linear regime of the material. Moreover, the evolution of fiber-matrix debonding and matrix cracking is observed in-situ at the microscale. This data, along with images segmented with a newly developed ML toolset [2], was used to create and validate physics-based micromechanics models. An image of the failed micropillar is shown in Figure 1. The techniques developed in the initial compression experiment was tailored to the validation needs of the models and expanded to include different sized samples as well as possibly tension and fatigue.

Laura Wilson

Three-dimensional dispersion in the type-II Dirac semimetals PtTe 2 and PdTe 2 revealed through circular dichroism in angle-resolved photoemission spectroscopy

PtTe 2 and PdTe 2 are among the first transition metal dichalcogenides that were predicted to host type-II Dirac fermions, exotic particles prohibited in free space. These materials are layered and air stable, which makes them top candidates for technological applications that take advantage of their anisotropic magnetotransport properties. Here, in this work, we provide a detailed characterization of the electronic structure of PtTe 2 and PdTe 2 using angle-resolved photoemission spectroscopy (ARPES) and density functional theory calculations, offering an alternative interpretation for one of the Dirac-like dispersions in these materials. Through the use of circularly polarized light, we report a different behavior of such dispersion in PdTe 2 compared to PtTe 2 , that we relate to a symmetry analysis of the dipole matrix element. Such analysis reveals a link between the observed circular dichroism and the different momentum-dependent terms in the dispersion of these two compounds, despite their close similarity in crystal structure. Additionally, our data show a clear difference in the circular dichroic signal for the type-II Dirac cones characteristic of these materials, compared to their topologically protected surface states. Our paper provides a useful reference for the ARPES characterization of other transition metal dichalcogenides with topological properties and illustrates the use of circular dichroism as a guide to identify the topological character and attributes of two otherwise equivalent band dispersions.

angle-resolved photoemission spectroscopy

Dimensional Evolution Guides Property Control in the A n Cu 4– n TiS 4 Semiconductor Series

Through progressive reduction of the three-dimensional (3D) covalent network of Cu 4 TiS 4 , we isolate seven new members of the A n Cu 4–n TiS 4 family (A = alkali metal; n = 0–4), spanning 3D, 2D, 1D, and 0D structural fragments. The dimensional reduction is rational, as it preserves the edge-sharing connectivity between [CuS 4 ] 7– and [TiS 4 ] 4– tetrahedra across the series. This structural evolution is driven by the stepwise substitution of Cu with alkali metals, guiding the formation of fragments with reduced dimensionality. The effects of “n” and “A” on the crystal structures, stabilities, electronic structures, and optoelectronic properties are profound, demonstrating that the manipulation of alkali metal size and A n Cu 4–n TiS 4 stoichiometry enables predictable variations in structure and properties. For example, the n = 0 and n = 4 end members of the A n Cu 4–n TiS 4 family set the range of achievable band gaps with 2.00 eV for Cu 4 TiS 4 , 2.60 eV for Na 4 TiS 4 , and intermediate values for the n = 1–3 members. Notably, CsCu 3 TiS 4 exhibits exceptional air stability and congruent melting, with density functional theory (DFT) calculating moderate hole and electron effective masses in specific crystallographic directions (mh = 1.24m 0 , me = 0.87m 0 ). Additionally, A 3 CuTiS 4 (A = Na, K, Rb) displays direct band gap behavior and long photoluminescence lifetimes of 2.3–8.6 μs, and K 3 CuTiS 4 has a PLQY of 5.19%. These findings underscore the potential of the A n Cu 4–n TiS 4 family for applications in optoelectronics and demonstrate widely applicable design concepts that unveil rational stoichiometries within a given composition space to generate a series of crystal structures related through an evolving covalent dimensionality that corresponds to a predictable electronic structure and property progression.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Effect of the Nature of Both Cation and Anion Substitution on the Structural Symmetry of Li‐Rich 3 d ‐Metal Chalcogenide Electrodes

