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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Designing for cooperative grain boundary segregation in multicomponent alloys

Tailoring the nanoscale distribution of chemical species at grain boundaries is a powerful method to dramatically influence the properties of polycrystalline materials. However, classical approaches to the problem have tacitly assumed that only competition is possible between solute species. In this paper, we show that solute elements can cooperate in the way they segregate to grain boundaries: In properly targeted alloys, the different chemical species cooperate to each fill complementary grain boundary sites disfavored by the other. By developing a theoretical “spectral” approach to this problem based on quantum-accurate grain boundary site distributions, we show how grain boundaries can be cooperatively alloyed, whether by depletion or enrichment. We provide machine-learned cosegregation information for over 700 ternary aluminum-based alloys and experimentally validate the concept in one ternary alloy where cosegregation is not expected by prior models but is expected based on the cooperative model.

grain boundaries↗
DOE OSTI2024

Evidence of short chains in liquid sulfur

High energy x-ray pair distribution function measurements show the average coordination number of the first shell in liquid sulfur is 1.86 ± 0.04 across the λ-transition, not precisely 2.0 as widely accepted. This indicates that upon melting, liquid sulfur does not comprise solely of S 8 rings but also possesses a significant number of short chains. Intensities of the pre-peak and first diffraction peak of the x-ray structure factor and third peak height of the pair distribution function all show deviations at the λ-transition temperature T λ , associated with the break-up of S 8 rings and the start of oligomer polymerization. A significant number of non-bonded or loosely bonded “interstitial atoms,” with an average coordination number of 0.20 ± 0.005, are also observed in the so-called “forbidden zone” between the first and second shells upon melting. The number of interstitial atoms is found to decrease to a minimum at the λ-transition, but the majority persist into the high temperature polymerized liquid. Furthermore, the existence of short chains and nearby interstitial atoms represent the two main factors required to initiate the S 8 -ring to chain transition, as proposed by recent molecular dynamics simulations.

Chemical bonding↗
DOE OSTI2026

Risk-Aware Measurement Synchronization and Recovery for DSSE With Heterogeneous Data Sources

Power distribution systems are increasingly integrating heterogeneous sensors with varying data reporting rates and types, which pose challenges to achieving observability at the desired temporal resolution of distribution system state estimation (DSSE). Multisensor failures caused by extreme events exacerbate these issues, introducing substantial uncertainties into DSSE. This article proposes a novel solution to these challenges by ensuring high-resolution system observability despite heterogeneous data sources and multisensor failures. First, a deep learning architecture combining long short-term memory (LSTM) and graph convolutional network (GCN) is employed to synchronize meters with different reporting rates, aiming to achieve system observability. A random-walk-model-based approach is introduced to generate pseudo-measurements while properly characterizing their uncertainties under multisensor failures. Finally, a disaster-risk-informed observability metric (RiOM) is defined to quantify the uncertainty associated with state estimation results. The proposed framework offers deeper insights into the system observability on the fly compared with conventional analysis. The effectiveness of the framework is demonstrated on an IEEE standard test case and a large-scale real-world distribution feeder in mid-Minnesota in the U.S.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A Fast Dynamic Internal Predictive Power Scheduling Approach for Power Management in Microgrids: Preprint

This paper presents a Dynamic Internal Predictive Power Scheduling (DIPPS) approach for optimizing power management in microgrids, particularly focusing on external power exchanges among diverse prosumers. DIPPS utilizes a dynamic objective function with a time-varying binary parameter to control the timing of power transfers to the external grid, facilitated by efficient usage of energy storage for surplus renewable power. The microgrid power scheduling problem is modeled as a mixed-integer nonlinear programming (MINLP-PS) and subsequently transformed into a mixed-integer linear programming (MILPPS) optimization through McCormick's relaxation to reduce computational complexity. A predictive window window with 6 data points is solved at an average of 0.92s, a 97.6% improvement over the 38.27s required for the MINLP-PS formulation, implying the numerical feasibility of the DIPPS approach for real-time implementation. Finally, the approach is validated against a static objective using real-world load data across three case studies with different time-varying parameters, demonstrating the ability of DIPPS to optimize power exchanges and efficiently utilize distributed resources while shifting the external power transfers to specified time durations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Enhancing Discoverability and Management of Atmospheric Data at Scale: Solutions from the ARM Data Center

