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DOE OSTI2022

Fifty ways to build a deuteron: a variational calculation of two-nucleon systems

A variational study of two-nucleon systems with lattice quantum chromodynamics is performed using a wide range of interpolating operators: dibaryon operators built from products of momentum-projected nucleons, hexaquark operators built from six spatially localized quarks, and quasi-local operators inspired by two-nucleon bound-state wavefunctions in nuclear effective field theories. Correlation-function matrices involving products of these operators are constructed by computing timeslice-to-all quark propagators with sparsening techniques. Comparisons between results obtained using the same gauge-field ensemble but different interpolating-operator sets demonstrate that interpolating-operator dependence can lead to significant effects on the two-nucleon energy spectra obtained using both variational and non-variational methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Application of electron backscatter diffraction techniques to quantify effects of aging on sub-grain and spatial heterogeneity in NMC cathodes

Identification and evaluation of structural heterogeneity in spent cathode materials is crucial to developing appropriate remediation strategies for novel recycling processes. Native heterogeneities may be exacerbated during the cell's operational lifetime, as sub-particle-scale variations induce anisotropic expansion and contraction upon cycling. Structural transformations resulting from repeated cycling and calendar aging predominantly occur at the secondary particle surface and at the grain boundaries (GBs) between primary particles. However, the diffusion and stress build up around and across GBs are poorly understood. In this study, electron backscatter diffraction (EBSD) is employed to track sub-grain lattice structure across a statistically relevant number of Li(Ni0.33Mn0.33Co0.33)O2 (NMC-111) particles. Specifically, differences in lattice misorientation – measured as the deviation from the grain's average orientation – are tracked as a function of position within the electrode (near current collector, middle, and near separator) and as a function of electrochemical cycling. Further, a novel method of structural analysis is developed, offering insight into sub-grain diffusion behavior by comparing lattice misorientation near the grain boundary versus in the grain bulk. The present results suggest that electrode-scale spatial heterogeneity in lattice structure is induced by initial manufacturing conditions, and that radial gradients in lattice misorientation evolve at the primary particle scale with repeated electrochemical cycling.

25 ENERGY STORAGE↗

DOE OSTI2024

Uncovering grain and subgrain microstructure at the scale of additive manufacturing melt tracks with a scalable cellular automaton solidification model

Metal additive manufacturing, characterized by rapid solidification, yields refined grains with a distinctive cellular subgrain microstructure that plays a pivotal role in determining material properties. Due to the significant computational expense demanded to simulate the required physics with submicron spatial resolution, their numerical simulations have been limited to proof-of-concept studies to either 2D or small subregions of a melt pool. In this study, an open-source, scalable, solidification code, muMatScale, based on the cellular automaton method, has been developed to predict the grain and the underlying subgrain microstructure over an entire melt pool. The model incorporates flexible parallelization schemes, utilizing MPI and OpenMP GPU Offloading, in addition to appropriate multi-physics specific to non-equilibrium rapid solidification in AM. The impact of nucleation parameters on grain microstructures was investigated with a focus on grain size variations and morphology transitions. With selected nucleation parameters, the simulation predicted the grain size, subgrain morphology, crystallographic orientation, and microsegregation aligned with experimental measurements. The model demonstrates that epitaxial grain growth is a dominant factor at the melt pool boundary, influencing grain size variation under different grain sizes in the build plate while maintaining consistent primary dendrite arm spacing under identical thermal conditions. Here, the highly efficient numerical model enables large-scale simulations with a spatial resolution of 100 nm or less, unveiling unprecedented insights into thermal and solutal diffusion driven grain growth, and the subgrains with microsegregation within grains in 3D across scales. muMatScale will enable the linking of submicron length-scale microstructure to part-level material behavior by investigating fundamental solidification problems at the intercellular scale in many-track and many-layer builds.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Theory and numerics of subspace approximation of eigenvalue problems

Large-scale eigenvalue problems arise in various fields of science and engineering and demand computationally efficient solutions. In this study, we investigate the subspace approximation for parametric linear eigenvalue problems, aiming to mitigate the computational burden associated with high-fidelity systems. Furthermore, we provide general error estimates under non-simple eigenvalue conditions, establishing some theoretical foundations for understanding the convergence behavior of subspace approximations. Numerical examples, including problems with one-dimensional to three-dimensional spatial domain and one-dimensional to two-dimensional parameter domain, are presented to demonstrate the efficacy of reduced basis method in handling parametric variations in boundary conditions and coefficient fields to achieve significant computational savings while maintaining high accuracy, making them promising tools for practical applications in large-scale eigenvalue computations.