Abstract Li‐rich layered chalcogenides have recently led to better understanding of the anionic redox process and its associated high capacity while providing ways to overcome its practical limitations of voltage fade and irreversibility. This study reports on the feasibility of triggering anionic activity in Li 2 TiS 3 , through anionic substitution (Se for S) or cationic substitution (Fe for Ti). Herein, the chalcogenide chemical space is further explored to prepare mono‐substituted Li 1.7 Ti 0.85 Mn 0.45 Ch 3 (Ch = S/Se) and doubly substituted cationic and anionic phases (Li 1.7 Ti 0.85 Fe 0.45 S 3‐z Se z ) which crystallize either in the O3‐ or O1‐type structures depending upon substituents. All series show a bell‐shape capacity variation as function of the transition metal (TM) substitution degree with values up to 240 mAh g −1 . For specific compositions, a structural O3 to O1 phase transition is observed upon Li removal, which is not reversible upon Li re‐insertion due to kinetic limitations and negatively affects long‐term cycling performance. Density functional theory (DFT) calculations confirm the O3/O1 relative stability along the different series and point subtle electronic differences in the TM‐doping, rationalizing the structural and electrochemical behaviors of these phases upon cycling. These findings provide further insights into the link between structural and electronic stability, which is of key importance for designing chalcogenide‐based anionic redox compounds.

Chemistry

Quantifying the dislocation content of atomically resolved grain boundary line defects using the Nye tensor

The Nye tensor, which quantifies the density of Burgers vector for a given dislocation line direction, can be effectively used to characterize dislocation content in bulk crystals from atomic-resolution transmission electron microscopy images. The Nye tensor can be calculated from these images, in part because the reference state is simply defined by the lattice of the perfect crystal. The application of the Nye tensor to interfacial line defects, for which the natural reference state is the dichromatic pattern of the two grains in their reference orientation, poses additional challenges. In this work, we present a method that employs the Nye tensor to characterize the edge dislocation content of line defects at grain boundaries from atomic-resolution images. This approach enables us to rapidly characterize all edge dislocation content along a grain boundary. Additionally, the Nye tensor provides information about line defect core structure. Finally, we demonstrate this method on two exemplar defects: a twin boundary disconnection and a facet junction in face-centered cubic Au.

Crystallographic defects

NanoPSD: A software for automatic detection of Nano-Particle Shape Distribution in electron microscopy images

Accurate quantification of the size and morphology of nanoparticles from electron microscopy (EM) images is essential to understand growth mechanisms, surface reactivity, and functional behavior in nanoscale materials. Manual analysis remains slow, subjective, and difficult to reproduce in large datasets. We introduce NanoPSD (Nano-Particle Shape Distribution), an open-source and fully automated framework for quantitative particle detection and morphology analysis from EM images. NanoPSD integrates adaptive contrast enhancement, polarity-agnostic scale-bar detection, Optical Character Recognition (OCR)-based calibration, and classical segmentation via Otsu thresholding with morphological refinement. Particle contours are used to extract geometric descriptors, including equivalent circular diameter, aspect ratio, circularity, and solidity, enabling automated classification into spherical, rod-like, and aggregate morphologies. The framework supports both single-image and batch processing, generating publication-quality visualizations, LaTeX-ready tables, and structured comma-separated values (CSV) datasets. As a demonstration, we applied NanoPSD to plasma-synthesized nanoparticle samples diagnosed via transmission electron microscopy (TEM). The code produced statistically robust size and morphology distributions spanning a few to tens of nanometers with minimal user supervision. The pipeline demonstrates high reproducibility and scalability, processing large image collections with consistent calibration and output formatting. Its modular design enables seamless integration of future deep-learning-based segmentation models, providing a pathway toward intelligent, data-driven electron microscopy analysis.

36 MATERIALS SCIENCE

Eutelsat 2: SAR-10009 nickel-hydrogen battery

The topics are presented in viewgraph form and include SAR-10009 design features, specific energy, analyses and testing, redundant structural insulation, electronics, corrosion protection, battery cell life cycle tests, and spacecraft launches.

Miller, Lee

Equation of state for Hf, Ta, W, Re, Os, Ir, Pt, and Au to multi-terapascal pressures from density-functional theory

We present the zero-temperature equation of state (pressure dependence of compression) and phase stability predictions for the 5d-transition metals obtained from all-electron density-functional theory (DFT) calculations. The results compare favorably with experiments but extend beyond current experimental capabilities to 10 TPa. Our study reveals phase changes that are explained from the calculated electronic structure. The cubic face-centered and body-centered structures (fcc and bcc), together with two-, three-, and four-layered hexagonal structures, play major roles under compression. The results’ dependence on the electron exchange and correlation in the DFT approach is investigated, and it is shown that the impact of the choice, while significant at lower pressures, diminishes in the terapascal regime. We further illustrate that the normal parabolic trends in atomic volume and bulk modulus with atomic number, due to the occupation of bonding and anti-bonding 5d states, break down at TPa pressures, suggesting drastically different chemical bonding at these extreme conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

