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1,444 records · Page 14

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

Development of a One-Domain Volume-Averaged Navier–Stokes Solver

The interaction between a high-enthalpy flow and a thermal protection material is inherently multiscale and multiphysics. In conventional aerothermal analyses, the external flow and material response are generally modeled using separate computational domains coupled through boundary conditions at the material surface. Although this approach has supported many practical applications, it requires assumptions about the location and behavior of the interface and may become difficult to apply when material decomposition, internal reactions, and surface recession substantially alter the porous structure. This report presents the development of a one-domain formulation in which the free-fluid and porous-material regions are represented within a single computational domain. The formulation is based on the volume-averaged Navier–Stokes (VANS) equations, derived from the governing equations for reacting, compressible flow and condensed material. Volume averaging transfers the influence of the unresolved material microstructure to the macroscale equations through effective transport properties, interfacial source terms, and dispersion fluxes. Particular attention is given to regions in which porosity and permeability vary rapidly, including the diffuse transition between a porous material and the surrounding fluid. The resulting equations are implemented in the Porous-material Analysis Toolbox based on OpenFOAM (PATO). The report describes the pressure–velocity coupling strategy used by the solver, examines spatial filtering techniques for deriving effective properties, and evaluates the influence of a smoothly varying interface permeability. Numerical demonstrations include canonical porous-flow configurations, a flow-tube configuration representative of FiberForm® permeability experiments, and the oxidation of a porous carbon material. The purpose of this work is to establish a mathematical and computational foundation for a unified treatment of flow and thermal protection material response. The present formulation is intended to support the progressive inclusion of additional physical processes, including multicomponent transport, finite-rate gas–surface chemistry, pyrolysis, internal oxidation, and material recession. It also provides a framework for connecting pore-scale simulations and microstructural characterization with macroscale aerothermal-response calculations. This report is intended for researchers and engineers working in computational fluid dynamics, porous-media transport, material response, and thermal protection system modeling. It documents both the theoretical development and the initial numerical assessment of the one-domain approach, while identifying the closure of effective and dispersion terms as an important subject for continued investigation.

Ablation

Explainable machine learning reveals that local structural motifs encode the thermodynamic state across the CuZr metallic glass-forming range

Metallic glasses derive their properties from the statistics of local atomic motifs rather than from long-range order, yet a quantitative, chemistry-specific link between motif populations and the underlying glassy state has remained elusive. In this work we combine large-scale molecular dynamics, Voronoi tessellation, deep neural networks, and SHapley Additive exPlanations (SHAP) to identify which local structural motifs define the glassy state of Cu—Zr metallic glasses. A dataset of 17,180 atomistic configurations spanning ten compositions (Cu 20 Zr 80 –Cu 80 Zr 20 ) and four quench rates (10 9 –10 12 K/s) is used to train a feed-forward neural network that regresses temperature across the 50–2000 K liquid–supercooled–glass range, achieving a mean absolute error of 19.89 K and R 2 = 0.9974, confirming that the local structural state is faithfully encoded in motif-level structure. SHAP analysis then reveals that a tightly coupled near-icosahedral family of motifs (coordination numbers (CN) 11–13, including the full icosahedron 001200 and its single-atom-perturbation sibling 10930) collectively encodes the thermodynamic state of the system across the full glass-forming range. The CN = 11–13 ordered members carry negative SHAP values at high populations, tracking the most deeply-quenched configurations, while 10930 shows the reversed signature consistent with its role as a soft-spot host whose population shrinks as the icosahedral network deepens. The analysis demonstrates that explainable machine learning can isolate the minimal motif vocabulary defining the glassy state and recovers the near-icosahedral building blocks previously identified by data-driven analyses of Cu—Zr. The approach provides a general, chemistry-specific route for characterizing the structural state of disordered materials.

