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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Role of 3D neoclassical particle flux in density pump-out during ELM control by RMP in DIII-D

Application of three-dimensional (3-D) resonant magnetic perturbations, for the purpose of controlling edge localized modes (ELMs) in high confinement (H-mode) tokamak fusion operations, routinely leads to significantly reduction of the plasma density during the discharge, a phenomenon termed 'density pump-out'. Understanding the density pump-out phenomenon due to 3-D fields is a longstanding challenging issue. This work discusses a self-consistent toroidal model that allows initial value simulation of the density pump-out effect. The model successfully reproduces pump-out phenomenology in DIII-D ELM suppression experiments. The radial particle flux, associated with the 3-D neoclassical effects (the neoclassical toroidal viscosity, NTV), is discovered to play an important role in producing the observed large density pump- out. The key physics is associated with the drift kinetic Landau resonances between the toroidal precession of trapped thermal ions and electrons from one side, and the magnetic field perturbation from the other side. Such resonances, occurring near the top of the pedestal region, substantially enhances the radial particle flux associated with NTV. As a general consequence of the resonant NTV flux, larger density pump- out occurs in plasmas with lower collisionality and slower toroidal rotation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Cornering relative symmetry theories

The symmetry data of a 𝑑-dimensional quantum field theory (QFT) can often be captured in terms of a higher-dimensional symmetry topological field theory. In top-down (i.e., stringy) realizations of this structure, the QFT in question is localized in a higher-dimensional bulk. In many cases of interest, however, the associated (𝑑+1)-dimensional bulk is not fully gapped and one must instead consider a filtration of theories to reach a gapped bulk in 𝐷 =𝑑 + 𝑚 dimensions. Overall, this leads us to a nested structure of relative symmetry theories which descend to coupled edge modes, with the original QFT degrees of freedom localized at a corner of this 𝐷-dimensional bulk system. We present a bottom-up characterization of this structure and also show how it naturally arises in a number of string-based constructions of QFTs with both finite and continuous symmetries.

M-theory↗
DOE OSTI2022

A Macroalgal Cultivation Modeling System (MACMODS): Evaluating the Role of Physical-Biological Coupling on Nutrients and Farm Yield

Offshore aquaculture has the potential to expand the macroalgal industry. However, moving into deeper waters requires suspended structures that will present novel farm-environment interactions. Here, we present a computational modeling framework, the Macroalgal Cultivation Modeling System (MACMODS), to explore within-farm modifications to light, seawater flow, and nutrient fields across time and space scales relevant to macroalgae. A regional ocean model informs the site-specific setting, the Santa Barbara Channel in the Southern California Bight. A fine-scale hydrodynamic model predicts modified flows and turbulent mixing within the farm. A spatially resolved macroalgal growth model, parameterized for giant kelp, Macrocystis pyrifera , predicts kelp biomass. Key findings from model integration are that regional ocean conditions set overall farm performance, while fine-scale within-farm circulation and nutrient delivery are important to resolve variation in within-farm macroalgal performance. Therefore, we conclude that models resolving within-farm dynamics can provide benefit to farmers with insight on how farm design and regional ocean conditions interact to influence overall yield. Here, the presence of repeating longlines aligned with the mean current generate flow diversions around the farm as well as attached Langmuir circulations and increased turbulence intensity. These flow-induced phenomena lead to less biomass in the interior portion of the farm relative to the edges. We also find that there is an effluent “footprint” that extends as much as 20 km beyond the farm. In this regard, MACMODS can be used to not only evaluate farm design and cultivation practices that maximize yield but also explore interactions between the farm and ecosystem in order to minimize impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Graph-based machine learning improves just-in-time defect prediction