Eigenvalue problems↗

DOE OSTI2025

Myna: Connecting powder bed fusion build data to simulation tools for digital twin applications

Additive manufacturing (AM), as a digital process, can generate a detailed digital thread linking a part’s design and manufacturing to its operational performance. As AM systems advance, an increasing amount of process data is stored in manufacturing databases. In principle, this data can be utilized by simulation-based digital twin approaches, such as real-time process control and asynchronous post-processing guidance. However, few tools currently exist for systematically integrating digital thread data with computational tools. Here, in this study, we propose a software package, called Myna, for connecting data from powder bed fusion processes to simulation tools. The utility of such a platform is demonstrated using build data from the Oak Ridge National Laboratory Manufacturing Demonstration Facility “Peregrine v2023-10” public dataset to automatically configure and run 54 semi-analytical 3DThesis melt pool simulations, 78 numerical Additive FOAM melt pool simulations, and 3 ExaCA microstructure simulations. The simulated, spatially registered microstructures are then compared directly with electron backscatter diffraction characterization of the corresponding as-built part locations. The resulting simulated microstructure showed variation as a function of process parameters, particularly stripe width; however, the experimental data had little variation between the microstructure texture and grain size resulting from different processing conditions. Analysis of the discrepancies suggest that it is possible a two-phase ferritic-austenitic solidification model is needed to accurately predict grain size and texture for certain stainless steel 316L feedstock compositions under powder bed fusion conditions, providing direction for future research. As illustrated here, due to the number and complexity of the simulations involved in AM process-structure–property predictions, automated methods to connect process data and simulations will remain necessary tools for testing hypotheses and implementing digital twin applications.

Knapp, Gerald L. [Oak Ridge National Laboratory (O↗

DOE OSTI2024

Infinitely rugged intra-cage potential energy landscape in metallic glasses caused by many-body interaction

The absence of translational symmetry in glassy materials poses a significant challenge in establishing effective structure-property relationships in real space. Consequently, the potential energy landscape (PEL) in phase space is widely utilized to comprehend the complex phenomena in glasses. The classical PEL features a two-scale profile comprising mega-basins and sub-basins, corresponding to α-relaxations (e.g. glass transition) and β-relaxations (e.g. local cage-breaking atomic rearrangements), respectively. Recent studies, however, reveal that sub-basins are not smooth and contain finer structures, the origins of which remain elusive. Here we probe the smoothness of sub-basin bottoms in glasses' PEL by introducing small intra-cage cyclic loading and then measuring the net changes in atomic-level stresses. Compared to glasses with pair interaction, glasses with many-body interaction exhibit orders-of-magnitude larger and loading-dependent stress changes even before the first cage-breaking event takes place, which reflect much more feature-rich sub-basins. We further demonstrate this stark contrast stems from the spatial distribution of individual atom's constraining force field. Specifically, at vanishing perturbations, many-body interactions disrupt the positive-definite synchrony in energy variations of the perturbed atom and the whole system, causing inherently less confined atomic responses and infinitely rugged sub-basins. The implications of these findings for the selective addition or removal of fine structures in the PEL and the subsequent tuning of glassy materials' responses to external stimuli are also explored.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Disentangling Coexisting Structural Order Through Phase Lock-In Analysis of Atomic-Resolution STEM Data

As a real-space technique, atomic-resolution STEM imaging contains both amplitude and geometric phase information about structural order in materials, with the latter encoding important information about local variations and heterogeneities present in crystalline lattices. Such phase information can be extracted using geometric phase analysis (GPA), a method which has generally focused on spatially mapping elastic strain. Here we demonstrate an alternative phase demodulation technique and its application to reveal complex structural phenomena in correlated quantum materials. As with other methods of image phase analysis, the phase lock-in approach can be implemented to extract detailed information about structural order and disorder, including dislocations and compound defects in crystals. Extending the application of this phase analysis to Fourier components that encode periodic modulations of the crystalline lattice, such as superlattice or secondary frequency peaks, we extract the behavior of multiple distinct order parameters within the same image, yielding insights into not only the crystalline heterogeneity but also subtle emergent order parameters such as antipolar displacements. When applied to atomic-resolution images spanning large (~0.5 × 0.5 μm 2 ) fields of view, this approach enables vivid visualizations of the spatial interplay between various structural orders in novel materials.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2025

Multimodal characterization of Te inclusions in Cd 1−x Zn x Te and Cd 1−x Zn x Te 1−y Se y for gamma and X-ray detectors