36 MATERIALS SCIENCE

Adapting High-Resolution X-Ray Microcalorimeter Spectrometers to Transform MFE Plasma Diagnostics

The aim of this project was to begin the transformation of magnetic fusion energy (MFE) X-ray diagnostics by applying detector technology developed over the past several decades by the astrophysics community. We installed and operated an X-ray microcalorimeter detector system under fusion-relevant plasma conditions at the Madison Symmetric Torus (MST). X-ray microcalorimeter spectrometers combine the best characteristics of instrumentation currently available on fusion devices: the high spectral resolution of crystal spectrometers (2 eV) and broadband coverage provided by pulse-height analysis systems. These spectrometers have small port-access requirements, a key advantage for future MFE experiments. This new plasma diagnostic technique will satisfy the need for multispecies impurity ion data by providing absolute measurements of impurity core accumulation, and it will provide the core impurity ion temperature. This project was a joint effort between Lawrence Livermore National Laboratory (LLNL) and researchers at the Wisconsin Plasma Physics Laboratory (WiPPl) at the University of Wisconsin–Madison (UW–Madison). Megan E. Eckart is the principal investigator at LLNL, which is funded separately from UW–Madison. This final report fulfills the reporting obligation of the UW–Madison effort.

Den Hartog, Daniel J. [Department of Physics, Univ

Synthetic battery cycling techniques

Synthetic battery cycling makes use of the fast growing capability of computer graphics to illustrate some of the basic characteristics of operation of individual electrodes within an operating electrochemical cell. It can also simulate the operation of an entire string of cells that are used as the energy storage subsystem of a power system. The group of techniques that as a class have been referred to as Synthetic Battery Cycling is developed in part to try to bridge the gap of understanding that exists between single cell characteristics and battery system behavior.

Leibecki, H. F.

Visualization of the surface distribution of photocatalytic activity at the anatase/rutile TiO2 interface using X-ray photoelectron emission microscopy

We applied X-ray photoelectron emission microscopy (XPEEM) to visualize the surface distribution of photocatalytic activity at the anatase/rutile (A/R) interface of titanium dioxide. Acetic acid was adsorbed on the surface, and its decomposition and desorption reactions under ultraviolet light irradiation were monitored by observing C 1s spectra, enabling direct observation of the spatial distribution of photocatalytic activity. Complementary crystal structure information was obtained using spatially resolved low-energy electron diffraction, low-energy electron microscopy, X-ray absorption spectroscopy, and micro-focused Raman spectroscopy. Comparison with these structural data allowed for the evaluation of the photocatalytic activity as a function of the distance from the A/R interface. The activity is enhanced in the vicinity of the interface and gradually decreases toward both the anatase and rutile regions. These results demonstrate that XPEEM is an effective technique for spatially resolved mapping of photocatalytic activity, which has\\r\\npreviously been inaccessible using conventional characterization techniques.

25 ENERGY STORAGE

Imaging of a van der Waals spin-orbit torque system using spin ensembles in hBN

Recently, optically active spin defects embedded in two-dimensional (2D) van der Waals (vdW) crystals have emerged as a transformative quantum sensing platform to explore cutting-edge materials science. Taking advantage of excellent solid-state integrability, this new class of spin defects can be readily arranged in nanoscale proximity to target materials, showing great promise for realizing in-situ quantum sensing of microscopic spin and charge behaviors in vdW heterostructures. Here we report hexagonal boron nitride-based quantum imaging of field-free deterministic magnetic switching and electric current distributions in an all-vdW spin-orbit torque (SOT) system. By visualizing variations of nanoscale magnetic stray field profile of room-temperature 2D magnet Fe 3 GaTe 2 under different SOT conditions, we show how the magnetic switching evolves from deterministic to stochastic behavior due to the interplay between spin orientations, anisotropy and Joule heating. Micromagnetic simulations rationalize our results well, revealing the role of field-like SOT in inhibiting thermal fluctuation driven stochastic switching and chaotic multi-domain competition. This understanding, which is otherwise difficult to access by conventional transport measurements, offers valuable insights into material design, testing, and performance evaluation of next-generation vdW spintronic devices.

