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DOE OSTI2026

Emerging hierarchical dislocation structures: Insights from scanning electron microscopy-electron backscatter diffraction in situ tensile testing and multifractal analysis

Understanding the evolution of dislocation structures during plastic deformation is critical for predicting the mechanical performance of metallic materials. In this work, we applied in situ scanning electron microscopy/electron backscatter diffraction tensile testing combined with multifractal (MF) analysis to assess deformation-induced dislocation structure evolution in solution-annealed 304 L stainless steel, both in its as-received and neutron-irradiated states (5.4 displacements per atom). The analysis of kernel average misorientation patterns revealed the formation of hierarchical dislocation arrangements that exhibit clear MF scaling behavior. Despite pronounced visual differences between nonirradiated and irradiated specimens—most notably, the appearance of dislocation channels after irradiation—the singularity spectra suggest that both conditions give rise to similar underlying hierarchical structures. MF analysis provides a quantitative measure of the spatial complexity and self-organization of dislocation patterns, highlighting the accelerated emergence and evolution of the dislocation structures in irradiated polycrystalline materials, as well as the limitation of their spatial extent. The findings indicate that irradiation not only modifies microstructure but also alters correlation-driven dislocation organization. More generally, they demonstrate that MF analysis is a powerful tool for probing mesoscale deformation mechanisms.

Dislocation structures↗

DOE OSTI2025

Classifying One-Dimensional Quantum States Prepared by a Single Round of Measurements

Measurements and feedback have emerged as powerful resources for creating many-body quantum states. However, a detailed understanding has been restricted to fixed-point representatives of phases of matter. Here, we go beyond this and characterize the patterns of many-body entanglement that can be deterministically created from measurement. Focusing on one spatial dimension, a framework is developed for the case where a single round of measurements is the only entangling operation. We show this creates matrix-product states and identify necessary and sufficient tensor conditions for preparability, which uniquely determine the preparation protocol. We use these conditions to both classify preparable quantum states and characterize their physical constraints. In particular, we find a trade-off between the richness of the preparable entanglement spectrum and correlation functions, which leads to a no-go theorem for preparing certain quantum states. More broadly, we connect properties of the preparation protocol to the resulting phase of matter, including trivial, symmetry-breaking, and symmetry-protected topological phases—for both uniform and modulated symmetries. This work offers a resource-theoretic perspective on preparable quantum entanglement and shows how to systematically create states of matter, away from their fixed points, in quantum devices. Published by the American Physical Society 2025

Sahay, Rahul (ORCID:0000000174579826)↗

DOE OSTI2024

Identification of Distorted Gamma-Ray Signature Patterns Using Digital Filtering and Auto-Associative Memory Implemented with a Hopfield Neural Network

The detection and identification of radioactive sources in search applications involve analyzing passive gamma-ray emissions from high-level radioactive materials. This process uses a mobile detector-spectrometer in a complex field test environment. Recently, the use of artificial intelligence for gamma-ray spectrum analysis has shown promising results. However, challenges persist in identifying isotopic signatures from spectral measurements that may be distorted due to source shielding, random variations in natural radioactive background, or insufficient measurement time to obtain clear spectral lines. Here, this paper presents a novel intelligent signature recognition method that combines digital filtering techniques with an artificial Hopfield Neural Network (HNN). The HNN leverages auto-associative memory to store training sample patterns and match them with incoming gamma spectra from distorted sources. It restores the testing sources’ measurements by finding the closest matching signature patterns in the spectral library. Before HNN recognition, the measured spectrum undergoes preprocessing with a digital image filter to reduce fluctuations. Performance of the proposed method is evaluated using a set of gamma-ray spectra measured with a sodium iodide detector. The data collected include measurements from six pure samples: 241 Am, 60 Co, 137 Cs, 192 Ir, 239 Pu, and 235 U, which are used for training and validation (i.e. six cases). Additionally, the data set contains 24 distorted synthesized sources with various fluctuating backgrounds. Test results demonstrate the potential of the proposed method to accurately recognize the correct isotope with high precision, achieving an accuracy rate exceeding 85%. Furthermore, the proposed method exhibits superior performance compared to the conventional multiple regression fitting and simple feedforward neural network methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Deconvoluting sources of variability in aerosol jet printing using light scattering measurements

Aerosol jet printing (AJP) is a digital additive manufacturing technique for hybrid and conformal electronics, where its contactless deposition readily enables patterning over 3D surface topography. However, the complexity of aerosol transport physics makes deposition rate sensitive to process variability, hindering widespread industry adoption. Light scattering measurements have recently been demonstrated as a capable tool for measuring deposition rate in real time, enabling closed-loop control and in-situ qualification frameworks. These inline optical measurements present further opportunity as a diagnostic tool to understand the effects of secondary process parameters affecting vapor–liquid equilibrium and heat and mass transport during deposition. Downstream of the optical measurement cell, changing the sheath gas flow rate, increasing temperature via an inline heater, and adding solvent vapor via a sheath gas bubbler were observed to alter drying physics during sheath-collimation, and thereby impaction efficiency. Further upstream, the introduction of solvent vapor via a carrier gas bubbler and liquid build-up in the printhead were seen to affect the quantitative relationship between the light scattering data and the true deposition rate. Using this information, tightened controls of meaningful secondary parameters were implemented to improve the batch-to-batch consistency for printing a dielectric ink. In addition to advancing AJP process reliability for production, this work demonstrates the capability of inline optical measurements to provide insight into process physics and deconvolute competing mechanisms that underly variability.

additive manufacturing↗

DOE OSTI2025

Mid-Infrared Photoluminescence from Tellurium Thin Films

Tellurium is an elemental semiconductor with a 0.34 eV optical band gap, showing promise for mid-infrared (MIR) optoelectronics including light-emitting diodes. However, quantitative measurement of the tellurium luminescence efficiency has not yet been investigated, and growing optically active films remain challenging. Here, we demonstrate the low-temperature growth of bright tellurium thin films by using physical vapor transport. The sample morphology is controlled by varying the growth temperature, yielding continuous thin films, microparticles, or nanowires. Additionally, we demonstrated patterned growth by using a seed layer for selective nucleation. Quantitative photoluminescence measurements at room temperature reveal an internal quantum yield of 2.0% at 0.34 eV for the as-grown tellurium films, comparable to the best-reported efficiencies of III-V and II-VI compound semiconductors with similar band gaps. Furthermore, we demonstrate band-gap tunability with Te-Se alloys, where up to 20% selenium incorporation gradually blue-shifts the band gap to 0.55 eV. The work demonstrates the potential use of tellurium for efficient MIR devices.

Wang, Shu↗

DOE OSTI2026

Quantitative measurements of dislocations in metals for advancing predictive simulations

LLNL applications require scientists to predict how materials evolve under various thermomechanical conditions. While this is achieved through physics-based simulations, uncertainty in the predictions of mechanical properties remains a serious challenge that limits the predictive capabilities of models because we lack methods to compare predictions of atomic-scale defects (dislocations) with experimental measurements. High energy X-ray diffraction (HEXRD) is the most relevant technique that can provide the necessary statistical information on dislocations. However, this technique is not yet quantitative because we lack a precise understanding of the relationship between X-ray diffraction patterns and the underlying material dislocation content and arrangements. To address this need, we used our novel computational X-ray diffraction method to simulate the effect of dislocations on the diffraction patterns. We compared virtual and experimental diffraction patterns. Results allowed us to clearly establish the relationship between X-ray diffraction patterns and the underlying dislocation structures, proving that it is feasible to quantitatively measure dislocation statistics with HEXRD. This project delivered a method that can provide the missing piece to LLNL’s mechanical property simulations in advanced metals by obtaining experimentally long-needed quantitative dislocation data, which could fully enable predictive capabilities.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Revealing the Defect‐Driven Ferroelectric Mechanisms of Aluminum Nitride

Wurtzite III-nitride compounds are CMOS-compatible with widespread industrial interest to exercise ferroelectricity, despite their polar structure being highly resistant to polarization reversal. Here, we induce and tune ferroelectric properties in w-AlN via direct-write ion-beam processing, using nanoscale patterned defect engineering as a post-growth alternative to conventional cation substitution. Nanometric piezoresponse spectroscopy of the focused He + beam patterned defect concentrations in ferroelectric Al 0.92 B 0.08 N measures a localized 10x enhancement in effective piezoresponse and 40% reduction in switching barrier. The irradiation-induced point defects convert piezoelectric AlN into a ferroelectric system with site-saturated nucleation and raise the dielectric susceptibility, switched polarization, and effective piezoelectric coefficient. Enhanced defect-lattice interactions in AlN increase carrier conduction and phonon scattering loss but preserve long-range crystallinity. Here, based on atomistic analysis of nudged elastic band density functional theory calculations and reactive force field simulations, both nitrogen vacancies and defect complexes disrupt bond ordering, facilitating a line-by-line low-barrier switching of pristine AlN.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Combustion-assisted ink-jet printing of nuclear targets

Advances in target fabrication are critical to high-precision measurements in nuclear physics. This work details the preparation of patterned CeO 2 and ThO 2 architectures and thin-film targets via ink-jet deposition of combustible solutions. The produced targets were characterized by scanning electron microscopy (SEM), and by alpha-particle spectroscopy for radioactive targets to determine densities. Ink jet printing of the targets, used both ethanol and 2-methoxyethanol as solvents, with cerium or thorium nitrate as the oxidizer and acetylacetone as the fuel. Additionally, we found that the distance between each droplet dispersion (step size) played the most significant role in determining the final pattern uniformity and thickness. A 50 μm step size leads to relatively thick targets with a density of 350 μg/cm 2 . Significant overlap in droplet sizes leads to a heterogeneous target with an undesirable cracked surface structure. In contrast, 150 μm spacing yields thinner (20 μg/cm 2 ) patterned structures with excellent surface coverage. This method of Ink-jet printing provides a straightforward, scalable, and high-efficiency pathway to prepare custom made, high-quality targets for nuclear physics experiments.

CeO2↗

DOE OSTI2024

Medium-assisted enhancement of χ c 1 ( 3872 ) production from small to large colliding systems

Studies of exotic hadrons such as the χ c 1 ( 3872 ) state provide crucial insights into the fundamental force governing the strong interaction dynamics, with an emerging frontier to investigate their production in high energy collisions where a partonic medium is present. The latest experimental measurements from the Large Hadron Collider show an intriguing evolution pattern of the χ c 1 ( 3872 ) -to- ψ ( 2 S ) yield ratio from proton-proton collisions with increasing multiplicities toward proton-lead and lead-lead collisions. Here we propose a mechanism of medium-assisted enhancement for the χ c 1 ( 3872 ) production, which competes with the more conventional absorption-induced suppression and results in a nonmonotonic trend from small to large colliding systems. Realistic simulations from this model offer a quantitative description of all available data. Predictions are made for the centrality dependence of this observable in PbPb collisions as well as for its system-size dependence from OO and ArAr to XeXe and PbPb collisions. In both cases, a nonmonotonic behavior emerges as the imprint of the competition between enhancement and suppression and can be readily tested by future data. Published by the American Physical Society 2024

Physics↗

DOE OSTI2024

Stretching and Bending Moduli of Bilayer Films Inferred from Wrinkle Patterns

Wrinkling patterns were used to investigate the mechanical properties of thin poly(styrene) (PS)/poly(methyl methacrylate) (PMMA) and PS/gold (Au) bilayer films. Films were floated on water with a water drop on the surface to induce wrinkling. The thicknesses and thickness ratios of the films were varied over a broad range. The PS/PMMA bilayer was chosen to provide a contrast in wetting properties, with equilibrium contact angles of θPMMA = 68° and θPS = 88° with water. The PS/Au bilayer was chosen to provide a large contrast in Young’s moduli, E Au = 72 GPa and E PS = 3.4 GPa. The stretching (Y) and bending (B) moduli of the bilayer films were obtained from measurements of the length and number of wrinkles in the wrinkle patterns. The experimentally derived values of Y and B were in reasonable agreement with the values computed from the bulk Young’s moduli and the thicknesses of the two components in the bilayer. The values of Y and B did not depend on which face of the film was exposed to the water droplet or bath when the capillary stresses were considered. Thus, finite size effects from the film thicknesses were unimportant over the range of thicknesses studied, and no relative displacement of the films was found, with the films remaining well-bonded even with deformation associated with wrinkling.

Chang, Jooyoung↗

DOE OSTI2025

Demonstration and Concept of Operations for a Zero-Knowledge Protocol Passive Imaging Measurement for Arms Control

Here, we present an imaging system that employs zero-knowledge protocols to protect sensitive geometrical information, along with procedures to increase confidence in the result. The goal of this work is to enable the inclusion of warhead confirmation measurements in future arms control treaties. We present a demonstration of both true positive and true negative measurements that validate models and establish authenticating procedures toward meeting acceptance requirements for use in nuclear facilities. We use a two-dimensional time-encoded fast neutron imaging system with an anti-symmetric mask pattern; the fast neutron count values exceeding minimum or maximum thresholds indicate that two measured items are not identical. Laboratory measurements over twenty trials show that alarm rates for negative confirmation measurements are within uncertainties of model predictions. Positive confirmation measurements indicate that alarm rates are large enough to encourage treaty compliance.

Sweany, Melinda Dominique [Sandia National Laborat↗

DOE OSTI2024

Observing low-altitude features in ozone concentrations in a shoreline environment via uncrewed aerial systems

Abstract. Ozone is a pollutant formed in the atmosphere by photochemical processes involving nitrogen oxides (NOx) and volatile organic compounds (VOCs) when exposed to sunlight. Tropospheric boundary layer ozone is regularly measured at ground stations and sampled infrequently through balloon, lidar, and crewed aircraft platforms, which have demonstrated characteristic patterns with altitude. Here, to better resolve vertical profiles of ozone within the atmospheric boundary layer, we developed and evaluated an uncrewed aircraft system (UAS) platform for measuring ozone and meteorological parameters of temperature, pressure, and humidity. To evaluate this approach, a UAS was flown with a portable ozone monitor and a meteorological temperature and humidity sensor to compare to tall tower measurements in northern Wisconsin. In June 2020, as a part of the WiscoDISCO20 campaign, a DJI M600 hexacopter UAS was flown with the same sensors to measure Lake Michigan shoreline ozone concentrations. This latter UAS experiment revealed a low-altitude structure in ozone concentrations in a shoreline environment showing the highest ozone at altitudes from 20–100 m a.g.l. These first such measurements of low-altitude ozone via a UAS in the Great Lakes region revealed a very shallow layer of ozone-rich air lying above the surface.

Meteorology & Atmospheric Sciences↗

DOE OSTI2024

Data-driven discovery of dynamics from time-resolved coherent scattering

Coherent X-ray scattering (CXS) techniques are capable of interrogating dynamics of nano- to mesoscale materials systems at time scales spanning several orders of magnitude. However, obtaining accurate theoretical descriptions of complex dynamics is often limited by one or more factors—the ability to visualize dynamics in real space, computational cost of high-fidelity simulations, and effectiveness of approximate or phenomenological models. In this work, we develop a data-driven framework to uncover mechanistic models of dynamics directly from time-resolved CXS measurements without solving the phase reconstruction problem for the entire time series of diffraction patterns. Our approach uses neural differential equations to parameterize unknown real-space dynamics and implements a computational scattering forward model to relate real-space predictions to reciprocal-space observations. This method is shown to recover the dynamics of several computational model systems under various simulated conditions of measurement resolution and noise. Moreover, the trained model enables estimation of long-term dynamics well beyond the maximum observation time, which can be used to inform and refine experimental parameters in practice. Finally, we demonstrate an experimental proof-of-concept by applying our framework to recover the probe trajectory from a ptychographic scan. Our proposed framework bridges the wide existing gap between approximate models and complex data.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Amplified Mesoscale and Submesoscale Variability and Increased Concentration of Precipitation under Global Warming over Western North America

Abstract Cold-season precipitation statistics in simulations from the storm-resolving WRF Model at 6-km and 1-h resolution over western North America are analyzed. Pseudo–global warming future simulations for the 2041–80 period, constrained by GCMs under the RCP8.5 scenario, are compared to the 1981–2020 historical simulation. The analysis focuses on the dynamical properties of precipitation time series at subdaily scales and on the morphology of storms. The statistical distribution of precipitation intensities in each pixel of the simulation domain is characterized through nonparametric statistical indicators: frequency of wet hours, mean wet-hour precipitation intensity, and Gini coefficient as a measure of the temporal concentration of the precipitation volume. Additionally, the temporal and spatial Fourier power spectra of precipitation time series and precipitation fields are analyzed. The half-power period (HPP) and half-power wavelength (HPW) are defined as spectral measures of the characteristic scales of precipitation’s temporal and spatial patterns. The results show statistically significant increases in the mean wet-hour precipitation intensity and in the Gini coefficient in 99% of the pixels, indicating that the seasonal precipitation volume becomes more concentrated within a smaller number of hours with higher precipitation intensity. The statistics of change in the frequency of wet hours are more contrasted across the simulation domain. The changes are also reflected in the power spectra, which show the spatial and temporal variability increasing proportionally more with finer spatial and temporal scales and the HPW and HPP decreasing. These projected changes are expected to have consequences, not only in terms of hydrologic impacts but also in terms of the predictability of precipitation patterns. Significance Statement The precipitation characteristics of winter storms over the western United States and southwestern Canada are analyzed in future climate simulations for the 2041–80 period. As compared to present-day climate, the most intense parts of the storms are projected to produce a higher rainfall volume, with increased concentration over smaller areas and shorter time intervals. The propensity of rainfall intensity to vary rapidly over time will be enhanced in the future according to the simulations. These model predictions imply an increased risk of rapid flooding in small basins. They also suggest that predicting several hours ahead the time and location at which a storm will produce maximum rainfall may become more challenging in the future.

Climate change↗

DOE OSTI2026

High-speed particle analysis using forward and backward two-dimensional angular optical scattering

Measurement of two-dimensional angle-resolved optical scattering (TAOS) patterns is an attractive technique for detecting and characterizing micron-sized high-speed flying particles. The elastic-scattering intensity pattern from a single particle as a function of spherical coordinate angles θ and ϕ provides detailed information on the particle’s morphology. By use of an ellipsoidal reflector and a high-speed CCD camera, scattering from a CW-laser was detected and resolved over a large angular range (θ from 12° to 168° and ϕ from 0° to 360°) from spherically shaped particles (e.g., amorphous silica and borosilicate glass) flowing through the reflector’s focal plane at speeds of 20 to 30 m/s. The scattering pattern from individual particles flying through the focal plane of the ellipsoid mirror provides insights about a particle’s size, clustering, roughness, and velocity.

Optics and optical instruments↗

DOE OSTI2026

Residential Vehicle-to-Home Backup Power Capabilities: Key Findings from a ComEd Beneficial Electrification R&D Pilot

This report summarizes key findings from a collaborative technical study of residential, non-grid-tied vehicle-to-home (V2H) backup power systems in Commonwealth Edison’s (ComEd’s) service territory. The work integrates (1) a feeder-level technoeconomic analysis (TEA) using historical outage-event data and simulated electric-vehicle (EV) driving/charging profiles to estimate potential reliability and customer interruption-cost impacts under V2H and vehicle-to-grid (V2G) adoption scenarios; (2) controlled laboratory performance testing of a representative V2H backup ecosystem to characterize transfer-to-backup behavior, sustained power delivery, efficiency trends, and repeatable reliability limitations; and (3) a cybersecurity assessment aligned with NIST Cybersecurity Framework (CSF) 2.0 and ISO/SAE 21434 to evaluate interface-level risk drivers and identify program-relevant mitigations. Results indicate that V2H can provide measurable resilience value, but outcomes are strongly context dependent on outage patterns and the share of events that are “V2H-applicable.” Typical transfer-to-backup behavior clustered on the order of minutes, but rare long-delay edge cases were observed (including an event approaching 30 minutes) and should be treated as a reliability risk. High-power testing showed that peak-rated output is not necessarily continuously deliverable; stable operation may require operation below nameplate ratings and attention to thermal and installation constraints. The cybersecurity assessment highlights a broad attack surface spanning commissioning, home networks, embedded services, and cloud/OTA pathways, motivating minimum controls for secure onboarding, signed updates, patch cadence, and coordinated vulnerability response for any scaled deployment.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Refactoring the elastic–viscous–plastic solver from the sea ice model CICE v6.5.1 for improved performance

This study focuses on the performance of the elastic–viscous–plastic (EVP) dynamical solver within the sea ice model, CICE v6.5.1. The study has been conducted in two steps. First, the standard EVP solver was extracted from CICE for experiments with refactored versions, which are used for performance testing. Second, one refactored version was integrated and tested in the full CICE model to demonstrate that the new algorithms do not significantly impact the physical results. The study reveals two dominant bottlenecks, namely (1) the number of Message Parsing Interface (MPI) and Open Multi-Processing (OpenMP) synchronization points required for halo exchanges during each time step combined with the irregular domain of active sea ice points and (2) the lack of single-instruction, multiple-data (SIMD) code generation. The standard EVP solver has been refactored based on two generic patterns. The first pattern exposes how general finite differences on masked multi-dimensional arrays can be expressed in order to produce significantly better code generation by changing the memory access pattern from random access to direct access. The second pattern takes an alternative approach to handle static grid properties. The measured single-core performance improvement is more than a factor of 5 compared to the standard implementation. The refactored implementation of strong scales on the Intel® Xeon® Scalable Processors series node until the available bandwidth of the node is used. For the Intel® Xeon® CPU Max series, there is sufficient bandwidth to allow the strong scaling to continue for all the cores on the node, resulting in a single-node improvement factor of 35 over the standard implementation. This study also demonstrates improved performance on GPU processors.

58 GEOSCIENCES↗

DOE OSTI2026

Flow pattern and void fraction characterization in nitrogen/water flows through a diamond-type triply periodic minimal surface lattice

Here, this study presents, to the authors knowledge, the first experimental investigation on the void fraction and flow patterns in two-phase flows through a diamond-type Triply Periodic Minimal Surface (TPMS) lattice. An additively manufactured TPMS structure was tested under upward co-current flow of a water/nitrogen mixture. Superficial velocities varied for a total of 42 test conditions (gas: 0.01–2.4 m/s; liquid: 0.01–2.4 m/s; mass flux: 20–2370 kg/m 2 ·s). High-speed video and X-ray imaging enabled time-averaged void fraction measurements and identified six distinct flow regimes which were used to develop a flow pattern map. Comparison of the void fraction data with correlations from literature demonstrated the Rouhani and Axelsson (1970) [49] correlation modified by Steiner (1993) [52] provided the best agreement, which was improved with empirically fit coefficients. This approach predicted the void fraction with errors < ±20% for 64% of the data, with a mean absolute percent deviation (MAPD) of 23%. The measured frictional pressure drop was compared to correlations from literature which captured the observed trends but did not provide good accuracy. The best agreement was found after optimizing the empirical coefficients of the Muller-Steinhagen & Heck (1986) [56] correlation; this approach captured 33% of the data within ±20% with a MAPD of 46% over the full range and captured 71% of the data within ±20% a MAPD of 13.3% at mass fluxes >1100 kg/m 2 -s. These results provide foundational insight into TPMS two-phase flow behavior and inform modeling and design of advanced heat exchange components incorporating TPMS geometries.

42 - ENGINEERING↗