While CdZnTe (CZT) and CdZnTeSe (CZTS) semiconductors have emerged as compounds for room-temperature gamma and X-ray detection materials, they continue to be constrained by the formation of Te-inclusion defects generated during the growth and post-growth phases of the material, which adversely affect the detector performance. We demonstrate the utility of multimodal microscopic imaging and analysis for the characterization of the optical and electronic properties of Te inclusions in CZT and CZTS crystals at both micron and nanometer length scales. Having first identified regions with micron-scale Te inclusions using confocal Raman microscopy techniques, optically coupled infrared scattering near-field optical microscopic mapping was performed to map the distribution of these inclusions with nanometer spatial resolution and correlate the presence of Te inclusions in the matrix with other properties. Kelvin probe force microscopy was then utilized to characterize the variations of the work function associated with the presence of Te inclusions. Here, we observe an increase of ~ 240 mV in the work function associated with Te inclusions compared to the bulk CZT/CZTS crystals. Additionally, we observe that individual bulk grains in CZT can exhibit slight potential variations. Our findings develop a portrait of the charge trapping mechanisms in CZT and CZTS that act to degrade detector performance, while the demonstration of these combined microscopy techniques provides a new analytical tool that can be utilized for further optimization of the detector performance for these semiconducting compounds.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Angular correlations of cosmic microwave background spectrum distortions from photon diffusion

ABSTRACT During cosmic recombination, charged particles bind into neutral atoms and the mean free path of photons rapidly increases, resulting in the familiar diffusion damping of primordial radiation temperature variations. An additional effect is a small photon spectrum distortion, because photons arriving from a particular sky direction were originally in thermal equilibrium at various spatial locations with different temperatures; the combination of these different blackbody temperature distributions results in a spectrum with a Compton y-distortion. Using the approximation that photons had zero mean free path prior to their second-to-last scattering, we derive an expression for the resulting y-distortion, and compute the angular correlation function of the diffusion y-distortion and its cross-correlation with the square of the photon temperature fluctuation. Detection of the cross-correlation is within reach of existing arcminute-resolution microwave background experiments such as the Atacama Cosmology Telescope and the South Pole Telescope.

Astronomy & Astrophysics↗

DOE OSTI2019

Responses of the Hadley Circulation to Regional Sea Surface Temperature Changes

We discuss idealized experiments performed with the Community Atmospheric Model 5.3 which indicate that the width and strength of the Hadley circulation (HC) are sensitive to the location of sea surface temperature (SST) increases. The HC edge shifts poleward in response to SST increases over the subtropical regions near and on the equatorward flank of the HC edge, and shifts equatorward in response to warming over the tropical area except for the western Pacific Ocean and Indian Ocean. The HC is strengthened in response to SST increases over the intertropical convergence zone (ITCZ) and is weakened in response to SST increases over the subsidence branch of the HC in the subtropics. Tropical SST increases off the ITCZ tend to weaken the HC in the corresponding hemisphere and strengthen the HC in the opposite hemisphere. These results could be used to explain the simulated HC changes induced by recent SST variations, and it is estimated that more than half of the SST-induced HC widening in 1980–2014 is caused by changes in the spatial pattern of SST.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Soil characteristics and land-use drive bacterial community assembly patterns

ABSTRACT Land-use and soil characteristics drive variation in soil community composition, but the influences of these factors on dispersal and community assembly at regional scale remain poorly characterized. Land-use remains a consistent driver of soil community composition even when exhibiting patchy spatial distribution at regional scale. In addition, disturbed and early successional soils often exhibit stochastic community assembly patterns. These observations suggest local community composition is influenced by dispersal and assembly from regional species pools. We examined bacterial community assembly within agricultural cropland, old-field, and forested sites across 10 landscapes in the region around Ithaca, New York (USA). We found that the Sloan neutral model explained assembly well at regional scale (R2 = 0.763), but that both soil pH and land-use imposed selection that shaped community composition. We show that homogeneous selection was a dominant assembly process with respect to both soil pH and land-use regime, but that these two factors interacted in their effects on bacterial community assembly. We conclude that bacterial community assembly at a regional scale is driven by dispersal from regional species pools and local selection on the basis of soil pH and other soil characteristics that vary with land-use.