Imaging techniques

Hydrogen Production and Li-Ion Battery Performance with MoS2-SiNWs-SWNTs@ZnONPs Nanocomposites

This study explores the hydrogen generation potential via water-splitting reactions under UV-vis radiation by using a synergistic assembly of ZnO nanoparticles integrated with MoS2, single-walled carbon nanotubes (SWNTs), and crystalline silicon nanowires (SiNWs) to create the MoS2-SiNWs-SWNTs@ZnONPs nanocomposites. A comparative analysis of MoS2 synthesized through chemical and physical exfoliation methods revealed that the chemically exfoliated MoS2 exhibited superior performance, thereby being selected for all subsequent measurements. The nanostructured materials demonstrated exceptional surface characteristics, with specific surface areas exceeding 300 m2 g−1. Notably, the hydrogen production rate achieved by a composite comprising 5% MoS2, 1.7% SiNWs, and 13.3% SWNTs at an 80% ZnONPs base was approximately 3909 µmol h−1g−1 under 500 nm wavelength radiation, marking a significant improvement of over 40-fold relative to pristine ZnONPs. This enhancement underscores the remarkable photocatalytic efficiency of the composites, maintaining high hydrogen production rates above 1500 µmol h−1g−1 even under radiation wavelengths exceeding 600 nm. Furthermore, the potential of these composites for energy storage and conversion applications, specifically within rechargeable lithium-ion batteries, was investigated. Composites, similar to those utilized for hydrogen production but excluding ZnONPs to address its limited theoretical capacity and electrical conductivity, were developed. The focus was on utilizing MoS2, SiNWs, and SWNTs as anode materials for Li-ion batteries. This strategic combination significantly improved the electronic conductivity and mechanical stability of the composite. Specifically, the composite with 56% MoS2, 24% SiNWs, and 20% SWNTs offered remarkable cyclic performance with high specific capacity values, achieving a complete stability of 1000 mA h g−1 after 100 cycles at 1 A g−1. These results illuminate the dual utility of the composites, not only as innovative catalysts for hydrogen production but also as advanced materials for energy storage technologies, showcasing their potential in contributing to sustainable energy solutions.

Chemistry

Data-Driven Discovery and Experimental Validation of Solvent Polarity Effects on Conjugated Polymer Solution-to-Film Assembly Pathways

Understanding how solvent properties influence the solution-to-film assembly of conjugated polymers remains a critical challenge due to the complex and intertwined nature of polymer–solvent interactions. In this study, we integrate a data-driven framework with experimental validation to identify key parameters influencing the assembly and performance of poly[2,5-(2-octyldodecyl)-3,6-diketopyrrolopyrrole-alt-5,5-(2,5-di(thien-2-yl)thieno[3,2-b]thiophene)] (DPP-DTT) in organic field-effect transistors (OFETs). A machine learning (ML) approach identified the normalized Reichardt polarity parameter (E T N ) as a significant descriptor correlated with DPP-DTT hole mobility (μ). Systematic DPP-DTT devices fabricated using solvents across a wide E T N range revealed that higher E T N solvents yield enhanced μ. To elucidate the structural origins of high μ, we conducted comprehensive analyses using UV–vis–NIR spectroscopy and grazing incidence wide angle X-ray scattering (GIWAXS) measurements. The results revealed that films processed from high E T N solvents exhibit reduced paracrystallinity. By analyzing the solution-state behavior using optical microscopy and solution WAXS, we revealed polymer solubility differences in the various solvents and associated distinct polymer assembly pathways, elucidating why the high E T N solvent produces long-range ordered films. Notably, the high E T N solvent shows a pronounced preference for liquid-crystal (LC)-mediated assembly, providing a mechanistic explanation for the enhanced structural order. Therefore, these results demonstrate that solvent polarity, as evaluated by E T N , serves as an important parameter that plays a significant role in the DPP-DTT assembly pathway and resultant solid-state morphology. This work provides a strategy for integrating data science with experiments to identify critical parameters associated with complex polymer systems and helps guide rational process design for high-performance organic electronics.