The ABCs of phase retrieval: Connecting the acronyms of scanning transmission electron microscopy

High-resolution scanning transmission electron microscopy (S/TEM) is an indispensable tool for characterizing the structure and properties of materials down to the atomic scale. Conventional S/TEM imaging, however, is limited by the phase problem, whereby the phase of the electron exit wave is lost upon detection. Recent advances in diffractive imaging and 4D-STEM have enabled a range of phase-retrieval techniques that computationally reconstruct the missing information encoded in the phase of the transmission function. These approaches offer improved dose efficiency and enhanced sensitivity to weakly scattering signals, extending quantitative imaging to beam-sensitive materials composed of light elements. In this work, we introduce the phase problem in electron microscopy and survey the diverse landscape of phase-retrieval techniques used in the field. Despite their many acronyms and algorithmic variations, these techniques share a common physical and mathematical foundation. We present a unified framework that connects these seemingly distinct methods, from parallax imaging and tilt-corrected bright-field (tcBF-STEM), to aberration-corrected bright-field (acBF-STEM), optimum bright-field (OBF-STEM) and single-sideband (SSB) ptychography, as well as first-moment integrated center of mass techniques (iCOM) and iterative ptychographic algorithms. Based on these insights, we discuss the opportunities and practical limitations of applying these methods across different materials systems, detector designs, and microscope configurations.Graphical abstractRepresentative electron microscopy configurations used for phase retrieval and diffractive imaging in S/TEM: (a) Zernike phase-contrast transmission electron microscopy (TEM), (b) small-convergence-angle four-dimensional scanning transmission electron microscopy (4D-STEM) for nanobeam-based phase reconstruction methods, and (c) large-convergence-angle 4D-STEM for ptychographic and related diffractive imaging techniques reviewed in this work.

36 MATERIALS SCIENCE

Realignment and suppression of charge density waves in the rare-earth tritellurides 𝑅⁢Te 3 (𝑅 = La, Gd, Er)

The rare-earth tritellurides have a rich phase diagram that includes charge density waves (CDWs), superconductivity, and magnetic order, offering a platform to study the interplay between these phases on a square-net system. Prior studies have shown that defects can affect the CDW characteristics in these materials, yet coupling between the CDW order and the underlying microstructure has not been studied at the nanoscale. Here we use scanning transmission electron microscopy at cryogenic temperatures to directly visualize the effects of defects on the CDW order and provide a spatially resolved microscopic correlation between the CDW transition and structural defects. Here, we show that in the presence of extended defects, such as dislocations and stacking faults, the weak orthorhombicity of the rare-earth tritellurides is lost and the material becomes pseudotetragonal. Since the orthorhombicity acts as a symmetry breaking field for the CDW transitions in rare-earth tritellurides, the presence of these extended defects modulates the energetics of the CDWs and suppresses the ground-state CDW phase at low temperature.

Charge density waves

Nuclear–Electronic Orbital General Rate Theory: Predicting Hydrogen Kinetic Isotope Effects in the Deep Tunneling Regime

Hydrogen transfer is a critical component of many chemical and biological processes. The ratio of rate constants for hydrogen and deuterium transfer defines the H/D kinetic isotope effect (KIE), which is a powerful tool for elucidating hydrogen transfer mechanisms. Interpretation of experimental H/D KIEs relies on accurate and affordable computational methods. However, due to their light mass, hydrogen and deuterium can undergo tunneling, which is challenging to describe in multidimensional molecular systems. Herein, we introduce the nuclear–electronic orbital general rate theory (NEO-GRT), which enables the efficient prediction of H/D KIEs based on full-dimensional molecular quantum chemistry calculations. The NEO-GRT approach describes the hydrogen transfer rate constant with a general expression that spans the vibrationally adiabatic and nonadiabatic hydrogen tunneling regimes. The input quantities are computed using NEO density functional theory, which treats the transferring hydrogen or deuterium nucleus quantum mechanically on the same level as the electrons. We investigate two intramolecular proton transfer reactions in organic molecules at temperatures down to 50 K to evaluate the performance of NEO-GRT by comparison to transition state theory and ring-polymer instanton theory. The KIEs computed with NEO-GRT agree with those calculated using ring-polymer instanton theory for the full-dimensional molecular systems at the same level of electronic structure theory. This agreement indicates that NEO-GRT captures the deep hydrogen tunneling effects, in contrast to transition state theory, which neglects such effects. Given its relatively low computational cost, NEO-GRT is a promising approach for predicting H/D KIEs in large organic and organometallic systems.