Microbiology↗

DOE OSTI2024

Real-time dynamics of the Schwinger model as an open quantum system with Neural Density Operators

Ab-initio simulations of multiple heavy quarks propagating in a Quark-Gluon Plasma are computationally difficult to perform due to the large dimension of the space of density matrices. This work develops machine learning algorithms to overcome this difficulty by approximating exact quantum states with neural network parametrisations, specifically Neural Density Operators. As a proof of principle demonstration in a QCD-like theory, the approach is applied to solve the Lindblad master equation in the 1 + 1d lattice Schwinger Model as an open quantum system. Neural Density Operators enable the study of in-medium dynamics on large lattice volumes, where multiple-string interactions and their effects on string-breaking and recombination phenomena can be studied. Thermal properties of the system at equilibrium can also be probed with these methods by variationally constructing the steady state of the Lindblad master equation. Scaling of this approach with system size is studied, and numerical demonstrations on up to 32 spatial lattice sites and with up to 3 interacting strings are performed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Simultaneous Observations of Electromagnetic Ion Cyclotron (EMIC) Waves and Pitch Angle Scattering During a Van Allen Probes Conjunction

On 22 December 2015, the two Van Allen Probes observed two sets of electromagnetic ion cyclotron (EMIC) wave bursts during a close conjunction when both Probe A and Probe B were separated by 0.57 to 0.68 R E . Here, the EMIC waves occurred during an active period in the recovery phase of a coronal mass ejection-driven geomagnetic storm. Both spacecraft observed EMIC wave bursts that had similar spatial structure within a 1–2 min time delay. The EMIC waves occurred outside the plasmasphere, within ΔL ≈ 1–2 of the plasmapause and within a few degrees in magnetic latitude of the equatorial plane. The spatial structure of the EMIC wave bursts may have been related to the proton drift paths outside the plasmasphere and influenced by total magnetic field strength variations associated with solar wind pressure enhancements. The EMIC waves were observed in a narrow L shell region from L ≈ 4.55–5.32 between 10 and 11 magnetic local time (MLT) on the outbound halves of the spacecraft orbits and from L ≈ 4.82–5.51 between 13 and 14 MLT on the inbound halves of the spacecraft orbits. However, Pc1 pulsations were observed on the ground over a broad range of local times. The anisotropy of the proton pitch angle distributions was enhanced when the EMIC waves were observed. Although the overall radiation belt response during this storm was dominated by acceleration and transport processes, the EMIC waves produced local pitch angle scattering of 13–15 keV protons and 2.1–2.6 MeV electrons, consistent with calculations of the expected resonant energies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Predictive Inverse Model for Advective Heat Transfer in a Short–Circuited Fracture: Dimensional Analysis, Machine Learning, and Field Demonstration

Identifying fluid flow maldistribution in planar geometries is a well–established problem in subsurface science/engineering. Of particular importance to the thermal performance of enhanced (or “engineered”) geothermal systems is identifying the existence of nonuniform (i.e., heterogeneous) permeability and subsequently predicting advective heat transfer. Here, machine learning via a genetic algorithm (GA) identifies the spatial distribution of an unknown permeability field in a two–dimensional Hele–Shaw geometry (i.e., parallel plates). The inverse problem is solved by minimizing the L2 norm between simulated residence time distribution (RTD) and measurements of an inert tracer breakthrough curve (BTC) (C–Dot nanoparticle). Principal component analysis (PCA) of spatially correlated permeability fields enabled reduction of the parameter space by more than a factor of 10 and restricted the inverse search to reservoir–scale permeability variations. Thermal experiments and tracer tests conducted at the mesoscale Altona Field Laboratory (AFL) demonstrate that the method accurately predicts the effects of extreme flow channeling on heat transfer in a single bedding–plane rock fracture. However, this is only true when the permeability distributions provide adequate matches to both tracer RTD and frictional pressure loss. Without good agreement to frictional pressure loss, it is still possible to match a simulated RTD to measurements, but subsequent predictions of heat transfer are grossly inaccurate. Here, the results of this study suggest that it is possible to anticipate the thermal effects of flow maldistribution, but only if both simulated RTDs and frictional pressure loss between fluid inlets and outlets are in good agreement with measurements.

42 ENGINEERING↗

DOE OSTI2022

Nanoscale imaging of phonon dynamics by electron microscopy

Spatially resolved vibrational mapping of nanostructures is indispensable to the development and understanding of thermal nanodevices, modulation of thermal transport and novel nanostructured thermoelectric materials. Through the engineering of complex structures, such as alloys, nanostructures and superlattice interfaces, one can significantly alter the propagation of phonons and suppress material thermal conductivity while maintaining electrical conductivity. There have been no correlative experiments that spatially track the modulation of phonon properties in and around nanostructures due to spatial resolution limitations of conventional optical phonon detection techniques. Here we demonstrate two-dimensional spatial mapping of phonons in a single silicon–germanium (SiGe) quantum dot (QD) using monochromated electron energy loss spectroscopy in the transmission electron microscope. Tracking the variation of the Si optical mode in and around the QD, we observe the nanoscale modification of the composition-induced red shift. We observe non-equilibrium phonons that only exist near the interface and, furthermore, develop a novel technique to differentially map phonon momenta, providing direct evidence that the interplay between diffuse and specular reflection largely depends on the detailed atomistic structure: a major advancement in the field. Our work unveils the non-equilibrium phonon dynamics at nanoscale interfaces and can be used to study actual nanodevices and aid in the understanding of heat dissipation near nanoscale hotspots, which is crucial for future high-performance nanoelectronics.

36 MATERIALS SCIENCE↗

DOE OSTI2021

2D monochromatic x-ray imaging for beam monitoring of an x-ray free electron laser and a high-power femtosecond laser

Single-shot simultaneous beam monitoring of an x-ray free electron laser (XFEL) and a high-power femtosecond laser is demonstrated using 2D monochromatic Kα imaging. In a pump-probe experiment carried out at the Matter in Extreme Conditions end-station of the Linac Coherent Light Source, a thin solid titanium foil irradiated by a 25-TW relativistic intensity laser for fast electron isochoric heating was probed by a 7.0 keV XFEL beam for x-ray Thomson scattering measurements. Using a spherical crystal imager (SCI), the spatial overlap of the beams was examined by measuring 4.5 keV titanium Kα x rays produced by laseraccelerated fast electrons and the x-ray beam. Changes in XFEL-induced Kα emission patterns were observed down to a ~20×40 μm2 rectangular shape as the beam was focused. Laser-only and two-beam shots reveal that large spatial offsets of laser-induced Kα spots in a horizontal direction is attributed to imprecise target positioning rather than shot-to-shot laser pointing variations. As a consequence, successful beam overlapping was observed on ~58% of all two-beam shots for 10 μm thick samples. The Kα measurements also show a linear relationship between total Kα yields and integrated x-ray scattering signals. Monochromatic xray imaging with SCI could be used as an on-shot beam pointing diagnostic in XFEL-laser or multiple short-pulse laser experiments.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Tetraquarks made of sufficiently unequal-mass heavy quarks are bound in QCD

Tetraquarks, bound states composed of two quarks and two antiquarks, have been the subject of intense study but are challenging to understand from first principles. We apply variational and Green’s function Monte Carlo methods to compute tetraquark ground-state energies in potential nonrelativistic QCD using a wide range of color and spatial wave functions. We find no evidence for bound tetraquarks composed of equal-mass quarks and antiquarks. Conversely, we find clear evidence for the existence of bound tetraquarks for sufficiently unequal quark/antiquark mass ratios at all overall mass scales where our effective theory results are applicable. We predict the critical mass ratios for bound state formation and study tetraquark bound states’ spatial and color structure at leading order and next-to-leading order in potential nonrelativistic QCD. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Solving the sample size problem for resource selection functions

Abstract Sample size sufficiency is a critical consideration for estimating resource selection functions (RSFs) from GPS‐based animal telemetry. Cited thresholds for sufficiency include a number of captured animals and as many relocations per animal N as possible. These thresholds render many RSF‐based studies misleading if large sample sizes were truly insufficient, or unpublishable if small sample sizes were sufficient but failed to meet reviewer expectations. We provide the first comprehensive solution for RSF sample size by deriving closed‐form mathematical expressions for the number of animals M and the number of relocations per animal N required for model outputs to a given degree of precision. The sample sizes needed depend on just 3 biologically meaningful quantities: habitat selection strength, variation in individual selection and a novel measure of landscape complexity, which we define rigorously. The mathematical expressions are calculable for any environmental dataset at any spatial scale and are applicable to any study involving resource selection (including sessile organisms). We validate our analytical solutions using globally relevant empirical data including 5,678,623 GPS locations from 511 animals from 10 species (omnivores, carnivores and herbivores living in boreal, temperate and tropical forests, montane woodlands, swamps and Arctic tundra). Our analytic expressions show that the required M and N must decline with increasing selection strength and increasing landscape complexity, and this decline is insensitive to the definition of availability used in the analysis. Our results demonstrate that the most biologically relevant effects on the utilization distribution (i.e. those landscape conditions with the greatest absolute magnitude of resource selection) can often be estimated with much fewer than animals. We identify several critical steps in implementing these equations, including (a) a priori selection of expected model coefficients and (b) regular sampling of background (pseudoabsence) data within a given definition of availability. We discuss possible methods to identify a priori expectations for habitat selection coefficients, effects of scale on RSF estimation and caveats for rare species applications. We argue that these equations should be a mandatory component for all future RSF studies.

Street, Garrett M.↗