36 MATERIALS SCIENCE

Quantum control of Hubbard excitons

Quantum control of the many-body wavefunction is a central challenge in quantum materials research, as it could yield a precise control knob to manipulate emergent phenomena. Floquet engineering, the coherent dressing of quantum states with periodic non-resonant optical fields, has become an important strategy for quantum control. Most applications to solid-state systems have targeted weakly interacting or single-ion states, leaving the manipulation of many-body wavefunctions largely unexplored. Here, in this work, we use Floquet engineering to achieve quantum control of a strongly correlated Hubbard exciton in the one-dimensional Mott insulator Sr 2 CuO 3 . A nonresonant midinfrared optical field coherently dresses the exciton wavefunction, driving its rotation between bright and dark states. We use resonant third-harmonic generation to quantify ultrafast π/2 rotations on the Bloch sphere spanned by these exciton states. Our work advances the quest towards programmable control of correlated states and exciton-based quantum sensing.

36 MATERIALS SCIENCE

High Pressure Synthesis of Ultrasmall Nanodiamonds with Nitrogen Vacancy Centers

C–H terminated nanometer scale diamonds ( d = 1 to 15 nm) are synthesized from 1-fluoroadamantane at high pressure (6–8 GPa) and high temperature (500–1500 °C) in a multianvil press. High resolution transmission electron microscopy, X-ray diffraction, Raman, diffuse reflectance Fourier transform infrared, and X-ray absorption spectroscopies demonstrate the excellent crystallinity and atomically flat C–H terminated surfaces of nanodiamonds with (111) and (110) facets. The importance of hydrogen to the synthesis of nanodiamond and its faceting is discussed. Following vacancy generation, annealing and oxidation of the nanodiamonds, optically detected magnetic resonance and electron spin resonance coherence times ( T 2 = 0.9 and 2.1 μs) of nitrogen vacancy (NV) centers are measured. Finally, the obtained T 2 values are equivalent to the shallow NV centers (depth <10 nm) in bulk diamond crystals and larger nanocrystals prepared by mechanical milling.

36 MATERIALS SCIENCE

Why Perovskite Thermal Stress is Unaffected by Thin Contact Layers

Metal halide perovskite photovoltaics have emerged as a high efficiency, low-cost alternative that can potentially rival or enhance conventional silicon technology. Despite exceptional initial power conversion efficiencies, achieving compliance with international standards and widespread adoption requires further enhancements to their operational stability. Notably, addressing mechanical strain and stress in brittle perovskites has emerged as a pivotal approach to mitigate chemical degradation and improve reliability during thermal cycling. Here, in this study, a popularized strain engineering strategy is investigated in which a high coefficient of thermal expansion (CTE) hole transport layer (i.e., PDCBT) is cast onto inorganic perovskite (CsPbI 2 Br) at 100 °C. Contrary to previously published results, the X-ray diffraction (XRD):Sin 2 ψ and substrate curvature measurement techniques show that the hole transport layer has no discernible impact on perovskite strain. The accuracy of the XRD:Sin 2 ψ method for measuring strain is highlighted in contrast to an analysis based on shifts of single XRD peaks which can be influenced by multiple artifacts. The findings in this study are in accordance with mechanics theory: thin layers are unable to induce significant strain changes in perovskite thin films as the force they apply is negligible compared to that applied by a thick and stiff substrate.