The Atmospheric Radiation Measurement (ARM) is a multi-laboratory and multi-institutional U.S. Department of Energy (DOE) Office of Science National User Facility. The ARM Data Center (ADC), located at Oak Ridge National Laboratory, collects, archives, and shares vast atmospheric data crucial for climate research. The ADC manages over 7 PB of data from 460 instruments worldwide, processing it into more than 11,000 diverse data products using the Network Common Data Form (NetCDF) for machine-independent accessibility. The primary challenge addressed in this paper is the efficient management and distribution of vast and diverse datasets essential for the climate research community, enhancing accessibility through advanced tools like Data Discovery. The ADC has developed advanced infrastructure and software architecture to handle the continuous influx of heterogeneous data to enhance data discoverability, resulting in increased scientific collaboration. In 2023, users from over 34 countries downloaded and utilized ARM data, resulting in 1,455 publications. The ADC’s efforts have significantly improved the discoverability and usability of atmospheric data, fostering extensive scientific research and collaboration. This paper details the solutions implemented by the ADC team for efficient data discovery and distribution, and it demonstrates ARM’s capability of staging processed data for scientific analysis.

Shah, Chirag [ORNL] (ORCID:0000000203145737)↗
DOE OSTI2024

A structural underpinning of the lower critical solution temperature (LCST) behavior behind temperature-switchable liquids

In this work, we use state-of-the-art X-ray scattering and molecular dynamics to analyze amine-water mixtures that show the unusual lower critical solution temperature (LCST) behavior. The goal is to provide direct experimental evidence for the entropy-lowering molecular cluster formation hypothesized as necessary for LCST behavior. Differential wide-angle X-ray scattering and pair distribution analysis and small-angle X-ray scattering measurements were combined with molecular modeling and liquid-liquid equilibrium measurements, revealing direct experimental evidence for the hypothesis. However, the response of the amine phase to accommodating water is even more subtle than the simple hypothesis suggests, with the formation of robust nanoscale reverse micelles. The techniques developed in this paper can be expected to yield insights in the use of temperature-switchable liquids in solvent extraction and other separations, and the stabilization of organelles in living cells that do not have physical membranes but do require compositional gradients to operate.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Distributed and Secure Spectrum Sharing for 5G and 6G Networks

Secure spectrum sharing or spectrum co-existence of multiple 5G networks and future 6G networks is a powerful enabler technology. The National Spectrum Strategy (NSS) published by the White House in November, 2023, and the subsequent NSS implementation plan led by the National Telecommunication and Information Administration (NTIA) is the driver of a national effort to enable co-existence of government incumbents and commercial networks in selected spectrum bands. Cellular networks such as 5G & 6G and non-cellular Wi-Fi 6E & 7 are the prominent wireless technologies considered for co-existence with incumbent wireless links. Security of the spectrum sharing solutions is a must to make this transformation of spectrum use possible, specially for mission critical communications. However, current spectrum sharing solutions rely on centralized data bases with inherent vulnerabilities. This paper focuses on secure spectrum sharing among multiple 5G networks using unlicensed and shared frequency bands. It presents an innovative AI/ML based distributed spectrum sharing approach that can be autonomously used by multiple networks. Each sharing network uses its own observation of the Radio Frequency (RF) environment, which consists of RF measurements reported from the 5G User Equipment (UE), to adjust the transmission power levels for secure co-existence. Data is presented to illustrate the superior performance of this solution compared to other spectrum sharing solutions where each network can utilize usage data of the other networks. Finally it discusses how this efficient spectrum sharing solution can evolve in the future for the 6G networks.

5G↗
DOE OSTI2025

Seeding Advanced Treated Wastewater for Purposes of Direct Potable Reuse

Direct potable reuse (DPR) is a promising solution to address water scarcity. However, a better understanding of how introducing advanced treated water (ATW) affects microbial communities present in distribution systems is needed. Here, in this study, we measured changes to the microbial water quality in simulated distribution systems that were conditioned using treated, unimpaired surface water (SW) and then transitioned to ATW. In addition, we investigated whether adding a biological filtration step would seed the microbial community of the ATW and whether the influence would persist in the simulated distribution systems. We found that the bulk water in the ATW-fed distribution systems had lower cell counts and ATP concentrations and a distinct microbial community (based on 16S amplicon sequencing) compared to the SW-fed or the seeded ATW-fed systems. However, biofilm community composition and biomass remained consistent regardless of the feedwater. Increased microbial biomass and diversity were present in the seeded ATW, with several amplicon sequence variants identified as being introduced by the biological filter. Our results suggest that directly introducing ATW to distribution systems could disturb the existing microbial community. Preparing ATW for distribution via biological filtration may deliver more predictable and stable microbial water quality than introducing unseeded ATW.

16S↗
DOE OSTI2024

Formation of Disordered Cocontinuous Phases by Randomly Linked Star Copolymers

Cocontinuous polymeric nanostructures have garnered significant interest due to their ability to combine different properties of two separate polymer domains. Randomly linked copolymer networks have proven to be especially robust for formation of disordered cocontinuous phases across wide composition ranges (≈30 wt % or more). While theoretical treatments of microphase-separated networks have focused primarily on the role of random elastic forces imposed on the self-assembled nanostructures by virtue of the network architecture, experimental studies seeking to disentangle these contributions from other potential effects, such as dispersity in preferred interfacial curvatures, have been scarce. To provide insight into this matter, we here study the self-assembly of randomly linked star copolymers (RSCs), constructed by linking premade polymer arms of polystyrene (PS) and poly(d,l-lactide) (PLA) using 3, 4, and 6-functional connectors. This architecture yields similar distributions of preferred curvature as networks made using corresponding difunctional strands, but lacks the elastic forces imposed by a network architecture. Gravimetry and small-angle X-ray scattering, coupled with scanning electron microscopy, were performed to identify the percolation of PS/PLA RSCs. Remarkably, the 4-arm RSC system exhibited a disordered cocontinuous window of ≈25 wt %, indicating that dispersity in preferred curvature can in some cases be sufficient to robustly drive formation of this morphology. However, the other RSC architectures showed smaller cocontinuous ranges, which we interpret in terms of the influence of homopolymer stars in the 3-arm case and the narrower distribution of preferred interfacial curvatures in the 6-arm case. Finally, thin layers of interconnected porous PS were achieved by solution-processing, suggesting that RSCs have the potential to serve as a robust and easily processable cocontinuous polymeric nanomaterials in both bulk and membrane geometries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Modulating the Electronic Transport of 2D Sb2Te3 Nanoplates by Coinage Metal Intercalation

Thermoelectric materials are particularly relevant to the current energy infrastructure and demands of the 21st century, converting waste heat into usable electricity. The solution intercalation of zerovalent copper into Sb2Te3 nanoplates, a well-established thermoelectric material, is reported. The copper intercalant is homogeneously distributed throughout the nanoplates, confirmed by scanning transmission electron microscopy coupled with energy-dispersive X-ray spectroscopy. The copper composition was shown to be 6 at. % by X-ray photoelectron spectroscopy. Copper ordering within the van der Waals gaps of the nanoplates is confirmed by selected area electron diffraction. Fabrication and thermoelectric property measurements of single-crystal Sb2Te3 and Cu-Sb2Te3 nanoplate devices show effective modulation of electrical conductivity and Seebeck coefficient with Cu intercalation. X-ray photoelectron spectroscopic studies in the valence-band region reveal additional electronic states from copper that appear near the Fermi energy, postulated to act as electron acceptors, leading to modulation of the electronic transport properties.

2D nanoplates↗
DOE OSTI2024

First experimental confirmation of island SOL geometry effects in a high radiation regime on W7-X

Abstract This work characterizes the detachment behavior and radiation characteristics of the low
iota configuration in the Wendelstein 7-X (W7-X) stellarator. The island scrape-off layer (SOL) of the
low iota has a poloidal mode number of 6 islands surrounding the last closed flux surface (LCFS).
The island geometry of the low iota configuration is significantly different to that of the standard
magnetic field configuration, whose detachment characteristics have already been described in previous
work[2, 3, 4]. Experimental results show that the radiation pattern in the low iota configuration
is starkly different to that of the standard magnetic field configuration, with radiation concentrated
at the island SOL O-points, rather than the X-points. Additionally, this O-point localized radiation
pattern is associated with unstable detachment, with both radiation oscillations in experiments and the
lack of a self-consistent plasma solution at high radiated power fraction in EMC3-Eirene simulations.
EMC3-Eirene simulations are used to understand the radiation distribution. It was found that the O-
point localized radiation arises first from local impurity accumulation near the parallel flow stagnation,
which is located close to the geometrical center of the island (”O-point”). The local cooling in this
region leads to plasma condensation in the islands in closest magnetic connection to the divertor target
plates. The heat source to this region of the island, which is thermally isolated from the upstream heat
source in terms of parallel transport, must arise via perpendicular heat transport. This heat source is
expected to be large for the low iota configuration due to its very small internal island field line pitch.
This work highlights the importance (complementary to previous work, e. g. [5, 6]) of the internal
island field line pitch not only on the radiation pattern, but also the detachment performance of the
island divertor.

Winters, Victoria (ORCID:0000000181087774)↗
DOE OSTI2026

Accelerating LHC event generation with simplified pilot runs and fast PDFs

High-precision calculations are an indispensable ingredient for the success of the LHC physics programme, yet their poor computing efficiency has been a growing cause for concern, threatening to become a paralysing bottleneck in the coming years. We present solutions to eliminate the apprehension by focussing on two major components of generalpurpose Monte Carlo event generators: the evaluation of parton distribution functions, and the generation of perturbative matrix elements. We show that for the cost-driving event samples employed by the ATLAS experiment to model omnipresent, irreducible Standard Model backgrounds, such as weak boson or top-quark pair production in association with jets, these computational components dominate the overall run time by up to 80 %. We demonstrate that a reduction of the computing footprint of LHAPDF and SHERPA by factors of around 40 can be achieved for multi-leg NLO event generation.

Bothmann, Enrico [Gottingen U.]↗
DOE OSTI2024

Forecasts for Land-Based Wind Deployment in the United States: Wind Industry Survey Results [Slides]

Recent land-based wind deployment in the United States has been sluggish, and expectations for future growth have moderated in recent years. Berkeley Lab conducted a brief survey of wind industry stakeholders to better understand barriers and solutions. The focus of the survey was on land-based wind projects in the United States – not offshore wind or distributed small wind projects. Respondents identified challenges related to the grid and to siting as the most pressing concerns.

17 WIND ENERGY↗
DOE OSTI2026

A Community Guide to Regulatory Barriers Affecting Microgrids (Reports 1-3)

In response to growing risks of power outages from extreme weather and aging infrastructure, communities are increasingly exploring the potential of microgrids to provide reliable energy access. Microgrids offer promising solutions to meet this challenge but face a complex landscape of non-technical barriers, particularly regulations concerning the provision and distribution of energy. Most existing legal and regulatory frameworks were designed for a centralized, one-way power system, and are often poorly suited to handle systems that independently balance distributed energy resources with local load. This three-part report series provides a strategic analysis of existing regulatory and legal factors affecting microgrid deployments to help non-technical community leaders and decision-makers better understand the feasibility of a microgrid in their community. -Report No. 1: Foundational Issues Facing Microgrids details the universal policy barriers all microgrids face, including utility interconnection processes, rate structures, and local permitting. -Report No. 2: Single Property Microgrids outlines how direct asset ownership and operating behind-the-meter can bypass some regulatory oversight, using the Blue Lake Rancheria microgrid as a case study. -Report No. 3: Multi-Property Microgrids tackles the complex challenges of crossing public rights-of-way and navigating utility franchise rights, highlighting the Coventry microgrid project. The series equips decision-makers with phased frameworks to navigate financial and regulatory complexities, engage effectively with local utilities and Authorities Having Jurisdiction (AHJs), and structure successful microgrid projects.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

End-to-end deep learning pipeline for real-time Bragg peak segmentation: from training to large-scale deployment

X-ray crystallography reconstruction, which transforms discrete X-ray diffraction patterns into three-dimensional molecular structures, relies critically on accurate Bragg peak finding for structure determination. As X-ray free electron laser (XFEL) facilities advance toward MHz data rates (1 million images per second), traditional peak finding algorithms that require manual parameter tuning or exhaustive grid searches across multiple experiments become increasingly impractical. While deep learning approaches offer promising solutions, their deployment in high-throughput environments presents significant challenges in automated dataset labeling, model scalability, edge deployment efficiency, and distributed inference capabilities. We present an end-to-end deep learning pipeline with three key components: (1) a data engine that combines traditional algorithms with our peak matching algorithm to generate high-quality training data at scale, (2) a modular architecture that scales from a few million to hundreds of million parameters, enabling us to train large expert-level models offline while deploying smaller, distilled models at the edge, and (3) a decoupled producer-consumer architecture that separates specialized data source layer from model inference, enabling flexible deployment across diverse computing environments. Using this integrated approach, our pipeline achieves accuracy comparable to traditional methods tuned by human experts while eliminating the need for experiment-specific parameter tuning. Although current throughput requires optimization for MHz facilities, our system's scalable architecture and demonstrated model compression capabilities provide a foundation for future high-throughput XFEL deployments.

Wang, Cong↗
DOE OSTI2024

The structure of CaO–MgO–Al 2 O 3 –SiO 2 melts and glasses doped with FeO X –NiO

Neutron and x-ray diffraction measurements have been performed on CaO–MgO–Al 2 O 3 –SiO 2 (CMAS) glasses doped with NiO–Fe X O at room temperature, along with x-ray measurements on aerodynamically levitated liquids at ≥2000 K. The disordered structures have been modeled using empirical potential structure refinement to investigate the relation between the aluminosilicate network and the modifying cations. The SiO 4 and AlO 4 tetrahedra are found to have wider Si–O and Al–O bond distance distributions in the glass, and the first Ca–O n coordination shell is highly distorted, redistributing different populations of long and short bonds between the liquid and the glass. The addition of Fe and Ni at low aluminosilicate content increases the number of free oxygens not bonded to AlO 4 or SiO 4 . Mg–O and Fe–O are both found to be predominantly fourfold and fivefold in the liquid and glassy states. Despite these low coordination numbers, their bond angle distributions indicate that they are predominantly in nontetrahedral-type geometries, with ferrous and ferric iron possessing similar coordination environments. The Ca–O and Mg–O average coordination numbers and enthalpies of solution are consistent with their higher reactivity within relatively acidic aluminosilicate melts.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Structural Evolution and Photoluminescence Quenching across the FASnI 3– x Br x ( x = 0–3) Perovskites

One of the primary methods for band gap tuning in metal halide perovskites has been halide (I/Br) mixing. Despite widespread usage of this type of chemical substitution in perovskite photovoltaics, there is still little understanding of the structural impacts of halide alloying, with the assumption being the formation of ideal solid solutions. The FASnI 3–x Br x (x = 0–3) family of compounds provides the first example where the assumption breaks down, as the composition space is broken into two unique regimes (x = 0–2.9; x = 2.9–3) based on their average structure with the former having a 3D and the latter having an extended 3D (pseudo 0D) structure. Pair distribution function (PDF) analyses further suggest a dynamic 5s 2 lone pair expression resulting in increasing levels of off-centering of the central Sn as the Br concentration is increased. These antiferroelectric distortions indicate that even the x = 0–2.9 phase space behaves as a nonideal solid-solution on a more local scale. Solid-state NMR confirms the difference in local structure yielding greater insight into the chemical nature and local distributions of the FA + cation. In contrast to the FAPbI 3–x Br x series, a drastic photoluminescence (PL) quenching is observed with x ≥ 1.9 compounds having no observable PL. In conclusion, our detailed studies attribute this quenching to structural transitions induced by the distortions of the [SnBr 6 ] octahedra in response to stereochemically expressed lone pairs of electrons. This is confirmed through density functional theory, having a direct impact on the electronic structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A physics-informed deep learning description of Knudsen layer reactivity reduction

A physics-informed neural network (PINN) is used to evaluate the fast ion distribution in the hot spot of an inertial confinement fusion target. The use of tailored input and output layers to the neural network is shown to enable a PINN to learn the parametric solution to the Vlasov–Fokker–Planck equation in the absence of any synthetic or experimental data. As an explicit demonstration of the approach, the specific problem of Knudsen layer fusion yield reduction is treated. Here, the predictions from the Vlasov–Fokker–Planck PINN are used to provide a non-perturbative solution of the fast ion tail in the vicinity of the hot spot, thus allowing the spatial profile of the fusion reactivity to be evaluated for a range of collisionalities and hot spot conditions. Excellent agreement is found between the predictions of the Vlasov–Fokker–Planck PINN and the results from traditional numerical solvers with respect to both the energy and spatial distribution of fast ions and the fusion reactivity profile, demonstrating that the Vlasov–Fokker–Planck PINN provides an accurate and efficient means of determining the impact of Knudsen layer yield reduction across a broad range of plasma conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