Hydrogen

Machine Learning for Multipactor Susceptibility Prediction in Planar RF Gaps

Multipactor discharge is a nonlinear electron avalanche that limits the performance of high-power radio-frequency (RF) and vacuum electronic devices. Predicting multipactor susceptibility traditionally relies on Monte Carlo or particle-in-cell (PIC) simulations, which become computationally expensive for large parametric studies. In this work, we present a supervised machine-learning (ML) framework for prediction of multipactor susceptibility in a two-surface planar geometry. The models are trained using high-fidelity PIC simulation generated susceptibility data and learn the relationship between operational parameters, geometry, and material-dependent secondary electron emission properties. The proposed approach enables rapid reconstruction of susceptibility charts while preserving the physical structure of multipactor growth regions.

43 PARTICLE ACCELERATORS

Machine learning pipeline for denoising low signal-to-noise ratio and out-of-distribution transmission electron microscopy datasets

High-resolution transmission electron microscopy (HRTEM) is crucial for observing material’s structural and morphological evolution at Angstrom scales, but the electron beam can alter these processes. Devices such as CMOS-based direct-electron detectors operating in electron-counting mode can be utilized to substantially reduce the electron dosage. However, the resulting images often lead to a low signal-to-noise ratio, which requires frame integration that sacrifices temporal resolution. Several machine learning (ML) models have been recently developed to successfully denoise HRTEM images. Yet, these models are often computationally expensive, and their inference speeds on GPUs are outpaced by the imaging speed of advanced detectors, precluding in situ analysis. Furthermore, the performance of these denoising models on datasets with imaging conditions that deviate from the training datasets has not been evaluated. To mitigate these gaps, we propose a new self-supervised ML denoising pipeline specifically designed for time-series HRTEM images. This pipeline integrates a blind-spot convolution neural network with pre-processing and post-processing steps, including drift correction and low-pass filtering. Results demonstrate that our model outperforms various other ML and non-ML denoising methods in noise reduction and contrast enhancement, leading to improved visual clarity of atomic features. Additionally, the model is drastically faster than U-Net-based ML models and demonstrates excellent out-of-distribution generalization. The model’s computational inference speed is in the order of milliseconds per image, rendering it suitable for application in in-situ HRTEM experiments.

36 MATERIALS SCIENCE

Analytical Model for Atomic Relaxation in Twisted Moiré Materials

By virtue of being atomically thin, the electronic properties of heterostructures built from two-dimensional materials are strongly influenced by atomic relaxation. The atomic layers behave as flexible membranes rather than rigid crystals. Here we develop an analytical theory of lattice relaxation in twisted moiré materials. We obtain analytical results for the lattice displacements and corresponding pseudo gauge fields, as a function of twist angle. We benchmark our results for twisted bilayer graphene and twisted WSe 2 bilayers using large-scale molecular dynamics simulations. Our single-parameter theory is valid in graphene bilayers for twist angles 𝜃 ≳ 0.7°, and in twisted WSe 2 for 𝜃 ≳ 1.6°. Furthermore, we also investigate how relaxation alters the electronic structure in twisted bilayer graphene, providing a simple extension to the continuum model to account for lattice relaxation.

36 MATERIALS SCIENCE

Statistical Study of Energy Dissipation in Magnetic Structures During Turbulent Reconnection in the Earth's Magnetotail

Magnetic reconnection is a ubiquitous plasma phenomenon that plays a critical role in particle heating and energization. During reconnection, the topology of magnetic field rearranges, depositing energy into the surrounding plasma through bulk flow, thermal heating, or non-thermal particle acceleration. While the pathways of this transformation from magnetic energy into kinetic have been studied extensively in recent years through theoretical or case-by-case observations, comprehensive statistical studies remain limited. In this paper, we present a statistical investigation using data from the Magnetospheric Multiscale (MMS) mission, and detail the particle energization mechanisms in magnetic structures found near reconnecting regions in turbulent Earth's magnetotail. We find that electrons with motion perpendicular to the magnetic field dominate $\vec{j}$ ⋅ $\vec{E}$ dissipation. In contrast to the conventional picture of unidirectional energy transfer to particles by laminar two-dimensional (2D) reconnection, we find that energy exchange within magnetic structures during turbulent reconnection tends to be bidirectional with only a small positive bias from electromagnetic fields to particles. Specific electron energization mechanisms are quantified, including those due to parallel electric field, Fermi energization from curvature drift, betatron heating from magnetic field inhomogeneity, and polarization drift.

Wang, Rachel [Princeton University, NJ (United Sta

Mesoscale Magnetostructural Phase Separation in Fe‐deficient Fe 5 GeTe 2

Two-dimensional van der Waals ferromagnet Fe 5-x GeTe 2 (F5GT) is promising for spintronic applications due to its high Curie temperature, layered structure, and ability to host complex magnetic textures. However, the origin of its sample-dependent magnetic anisotropy remains unclear, hindering control of its magnetic behavior. Here, we use spatially resolved cryogenic scanning transmission electron microscopy (STEM) to correlatively map magnetism, lattice structure, and chemistry across atomic-to-micron scales. We reveal that only mesoscale, not nanoscale, inclusions of a Fe-deficient secondary phase significantly modify magnetic behavior, establishing a previously unrecognized critical length scale. This phase separation, induced by quenching, leads to in-plane magnetic anisotropy, while slow cooling confines separation to a few nanometers and preserves out-of-plane anisotropy. These findings reconcile prior inconsistencies and establish a predictive framework for tuning magnetism in F5GT through thermal processing, with broader implications for controlling anisotropy in other two-dimensional magnetic materials.

2D ferromagnets

The Trajectory of Recent Solid State Fusion Results

Both NASA and Google have explored and funded Low Energy Nuclear Reaction (LENR) aka Solid-State Fusion or Lattice Confinement Fusion (LCF) research. NASA has funded efforts since 1989, and Google Research began in 2014. Google, and researchers initially-funded by Google, published significant scientific papers in Nature, Nature Communications and the Journal of Applied Physics. NASA began a significant set of LENR-triggering programs in 2012 resulting in papers in Physical Review C, the Journal of Electroanalytical Chemistry and the Journal of Condensed Matter Nuclear Science. Both NASA and Google engaged researchers across fields of nuclear physics, chemistry, electrochemistry, material science and more. NASA built upon early novel gas pumping experiments then followed the patented work of the US Navy SPAWAR (US8,419,919, “System and Method to Generate Particles”) and experiments with the Naval Surface Warfare Centers. Google supported researchers at Lawrence Berkeley National Laboratory (LBNL), the University of British Columbia (UBC), MIT and others. This resulted in patent applications and two granted patents (US10264661B2, “Target structure for enhanced electron screening” and US10566094B2 “Enhanced electron screening through plasmon oscillations”). These separate efforts, unknown to the researchers at the time, provided the impetus for the DoE ARPA-E LENR program followed by the DARPA DSO “Mechanisms for Amplification of Fusion Reaction Rates in Solids” (MARRS) program. This document briefly describes the overlapping NASA and Google Research efforts in plasma loading and electron screening emphasizing the results of the latest paper in Nature Communications. The papers and patents cited are listed.

electron screening

Unconventional solitonic high-temperature superfluorescence from perovskites

Fast thermal dephasing limits macroscopic quantum phenomena to cryogenic conditions and hinders their use at ambient temperatures. For electronic excitations in condensed media, dephasing is mediated by thermal lattice motion. Therefore, taming the lattice influence is essential for creating collective electronic quantum states at high temperatures. Although there are occasional reports of high-T c quantum effects across different platforms, it is unclear which lattice characteristics and electron–lattice interactions lead to macroscopically coherent electronic states in solids. Here we studied intensity fluctuations in the macroscopic polarization during the emergence of superfluorescence in a lead halide perovskite and showed that spontaneously synchronized polaronic lattice oscillations accompany collective electronic dipole emission. We further developed an effective field model and theoretically confirmed that exciton–lattice interactions lead to a new electronically and structurally entangled coherent extended solitonic state beyond a critical polaron density. The analysis shows a phase transition with two processes happening in tandem: incoherent disordered polaronic lattice deformations establish an order, while macroscopic quantum coherence among excitons simultaneously emerges. Recombination of excitons in this state culminates in superfluorescence at high temperatures. Our study establishes fundamental connections between the transient superfluorescence process observed after the impulsive excitation of perovskites and general equilibrium phase transitions achieved by thermal cooling. By identifying various electron–lattice interactions in the perovskite structure and their respective role in creating collectively coherent electronic effects in solids, our work provides unprecedented insight into the design and development of new materials that exhibit high-temperature macroscopic quantum phenomena.

36 MATERIALS SCIENCE