14 SOLAR ENERGY

Kinetic control of phase evolution and defect-mediated recombination in AACVD-grown copper antimony sulphide thin films

Copper antimony sulphide (CAS) is a multinary chalcogenide semiconductor in which small deviations from stoichiometry can drive phase competition and strong defect-mediated modulation of optoelectronic properties. However, the systematic roles of copper precursor fraction and deposition time in governing phase evolution, off-stoichiometry, and recombination dynamics in aerosol-assisted chemical vapour deposition (AACVD)-grown undoped CAS thin films remain insufficiently understood. In this work, undoped CAS thin films were deposited by AACVD using Cu(dedtc)2 and Sb(dedtc)3 single-source precursors at 550 °C and a carrier gas flow rate of 150 sccm, while the Cu(dedtc)2 mole fraction (x = 0.15 – 0.55) and deposition time (1 – 2 hours) were systematically varied to probe how growth kinetics influence phase composition, microstructure, and defect-mediated optical properties without post-deposition annealing or extrinsic doping. Increasing copper precursor content drives phase evolution toward tetrahedrite-dominant CAS films at intermediate Cu(dedtc)2 mole fractions, with the film deposited at x = 0.35 exhibiting the strongest tetrahedrite character within the parameter space examined. The films are also copper-rich, antimony-poor, and sulphur-deficient, consistent with off-stoichiometric growth and intrinsic defect formation, plausibly including copper interstitials, Cu-on-Sb antisites, and sulphur vacancies. These growth-dependent compositional deviations are accompanied by tunable indirect optical bandgaps of approximately 1.60 – 2.18 eV and weak visible photoluminescence governed by defect-mediated recombination. Time-resolved photoluminescence reveals bi-exponential decay behaviour with lifetimes of approximately 0.1 – 3.6 ns, with emission dominated by slower donor–acceptor pair recombination and a smaller contribution from faster trap-assisted pathways. Collectively, these results establish an explicit kinetic process–structure–defect–property relationship for AACVD-grown CAS thin films and provide a growth–structure–property framework relevant to future optimization of CAS-based optoelectronic and energy materials.

36 MATERIALS SCIENCE

Multifunctional electrochemical memory stabilized by phase coexistence

Our growing computing needs, especially in applications that heavily rely on artificial intelligence (AI), motivate a search for new components that could substantially augment the performance of general-purpose digital computers. Beyond ON/OFF switching, new components with linear multistate analog resistive tuning, nonlinear volatile switching, spiking, oscillatory, stochastic and other complex functionalities could enable highly efficient neuromorphic computing schemes for AI information processing. Compared to the extreme multifunctionality of biological neurons, realizing all the above characteristics in a single, scalable analog component remains a grand challenge. Here we investigate electrochemical gating combined with localized thermal activation to program and switch a single, vertically integrated and dimensionally scaled electrothermal chemical random access memory (ETCRAM) with a channel and reservoir composed of phase-separated vanadium oxide. Closely related to electrochemical RAM (ECRAM), ETCRAM uses an integrated gate-heater electrode to overcome kinetic barriers that help retain states at ambient temperatures. In addition to synapse-like stable and programmable analog resistance states arising from redox-tunable phase coexistence, a single component exhibits neuron-like nonlinear conductance switching with a tunable threshold and self-driven dynamics owing to the thermally driven metal-insulator phase transition in vanadium dioxide. More broadly, we demonstrate that electrochemically stabilized phase coexistence could unlock analog electronics with novel functionality, stability, reconfigurability, and scalability.

Oh, Sangheon [Sandia National Lab. (SNL-CA), Liver

Effect of Composition Variation on Isothermal Rapid Curing Resins for Aerospace Applications

