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At least 271 records · Page 15

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DOE OSTI2025

Thermal processing to modulate surface chemistry and bulk charge distribution in nickel-rich layered lithium positive electrodes

The broader application of nickel-rich layered oxides as positive electrode materials for lithium-ion batteries has been hindered by their high manufacturing cost and inferior cycling stability. Thermal processing, which is integral to electrode materials manufacturing and fundamental in materials science, has not been fully utilized to design advanced positive electrode materials. Herein, we demonstrate the capability of using quenching heat treatment to regulate Li distribution and modulate electronic structure near particle surface. The resulting materials exhibit less parasitic reactions with the electrolyte and an improved charge distribution homogeneity in secondary particles, leading to more stable cycling performance at high voltages (4.5 V vs Li/Li + ). Our synchrotron X-ray analyses reveal the underlying interplay between surface structure and bulk charge distribution in positive electrode materials particles. While strategies used to stabilize positive electrode materials through compositional control, surface modification, and electrolyte engineering have become mature, thermal processing can be advantageous to further improve positive electrode materials manufacturing.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Reversible control over the distribution of chemical inhomogeneities in multiferroic BiFeO3

Abstract Despite the appeal of flawless order, semiconductor technology has demonstrated that implanting inhomogeneities into single-crystalline materials is pivotal for modern electronics. However, the influence of the local arrangement of chemical inhomogeneities on the material’s functionalities is underexplored. In this work, we control the distribution of chemical inhomogeneities in La 3+ -substituted ferroelectric BiFeO 3 thin films. By means of a stress- and composition-driven phase transition, we trigger the formation of a lattice of La 3+ -rich and La 3+ -poor layers. This ordering correlates with the emergence of an antipolar phase. An electric field restores the original ferroelectric phase and re-randomizes the distribution of the La 3+ inhomogeneities. Leveraging these insights, we tune the polar/antipolar phase coexistence to set the net polarization of La 0.15 Bi 0.85 FeO 3 to any desired value between its saturation limits. Finally, we control the net polarization response in device-compliant capacitor heterostructures to show that inhomogeneity-distribution control is a valuable tool in the design of functional oxide electronics.

Science & Technology - Other Topics↗

DOE OSTI2024

Updimensioning strategy derived from synthetic equiaxed grain structures for approximating 3D grain size distributions from 2D visualizations with 1D parameters

We generated synthetic equiaxed grain structures using computer graphics software to explore the relationship between various grain size determination methods and true three-dimensional (3D) grain diameters. Mirroring grain measurement techniques, the synthetic 3D grain structures are imaged as 2D micrographs which are measured to yield 1D grain size parameters. Synthetic grain structures provide data at a mass scale and permit exploration of both polished and fractured surface micrographs, revealing one-to-one correspondence between exposed 2D grain cross-sections and individual 3D grains. Analysis of this correspondence yielded a procedure to approximate 3D equiaxed grain size and volume distributions based on the mode of the 2D fractograph grain size distribution. The 3D approximation procedure is shown to be less susceptible to different imaging conditions that affect small, undiscernible grains compared to the standard planimetric and linear intercept methods, which by design also tend to underestimate the 3D grain diameter. The procedure requires larger sample sizes to lower variance and a deeper analysis which could become more practical with machine learning (ML) models for grain boundary segmentation, which synthetic grain structures can help train. This work lays the foundation for analyzing other grain distributions such as columnar and composite grains in similar depth.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Utilizing Distributed Heterogeneous Computing with PanDA in ATLAS

In recent years, advanced and complex analysis workflows have gained increasing importance in the ATLAS experiment at CERN, one of the large scientific experiments at LHC. Support for such workflows has allowed users to exploit remote computing resources and service providers distributed worldwide, overcoming limitations on local resources and services. The spectrum of computing options keeps increasing across the Worldwide LHC Computing Grid (WLCG), volunteer computing, high-performance computing, commercial clouds, and emerging service levels like Platform-as-a-Service (PaaS), Container-as-a-Service (CaaS) and Function-as-a-Service (FaaS), each one providing new advantages and constraints. Users can significantly benefit from these providers, but at the same time, it is cumbersome to deal with multiple providers, even in a single analysis workflow with fine-grained requirements coming from their applications’ nature and characteristics. In this paper, we will first highlight issues in geographically-distributed heterogeneous computing, such as the insulation of users from the complexities of dealing with remote providers, smart workload routing, complex resource provisioning, seamless execution of advanced workflows, workflow description, pseudointeractive analysis, and integration of PaaS, CaaS, and FaaS providers. We will also outline solutions developed in ATLAS with the Production and Distributed Analysis (PanDA) system and future challenges for LHC Run4.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Optimization of distributed compute resources utilization in the CMS Global Pool

The CMS Submission Infrastructure is the primary system for managing computing resources for CMS workflows, including data processing, simulation, and analysis. It integrates geographically distributed resources from Grid, HPC, and cloud providers into federated pools managed by HTCondor and Glidein- WMS, for a total of around 500k CPU cores. This system dynamically manages workloads based on priorities defined by the collaboration. Additionally, CMS scheduling strategies must be flexible to handle multiple concurrent workloads while considering changing processing demands and resource availability from various providers.Efficient utilization of vast amounts of distributed compute resources is a key element for the success of the scientific programs of the LHC experiments. Optimizing the system is essential to maximize resource efficiency and fully utilize the distributed computing power. The CMS Submission Infrastructure team thus systematically investigates sources of inefficiency in workload scheduling to reduce their impact. In addition, a strategy of pilot overloading has been introduced to compensate for other inefficiency sources, thereby optimizing resource utilization and enhancing computational throughput.

Mascheroni, Marco [UC, San Diego (main)]↗

DOE OSTI2024

Parametrized ion-distribution model for extended x-ray absorption fine-structure analysis at high-energy-density conditions

Experiments today can compress solids near isentropically to pressures approaching 100 × 106 atmospheres; however, determining the temperature of such matter remains a major challenge. Extended x-ray absorption fine-structure (EXAFS) spectroscopy is one of the few techniques sensitive to the bulk temperature of highly compressed solid matter, and the validity of this temperature measurement relies on constraining the local ion structure from the EXAFS spectrum. At high-energy-density (HED) conditions, the local ion structure often becomes distorted, which must be accounted for during the EXAFS analysis. Described here is a technique, using a parametrized ion-distribution model to directly analyze EXAFS spectra that provides a better constraint on the local structure than traditional second- or third-order cumulant expansion techniques at HED conditions. The parametrized ion-distribution model is benchmarked by analyzing EXAFS spectra from nickel molecular-dynamics simulations at ∼100 GPa and shown to provide a 10%–20% improvement in constraining the cumulants of the true ion distribution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

A compact x-ray spectrometer for measurements of electron temperature distributions in inertial confinement fusion implosions at OMEGA

The Wedge Range Filter (WRF), commonly used for proton spectroscopy at the OMEGA Laser Facility and National Ignition Facility, is adapted to measure the x-ray continuum spectrum through transmission measurement using a continuous-gradient filter. Continuum x rays emitted from the hotspot of an implosion contain information about the plasma composition and electron temperature. The WRF data are leveraged to probe this distribution, specifically the electron temperature distribution. In this work, the data recorded with the WRF are forward modeled using a temperature distribution model folded with the WRF response function. An uncertainty analysis is conducted through a Bayesian regression algorithm using a Hamiltonian Monte Carlo sampler. This analysis enables the uncertainties in the instrument response to be folded into the uncertainty estimation of the electron temperature and absolute x-ray emission. Data analysis for a series of OMEGA implosions is presented and compared with radiation hydrodynamic simulations.

Lasers↗

DOE OSTI2025

Foliar elemental distribution in Blepharidium guatemalense assessed by synchrotron X-ray fluorescence spectroscopy and colorimetric optical microscopy

The hyperaccumulation phenomenon holds significant potential for Ni agromining in ultramafic areas; however, data on tropical hyperaccumulator species, particularly regarding metal distribution and tolerance mechanisms, remain scarce. Here, this study characterized the foliar elemental distribution of Blepharidium guatemalense, analyzed its metal localization at both tissue and cellular levels, and quantified its Ni accumulation when grown in Brazilian ultramafic soil. Plants were grown in pots for 90 days, and Ni concentrations in the aerial biomass and bio-ore were determined. Synchrotron-based micro-X-ray fluorescence (S-µXRF) was used to assess metal distribution in tissues, supplemented by microscopic examination with dimethylglyoxime (DMG) to visualize Ni accumulation in specific cell types. B. guatemalense reached 19,000 mg kg −1 Ni in leaves. Processing leaf biomass produced ash containing 24 wt% Ni, indicating promising metal-recovery potential for the species. S-µXRF revealed that Ni was predominantly localized in the central and secondary veins of the leaves, suggesting efficient vascular transport. Microscopic analysis using the colorimetric reagent DMG further showed that Ni accumulation occurs near the epidermis and phloem, suggesting that B. guatemalense employs specific physiological mechanisms for Ni translocation, potentially supporting both defense and growth functions. These results establish B. guatemalense as a promising candidate for large-scale Ni agromining in tropical regions.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Quench protection for high-temperature superconductor cables using active control of current distribution

Superconducting magnets of future fusion reactors are expected to rely on composite high-temperature superconductor (HTS) cable conductors. In presently used HTS cables, current sharing between components is limited due to poorly defined contact resistances between superconducting tapes or by design. The interplay between contact and termination resistances is the defining factor for power dissipation in these cables and ultimately defines their safe operational margins. However, the current distribution between components along the composite conductor and inside its terminations is a priori unknown, and presently, no means are available to actively tune current flow distribution in real-time to improve margins of quench protection. Also, the lack of ability to electrically probe individual components makes it impossible to identify conductor damage locations within the cable. In this work, we address both problems by introducing active current control of current distribution between components using cryogenically operated metal-oxide-semiconductor-field-effect transistors (MOSFETs). We demonstrate through simulation and experiments how real-time current controls can help to drastically reduce heat dissipation in a developing hot spot in a two-conductor model system and help identify critical current degradation of individual cable components. Finally, prospects of other potential uses of MOSFET devices for improved voltage detection, AC loss-driven active quench protection, and remnant magnetization reduction in HTS magnets are also discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Comprehensive earthquake catalogue update and spatiotemporal distribution analysis for Iraq and surrounding regions, northeastern Arabian Plate

The updated earthquake catalogue for Iraq covers the period from 1900 to the end of 2021 and includes over 37 000 recorded earthquakes. To create this comprehensive catalogue, five key steps were taken: compiling bulletins, calculating moment magnitudes, harmonizing magnitudes, establishing empirical conversion relations and evaluating the completeness of the catalogue. A notable enhancement in this update is the direct calculation of moment magnitudes for approximately 2800 earthquakes, achieved through the coda envelope technique and waveform data from the Mesopotamian Seismological Network (MPSN) in Iraq. This updated catalogue serves as a valuable resource for examining the spatiotemporal distribution of earthquakes, with respect to earthquake density, maximum moment magnitude and seismogenic depths. Additionally, the Gutenberg–Richter relationship was applied to calculate the a- and b-values specific to Iraq. The findings show that the Zagros Fold-Thrust Belt has a seismogenic layer (source) that ranges from 2 to 33 km deep and experiences high seismic activity. In contrast, the Mesopotamian Foredeep has a seismogenic layer ranging from 1 to 25 km deep and has lower seismic activity. The greatest seismic activity is concentrated around the Mandili-Badra-Teeb fault, which has experienced significant ruptures over time. The Outer Arabian Platform is identified as the main area of seismic activity, while additional activity occurs on the Inner Arabian Platform. Three major tectonic boundaries define the distribution of earthquakes in the northeastern Arabian Plate. These boundaries are defined by the Main Zagros Reverse Fault, the Zagros Foredeep Fault and the Anah Graben and Abu Jir-Euphrates Fault Zone. These boundaries highlight variations in seismicity levels and the spatial distribution of deformation in the region. The updated earthquake catalogue presented in this study is expected to play a vital role in regional seismicity assessments and seismic hazard analyses for Iraq and its surrounding areas.

58 GEOSCIENCES↗

DOE OSTI2025

Tomography of pions and kaons in the QCD vacuum: Transverse momentum dependent parton distribution functions

We evaluate the pion and kaon transverse momentum dependent parton distribution functions in the instanton liquid model, a model of the QCD vacuum at low resolution. The relevant transverse momentum distributions (TMDs) are factored into a constituent quark distribution times a rapidity dependent soft factor from staple-shaped Wilson lines, for fixed parton longitudinal momentum and transverse separation. The results are evolved to higher rapidities using the Collins-Soper kernel and higher resolution using renormalization group evolution. The comparison to existing extractions of pion TMDs from Drell-Yan data is briefly discussed.

classical solutions in field theory↗

DOE OSTI2026

Probing the 𝑗 dependence of angular distributions and 𝑁=20 shell rigidity via the 36 S (𝑝,𝑑) 35 S reaction

An investigation of the N=20 36 S nucleus has been performed through a detailed study of the 3 6S (p,d)3 5S neutron-removal reaction, employing a 66-MeV proton beam at iThemba Laboratory for Accelerator Based Sciences and an innovative target design. Using the high-resolution K = 600 magnetic spectrometer, 98 states in 3 5S were identified up to 16-MeV excitation energy, including 47 previously unobserved states. Angular distributions and spectroscopic factors, including isobaric analog-state contributions, were extracted for 81 levels. A pronounced j dependence in the angular distributions of ℓ=2 states provides refined insights into the spin-orbit splitting. Finite-range adiabatic distorted-wave approximation calculations qualitatively reproduce the observed j dependence. Comparisons of the measured 1d 5/2 spectroscopic strength distribution with large-scale shell-model and ab initio calculations show good agreement overall, and the robustness of the N=20 shell closure in 36 S is confirmed when comparing the relatively low fp orbital occupancies in 40 Ca and 3 6S across the Fermi surface. This study underscores the utility of neutron-removal reactions in probing nuclear structure and the Fermi surface of sd nuclei and beyond. The findings advance our understanding of shell evolution and offer constraining data for theoretical models.

20 ≤ A ≤ 38↗

DOE OSTI2025

T -odd parton distribution functions and azimuthal anisotropy at high transverse momentum in p − p and p − A collisions

Various azimuthal anisotropies ( v 1 , v 2 , v 3 , v 4 ), at high transverse momentum (high p T ), are shown to arise from the asymmetric scattering of transverse polarized quarks and gluons, arising from unpolarized nucleons (the Boer-Mulders effect) and resulting in unpolarized hadrons (the Collins effect). Combined with the asymmetric scattering of partons from polarization independent but transverse momentum dependent (TMD) distributions, we obtain a possible mechanism to understand the azimuthal anisotropy of hadrons at large transverse momentum observed in p − p collisions. Constraining the ratio of polarization dependent TMD distributions to polarization independent distributions by comparing with the data from p − p collisions, we find that scaling the acquired transverse momentum of the initial state partons from the proton, due to prescattering before the hard interaction, with the length of the nucleus ( k ⊥ 2 ∝ A 1 / 3 ), straightforwardly yields the azimuthal anisotropy at high p T in p − A collisions. Published by the American Physical Society 2025

Soudi, Ismail (ORCID:0000000235751782)↗

DOE OSTI2024

Systematic improvement of x -dependent unpolarized nucleon generalized parton distributions in lattice-QCD calculation

We present a first study of the effects of renormalization-group resummation (RGR) and leading-renormalon resummation (LRR) on the systematic errors of the unpolarized isovector nucleon generalized parton distribution in the framework of large-momentum effective theory. This work is done using lattice gauge ensembles generated by the MILC Collaboration, consisting of 2 + 1 + 1 flavors of highly improved staggered quarks with a physical pion mass at lattice spacing a ≈ 0.09 fm and a box width L ≈ 5.76 fm . We present results for the nucleon H and E generalized parton distributions (GPDs) with average boost momentum P z ≈ 2 GeV at momentum transfers Q 2 = [ 0 , 0.97 ] GeV 2 at skewness ξ = 0 as well as Q 2 ∈ 0.23 GeV 2 at ξ = 0.1 , renormalized in the modified minimal subtraction ( MS ¯ ) scheme at scale μ = 2.0 GeV , with two- and one-loop matching, respectively. We demonstrate that the simultaneous application of RGR and LRR significantly reduces the systematic errors in renormalized matrix elements and distributions for both the zero and nonzero skewness GPDs, and that it is necessary to include both RGR and LRR at higher orders in the matching and renormalization processes. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

DOE OSTI2025

Exploring the Three-Dimensional Momentum Distribution of Longitudinally Polarized Quarks in the Proton

By analyzing experimental data on semi-inclusive deep inelastic scattering off longitudinally polarized targets, we extract the transverse momentum dependence of the quark helicity distribution, i.e., the difference between the three-dimensional motion of quarks with polarization parallel or antiparallel to the longitudinal polarization of the parent hadron. We perform the analysis at next-to-leading and next-to-next-to-leading perturbative accuracy. The quality of the fit is very good for both cases, reaching a χ 2 per number of data points equal to 1.11 and 1.09, respectively. Although the limited number of data points leads to significant uncertainties, the data are consistent with an interpretation in which the helicity distribution is narrower in transverse momentum than the unpolarized distribution. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Quantum-enhanced distributed phase sensing with a truncated SU(1,1) interferometer

In recent years, distributed quantum sensing has gained interest for a range of applications requiring networks of sensors, from global-scale clock synchronization to high energy physics. In particular, a network of entangled sensors can improve not only the sensitivity beyond the shot noise limit, but also enable a Heisenberg scaling with the number of sensors. Here, using bright entangled twin beams, we theoretically and experimentally demonstrate the detection of a linear combination of two distributed phases beyond the shot noise limit with a truncated SU(1,1) interferometer. Specifically, we show a quantum noise reduction of 1.7 ± 0.3 dB below what is possible with the corresponding classical configuration. Additionally, we theoretically extend the use of a truncated SU(1,1) interferometer to a multi-phase-distributed sensing scheme that leverages entanglement as a resource to achieve a quantum improvement in the scaling with the number of sensors in the network. Our results pave the way for developing quantum-enhanced sensor networks that can achieve an entanglement-enhanced sensitivity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Network Anomaly Detection in Distributed Edge Computing Infrastructure

As networks continue to grow in complexity and scale, detecting anomalies has become increasingly challenging, particularly in diverse and geographically dispersed environments. Traditional approaches often struggle with managing the computational burden associated with analyzing large-scale network traffic to identify anomalies. This paper introduces a distributed edge computing framework that integrates federated learning with Apache Spark and Kubernetes to address these challenges. We hypothesize that our approach, which enables collaborative model training across distributed nodes, significantly enhances the detection accuracy of network anomalies across different network types. We show that by leveraging distributed computing and containerization technologies, our framework not only improves scalability and fault tolerance but also achieves superior detection performance compared to state-of-the-art methods. Extensive experiments on the UNSW-NB15 and ROAD datasets validate the effectiveness of our approach, demonstrating statistically significant improvements in detection accuracy and training efficiency over baseline models, as confirmed by MannWhitney U and Kolmogorov-Smirnov tests (p<0.05).

Marfo, William [University of Texas at El Paso,Dep↗

DOE OSTI2024

MassiveGNN: Efficient Training via Prefetching for Massively Connected Distributed Graphs

Graph Neural Networks (GNN) are indispensable in learning from graph-structured data, yet their rising computational costs, especially on massively connected graphs, pose significant challenges in terms of execution performance. To tackle this, distributed-memory solutions such as partitioning the graph to concurrently train multiple replicas of GNNs are in practice. However, approaches requiring a partitioned graph usually suffer from communication overhead and load imbalance, even under optimal partitioning and communication strategies due to irregularities in the neighborhood minibatch sampling. This paper proposes practical trade-offs for improving the sampling and communication overheads for representation learn- ing on distributed graphs (using popular GraphSAGE architecture) by developing a parameterized prefetch and eviction scheme on top of the state-of-the-art Amazon DistDGL distributed GNN framework, demonstrating about 15–40% improvement in end-to-end training performance on the NERSC Perlmutter supercomputer for various OGB datasets.

Machine Leanring, high performance comptuing, grap↗