The increasing complexity of today’s software requires the contribution of thousands of developers. This complex collaboration structure makes developers more likely to introduce defect-prone changes that lead to software faults. Determining when these defect-prone changes are introduced has proven challenging, and using traditional machine learning (ML) methods to make these determinations seems to have reached a plateau. In this work, we build contribution graphs consisting of developers and source files to capture the nuanced complexity of changes required to build software. By leveraging these contribution graphs, our research shows the potential of using graph-based ML to improve Just-In-Time (JIT) defect prediction. We hypothesize that features extracted from the contribution graphs may be better predictors of defect-prone changes than intrinsic features derived from software characteristics. We corroborate our hypothesis using graph-based ML for classifying edges that represent defect-prone changes. This new framing of the JIT defect prediction problem leads to remarkably better results. We test our approach on 14 open-source projects and show that our best model can predict whether or not a code change will lead to a defect with an F1 score as high as 77.55% and a Matthews correlation coefficient (MCC) as high as 53.16%. This represents a 152% higher F1 score and a 3% higher MCC over the state-of-the-art JIT defect prediction. We describe limitations, open challenges, and how this method can be used for operational JIT defect prediction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

X-ray spectroscopic identification of strain and structure-based resonances in a series of saturated carbon-cage molecules: Adamantane, twistane, octahedrane, and cubane

Novel nanocarbons such as fullerenes, nanotubes, graphene, and nanodiamond reside at the cutting edge of nanoscience and technology. Along with chemical functionalization, geometric constraints (such as extreme curvature in nanotubes or defects within or at the surfaces of diamond nanoparticles) significantly alter the electronic states of the nanocarbon material. Understanding the effects of steric strain on the electronic structure is critical to developing nanoelectronic applications based on these materials. This paper presents a fundamental study of how strain affects the electronic structure in a benchmark series of some fundamental saturated carbon cage compounds. Adamantane, C10H16, the smallest diamondoid and arguably the smallest nanodiamond crystallite, has carbon atoms essentially commensurate with diamond lattice positions and possesses by far the least molecular strain of this series. Twistane also is a C10H16 isomer but the fixed cyclohexane twist conformation of the central ring introduces additional strain into the cage. Octahedrane [(CH)12] and cubane [(CH)8] are considerably more strained, culminating in cubane where carbon–carbon bonds lie either parallel or orthogonal to one another. Using gas-phase near-edge x-ray absorption fine structure spectroscopy to probe the unoccupied electronic states, we observe two major progressions across this series. First, a broad C–C σ* resonance in the absorption splits into two more narrow and intense resonances with increasing strain. Second, the first manifold of states previously associated with tertiary C–H σ* in the diamondoid series appears to broaden and shift to lower energy. This feature is more than twice as intense in cubane than in octahedrane, even though these two molecules have only tertiary carbons, with the chemical formula (CH)x. The spectral differences are entirely due to the shape of the molecules; in particular, in cubane, the features arise from a high degree of p-p interaction between parallel C–C bonds. In contrast to the conventional wisdom that near-edge x-ray absorption is primarily an atomically localized spectroscopy, molecular shape and associated strain lead to the dominant features in spectra acquired from this fundamental series of carbon cage structures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Deciphering the Oxygen Absorption Pre-edge: A Caveat on its Application for Probing Oxygen Redox Reactions in Batteries

The pre-edges of oxygen-K X-ray absorption spectra have been ubiquitous in transition metal (TM) oxide studies in various fields, especially on the fervent topic of oxygen redox states in battery electrodes. However, critical debates remain on the use of the O-K pre-edge variations upon electrochemical cycling as evidences of oxygen redox reactions, which has been a popular practice in the battery field. This study presents an investigation of the O-K pre-edge of 55 oxides covering all 3d TMs with different elements, structures, and electrochemical states through combined experimental and theoretical analyses. It is shown unambiguously that the O-K pre-edge variation in battery cathodes is dominated by changing TM-d states. Furthermore, the pre-edge enables a unique opportunity to project the lowest unoccupied TM-d states onto one common energy window, leading to a summary map of the relative energy positions of the low-lying TM states, with higher TM oxidation states at lower energies, corresponding to higher electrochemical potentials. The results naturally clarify some unusual redox reactions, such as Cr 3+/6+ . This work provides a critical clarification on O-K pre-edge interpretation and more importantly a benchmark database of O-K pre-edge for characterizing redox reactions in batteries and other energy materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multiobjective Dynamic Optimization for Optimal Load-Following of Natural Gas Combined Cycle Power Plants under Stress Constraints

With the increasing penetration of intermittent renewable energy sources into the electric grid, there is an associated need for conventional thermal power plants that are designed to operate at base-load conditions to cycle their load rapidly and frequently and operate under low-load conditions. Fast load-following operations lead to plant efficiency loss and the reduction of equipment life. A high-fidelity dynamic model of a natural gas combined cycle power plant, with rigorous equipment level submodels, is developed to capture the plant transient performance and the thermomechanical stress evolution at the high-pressure drum is computed to assess the drum life consumption. Stress evolution is modeled for the location of the edge at the drum/downcomer junction that experiences high circumferential stress amplitude during the fast load-following operation, leading to higher fatigue damage than locations considered under existing design standards. A dynamic optimization problem is solved for optimal load-following operation. Depending on the value of the stress constraint and the desired ramp rate, satisfying the desired stress constraint may be infeasible without relaxing the ramp rate. A multiobjective dynamic optimization problem is solved using a lexicographic approach that minimizes ramp rate relaxation and maximizes efficiency while satisfying stress constraints, avoiding spraying to saturation, and maintaining main steam and reheat steam temperature within bounds. It was observed that the optimal ramp rate can be highly nonlinear as opposed to the industry-standard linear ramp rate. Nonlinear optimal ramp-rate profiles not only help to avoid stress constraints that may be unavoidable by using the linear profile but also result in higher efficiency than the linear profile. Furthermore, the study shows that there is a strong tradeoff between the relaxation in the plant ramp rate and the time-average thermal efficiency.

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

Carbon Mineralization of Sulfate Wastes Containing Pb: Synchrotron Pb M3-Edge XANES Analysis of Simultaneous Heavy Metal and Carbon Sequestration

Sulfate wastes are produced in large quantities and contain toxic heavy metals such as lead (Pb), posing environmental risks. Because of favorable solubility differences, these wastes can be repurposed for engineered carbon dioxide (CO 2 ) sequestration. Understanding the fate and mobility of heavy metals during this process is important. This study focuses on Pb and the effect of zinc (Zn) on Pb in carbon mineralization. Synthesized gypsum was treated with a carbonate-rich solution at pH 11.5 to convert the sulfates to carbonates. Aqueous solutions and mineral solids were analyzed. Synchrotron-based micro-X-ray fluorescence and a novel application of Pb M3-edge X-ray absorption near-edge structure provided detailed insights into Pb distribution and mineral forms. Results showed significant reductions in aqueous Pb and Zn concentrations, indicating effective metal sequestration. Carbon mineralization transformed Pb from soluble anglesite (PbSO 4 ) into insoluble cerussite (PbCO 3 ) and hydrocerussite (Pb 3 (CO 3 ) 2 (OH) 2 ). Pb primarily precipitated onto calcium carbonate surfaces through surface-mediated precipitation reactions. While the presence of Zn modified crystallization dynamics, it did not impede Pb sequestration and potentially enhanced surface reactivity, facilitating greater Pb immobilization. These findings highlight carbon mineralization as a sustainable approach to immobilize toxic metals in sulfate wastes while advancing CO 2 sequestration efforts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Potential design problems for ITER fusion device

The international thermonuclear experimental reactor (ITER) is a worldwide project currently being built in France for the demonstration of the feasibility of thermonuclear technologies for future realization of successful commercial fusion energy. ITER is of the tokamak based design using strong magnetic fields to confine the very hot plasma needed to induce the fusion reaction. Tokamak devices are currently the front leading designs. Building a successful magnetic fusion device for energy production is of great challenge. A key obstacle to such design is the performance during abnormal events including plasma disruptions and so-called edge-localized modes (ELMs). In these events, a massive and sudden release of energy occurs quickly, due to loss of full or partial plasma confinement, leading to very high transient power loads on the reactor surface boundaries. A successful reactor design should tolerate several of these transient events without serious damages such as melting and vaporization of the structure. This paper highlights, through comprehensive state-of-the-art computer simulation of the entire ITER interior design during such transient events, e.g., ELMs occurring at normal operation and disruptions during abnormal operation, potential serious problems with current plasma facing components (PFCs) design. The HEIGHTS computer package is used in these simulations. The ITER reactor design was simulated in full and exact 3D geometry including all known relevant physical processes involved during these transient events. The current ITER divertor design may not work properly and may requires significant modifications or new innovative design to prevent serious damage and to ensure successful operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Free-Energy Landscapes and Surface Dynamics in Methane Activation on Ni(511) via Machine Learning and Enhanced Sampling

Methane activation on stepped Ni(511) surfaces involves the rearrangement of surface atoms as the chemical reaction proceeds. This process is particularly sensitive to temperature. Using machine-learned interatomic potentials (MLIPs) coupled with enhanced sampling techniques, we investigate the activation of methane under realistic operando conditions. Our analysis reveals that methane dissociation occurs predominantly at step-edge nickel atoms. As CH x (where x = 3 or 4) species bind to additional surface nickel atoms, their reduced mobility leads to entropic penalties that suppress certain configurations and transition states. This is reflected in the underlying free energy surfaces, where configurations such as methyl binding to hollow sites and activation routes involving two nickel atoms become unfavorable as temperature increases. At elevated temperatures, methane activation extends from step-edge sites to terrace regions because of reduced free-energy barriers and enhanced surface dynamics. By decomposing the free-energy into enthalpic and entropic contributions, we uncover temperature-dependent shifts in the preferences of methane for the relevant active sites and arrive at a detailed molecular picture of methane activation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Site‐Specific Reduction‐Induced Hydrogenation of a Helical Bilayer Nanographene with K and Rb Metals: Electron Multiaddition and Selective Rb + Complexation

Abstract The chemical reduction of π‐conjugated bilayer nanographene 1 (C 138 H 120 ) with K and Rb in the presence of 18‐crown‐6 affords [K + (18‐crown‐6)(THF) 2 ][{K + (18‐crown‐6)} 2 (THF) 0.5 ][C 138 H 122 3− ] ( 2 ) and [Rb + (18‐crown‐6) 2 ][{Rb + (18‐crown‐6)} 2 (C 138 H 122 3− )] ( 3 ). Whereas K + cations are fully solvent‐separated from the trianionic core thus affording a “naked” 1 .3 − anion, Rb + cations are coordinated to the negatively charged layers of 1 .3 − . According to DFT calculations, the localization of the first two electrons in the helicene moiety leads to an unprecedented site‐specific hydrogenation process at the carbon atoms located on the edge of the helicene backbone. This uncommon reduction‐induced site‐specific hydrogenation provokes dramatic changes in the (electronic) structure of 1 as the helicene backbone becomes more compressed and twisted upon chemical reduction, which results in a clear slippage of the bilayers.

Zhou, Zheng↗
DOE OSTI2021

Site‐Specific Reduction‐Induced Hydrogenation of a Helical Bilayer Nanographene with K and Rb Metals: Electron Multiaddition and Selective Rb + Complexation

Abstract The chemical reduction of π‐conjugated bilayer nanographene 1 (C 138 H 120 ) with K and Rb in the presence of 18‐crown‐6 affords [K + (18‐crown‐6)(THF) 2 ][{K + (18‐crown‐6)} 2 (THF) 0.5 ][C 138 H 122 3− ] ( 2 ) and [Rb + (18‐crown‐6) 2 ][{Rb + (18‐crown‐6)} 2 (C 138 H 122 3− )] ( 3 ). Whereas K + cations are fully solvent‐separated from the trianionic core thus affording a “naked” 1 .3 − anion, Rb + cations are coordinated to the negatively charged layers of 1 .3 − . According to DFT calculations, the localization of the first two electrons in the helicene moiety leads to an unprecedented site‐specific hydrogenation process at the carbon atoms located on the edge of the helicene backbone. This uncommon reduction‐induced site‐specific hydrogenation provokes dramatic changes in the (electronic) structure of 1 as the helicene backbone becomes more compressed and twisted upon chemical reduction, which results in a clear slippage of the bilayers.

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

Inducing Ferrimagnetic Exchange in 1D-FeSe 2 Chains Using Heteroleptic Amine Complexes: [Fe(en)(tren)][FeSe 2 ] 2

[Fe(en)(tren)][FeSe 2 ] 2 (en = ethylenediamine, C 2 H 8 N 2 , tren = tris(2-aminoethyl)amine, C 6 H 18 N 4 ) has been synthesized by a mixed-ligand solvothermal method. Its crystal structure contains heteroleptic [Fe(en)(tren)] 2+ complexes with distorted octahedral coordination, incorporated between 1D-FeSe 2 chains composed of edge–sharing FeSe 4 tetrahedra. The twisted octahedral coordination environment of the Fe–amine complex leads to partial dimerization of Fe–Fe distances in the FeSe 2 chains so that the FeSe 4 polyhedra deviate strongly from the regular tetrahedral geometry. 57 Fe Mössbauer spectroscopy reveals oxidation states of +3 for the Fe chain atoms and +2 for the Fe complex atoms. The close proximity of Fe atoms in the chains promotes ferromagnetic nearest neighbor interactions, as indicated by a positive Weiss constant, θ = +53.8(6) K, derived from the Curie–Weiss fitting. Magnetometry and heat capacity reveal two consecutive magnetic transitions below 10 K. DFT calculations suggest that the ordering observed at 4 K is due to antiferromagnetic intrachain interactions in the 1D-FeSe 2 chains. The combination of two different ligands creates an asymmetric coordination environment that induces changes in the structure of the Fe–Se fragments. Finally, this synthetic strategy opens new ways to explore the effects of ligand field strength on the structure of both Fe-amine complexes and surrounding Fe–Se chains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Energy Funneling in a Noninteger Two-Dimensional Perovskite

Energy funneling is a phenomenon that has been exploited in optoelectronic devices based on low-dimensional materials to improve their performance. Here, we introduce a new class of two-dimensional semiconductor, characterized by multiple regions of varying thickness in a single confined nanostructure with homogeneous composition. This "noninteger 2D semiconductor" was prepared via the structural transformation of two-octahedron-layer-thick (n = 2) 2D cesium lead bromide perovskite nanosheets; it consisted of a central n = 2 region surrounded by edge-lying n = 3 regions, as imaged by electron microscopy. Thicker noninteger 2D CsPbBr 3 nanostructures were obtained as well. Finally, these noninteger 2D perovskites formed a laterally coupled quantum well band alignment with virtually no strain at the interface and no dielectric barrier, across which unprecedented intramaterial funneling of the photoexcitation energy was observed from the thin to the thick regions using time-resolved absorption and photoluminescence spectroscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Impact of n -Butylammonium Bromide on the Chemical and Electronic Structure of Double-Cation Perovskite Thin Films

2D/3D perovskite heterostructures have emerged as a promising material composition to reduce nonradiative recombination in perovskite-based LEDs and solar cells. Such heterostructures can be created by a surface treatment with large organic cations, for example, n-butylammonium bromide (BABr). To understand the impact of the BABr surface treatment on the double-cation (Cs 0.17 FA 0.83 Pb(I 0.6 Br 0.4 ) 3 ) (FA = formamidinium) perovskite thin film and further optimize the corresponding structures, an in-depth understanding of the chemical and electronic properties of the involved surfaces, interfaces, and bulk is required. We study the impact of the BABr treatment with a combination of surface-sensitive X-ray photoelectron spectroscopy and bulk-sensitive resonant inelastic soft X-ray scattering (RIXS). A quantitative analysis of the BABr-treated perovskite thin film shows a modified chemical perovskite surface environment of carbon, nitrogen, bromine, iodine, and lead, indicating that the treatment leads to a perovskite surface with a modified composition and bonding structure. With K-edge RIXS, the local environment at the nitrogen and carbon atoms is probed, allowing us to identify the presence of BABr in the perovskite bulk albeit with a modified bonding environment. This, in turn, identifies a "hidden parameter" for the optimization of the BABr treatment and overall performance of 2D/3D perovskite solar cell absorbers.

2D/3D perovskite heterostructure↗
DOE OSTI2025

Probabilistic Diffusion Models Advance Extreme Flood Forecasting

Extreme floods pose escalating risks in a changing climate, yet forecasting remains challenging due to peak flow underestimation and high uncertainty. We introduce diffusion-based runoff model (DRUM), a probabilistic deep learning (DL) approach that advances extreme flood forecasting across representative basins in the contiguous United States. DRUM outperforms state-of-the-art benchmarks, enhancing nowcasting skill for the top 1‰ of flows in 72.3% of studied basins. Under operational scenarios, DRUM extends reliable lead times by nearly a full day for 20- and 50-year floods. When evaluated with measured precipitation, an ideal condition, recall improves by 0.3–0.4 and the early warning window extends by 2.3 days for 50-year floods. The enhancement potential varies regionally, with precipitation-driven flood zones in the eastern and northwestern US benefiting most, gaining 3–7 days in lead time. These findings highlight the transformative potential of diffusion models as a cutting-edge generative AI technique for advancing hydrology and broader Earth system sciences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Elimination of detrimental grain boundary segregation in garnets

Garnet Li 7 La 3 Zr 2 O 12 electrolyte is considered a key enabler of solid-state batteries with Li metal electrodes, but the grain boundaries impair its performance. To date, the understanding of grain boundary structures and its impact on performance remains elusive. Here, we show that element segregation at Li 7 La 3 Zr 2 O 12 grain boundaries critically governs Li transport and nucleation. During conventional sintering, Al, Ta, and La segregate at grain boundaries, locally depleting Li and creating space-charge layers that lower total ionic conductivity. Simultaneously, this segregation leads to higher electronic conductivity along grain boundaries, which promotes Li nucleation at grain boundary edges with increased risk of dendrite formation. The underlying mechanism of segregation is governed by both thermodynamic driving forces and diffusion kinetics. Building on this understanding, we develop a strategy to achieve segregation-free grain boundaries through a rapid sintering protocol that utilizes the onset of solid-state softening. This approach yields transparent, polycrystalline Li 7 La 3 Zr 2 O 12 with negligible grain boundary impedance and enhanced dendrite tolerance. By elucidating the structural origins and electrochemical consequences of grain boundary segregation, this work provides a guidance for the rational optimization of solid electrolytes.

Energy - Storage↗
DOE OSTI2023

Covalent organic frameworks in heterogeneous catalysis: recent advances and future perspective

Catalysis is ubiquitous in ~90% of chemical manufacturing processes and contributes up to 35% of global GDP. Hence, the development of advanced catalytic systems is of utmost importance for academia, industry, and government. Covalent organic frameworks (COFs) are a rapidly emerging class of crystalline porous materials that precisely integrate organic monomer units into extended periodic networks, offering a propitious platform for heterogeneous catalysis due to salient structural merits of ultralow density, high crystallinity, permanent porosity, structural tunability, functional diversity, and synthetic versatility. The past decade has witnessed an upsurge of interest in COFs for heterogeneous catalysis and this trend is expected to continue. In this review, we briefly introduce COF chemistry concerning the design principles, growth mechanism, and cutting-edge advances in structural evolution, linkage chemistry, and facile synthesis. Further, we then scrutinize four leading design strategies for COF catalysts, namely pristine COFs with catalytically active backbones, COFs as hosts for the inclusion of catalytic species, COF-based heterostructures, and COF-derived carbons for thermo-, photo-, and electrocatalysis. Next, we overview the most recent advances (mainly from 2020 to 2023) of COFs in heterogeneous catalysis, along with their fundamentals and advantages. Finally, we outline the current challenges and offer our perspectives on the future directions of COFs for heterogeneous catalysis.

36 MATERIALS SCIENCE↗