To meet the projected demand for single-aisle composite aircraft in 2040, the production rate of these aircraft will need to increase by four to six times what is currently achievable. A composite manufacturing process with the potential to enable the targeted rates is isothermal resin infusion where infusion and cure occur at the same temperature. However, presently there is not an accepted aerospace-grade resin that can support this isothermal infusion process and maintain acceptable resin properties. Therefore, resin development initiatives have designed anionic catalyzed epoxy systems capable of isothermal infusion and rapid cure at a temperature below 100 ˚C in one hour. High-performance aerospace properties are achieved after undergoing a freestanding post-cure. The resins facilitate faster, energy efficient production cycles by reducing the time and temperature required for cure and eliminating temperature ramps typically required of materials used in the aerospace industry. This work discusses several of the developed resin systems and the impact of varying composition on rheological, thermal, and mechanical properties. Carbon fiber composites were fabricated for one composition by resin transfer molding to demonstrate the potential of these isothermal, rapid cure systems for meeting industry needs.

resin transfer molding

Characterization of a New Phase and Its Effect on the Work Characteristics of a Near-Stoichiometric Ni30Pt20Ti50 High-Temperature Shape Memory Alloy (HTSMA)

A new phase observed in a nominal Ni 30 Pt 20 Ti 50 (at.%) high temperature shape memory alloy has been characterized using transmission electron microscopy and 3-D atom probe tomography. This phase forms homogenously in the B2 austenite matrix by a nucleation and growth mechanism and results in a concomitant increase in the martensitic transformation temperature of the base alloy. Although the structure of this phase typically contains a high density of faults making characterization difficult, it appears to be trigonal (-3m point group) with a o ~1.28 nm and c o ~1.4 nm. Precipitation of this phase increases the microhardness of the alloy substantially over that of the solution treated and quenched single-phase material. The effect of precipitation strengthening on the work characteristics of the alloy has been explored through load-biased strain-temperature testing in the solution-treated condition and after aging at 500 ºC for times ranging from 1 to 256 hours. Work output was found to increase in the aged alloy as a result of an increase in transformation strain, but was not very sensitive to aging time. The amount of permanent deformation that occurred during thermal cycling under load was small but increased with increasing aging time and stress. Nevertheless, the dimensional stability of the alloy at short aging times (1-4 hours) was still very good making it a potentially useful material for high-temperature actuator applications.

A Garg

Recent Developments in Safe Lithium Ion Battery Design for Human Space Flight

This presentation provides an overview of EVA batteries and introduces the concept of designing lithium ion batteries that resist the propagation of a single cell catastrophic failure. Thermal runaway initiation methods are briefly discussed, and the safe performance of the resulting designs is summarized. Approached in an incremental fashion, each subsequent battery design is introduced, ending with a current development for the Exploration EVA spacesuit. Challenges in achieving safe design performance with limited internal volume are briefly discussed and forward work is identified. Video examples of both propagating and non-propagating designs are included.

lithium ion

A Tutorial on Bayesian analysis of linear shock compression data

Gas gun and other shock compression experiments often produce shock wave velocity measurements that are linearly associated with particle velocity. Traditionally, this empirical relationship is quantified with a single Hugoniot curve that is estimated using least squares regression. However, for downstream modeling and simulation tasks, it is often more useful to have multiple Hugoniot curves in the pressure–volume plane that are consistent with the data. We employ Bayesian uncertainty quantification methods as a framework for propagating measurement uncertainty through to model parameters and predictions. Specifically, this Tutorial shows how to sample multiple Hugoniot curves in the pressure–volume plane that are consistent with the shock wave-particle velocity measurements in a two-step Bayesian approach. First, we obtain an analytical expression for the posterior distribution of the linear model parameters using Bayesian linear regression. Second, we propagate samples from the posterior distribution through the Rankine–Hugoniot equations to yield Hugoniot curves in the pressure–volume plane. The procedure is demonstrated with publicly available data on argon, copper, and nickel, and compared against bootstrapping and linear regression. The Bayesian procedure is shown to be interpretable, computationally inexpensive, and less sensitive than an alternative bootstrapping approach to the removal of the point in the copper dataset that has the largest particle velocity. As a Tutorial on Bayesian methodology for the shock compression community, we provide several derivations and explanations that make this paper self-contained, and make all code and data available at github.com/llnl/BALSCD.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC