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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Crystal mechanics-based thermo-elastic constitutive modeling of orthorhombic uranium using generalized spherical harmonics and first-order bounding theories

In earlier works, a mathematical procedure for invertible microstructure-property linkages was developed using computationally efficient spectral methods for polycrystalline cubic and hexagonal metals. This paper formulates such invertible microstructure–property linkages for orthorhombic polycrystalline metals relying on the generalized spherical harmonics (GSH) spectral basis. The procedure is used to compute property closures of orthorhombic polycrystals. The closures represent the complete set of theoretically possible combinations of effective properties for a selected material. The procedure relies on the first-order bounding theories and considers orientation distribution functions (ODFs) as the main microstructural descriptor influencing homogenized properties. Numerous examples of these closures involving second-rank thermal expansion and fourth-rank elastic stiffness tensorial properties over a broad range of temperatures are presented for α-uranium (α-U). In doing so, certain key properties of these closures are exploited to facilitate their computation with drastically reduced computational effort. Along with the recently developed GSH-based interpolation procedure for ODFs from coarsely spaced experimental measurement grids to finely spaced finite element mesh resolution grids presented in Barrett et al., the developed computationally efficient ODF-effective property linkages are used to establish a crystal mechanics-based simulation framework coupled with the finite element method (FEM). The ODF dependent thermal expansion and elastic stiffness tensors are efficiently calculated at every integration point and used by the FEM to predict the overall distortion of a hemispherical part made of α-U during heating. In conclusion, it is shown that the developed framework can be used to simulate microstructurally heterogeneous components under thermo-mechanical loadings in a computationally efficient manner.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Flexible all-organic nanocomposite films interlayered with in situ synthesized covalent organic frameworks for electrostatic energy storage

Poly(vinylidene fluoride)-based terpolymers, known for having the largest dielectric constant among the existing dielectric polymers, are attractive materials for electrostatic film capacitors used in lightweight electrification systems. However, the potential of these terpolymers in film capacitor applications remains constrained by their low electrical insulating and mechanical strengths. To address these limitations, we introduced rigid covalent organic framework (COF) nanospheres into the thin films of soft terpolymers via in situ synthesis and a facile layer-by-layer solution casting method, whereby multilayer films consisting of two polymer outer layers and a COF-containing middle layer were readily obtained. The resultant all-organic thin films exhibit simultaneously high dielectric constant, enhanced breakdown strength, superior energy density (~25 J cm –3 ) at efficiencies over 80%, along with greatly improved mechanical self-supporting capability and excellent mechanical flexibility. Here, this work demonstrates the unprecedented use of COF for electrostatic energy storage, uncovering its potential for flexible electronic applications operating under high electric fields.

25 ENERGY STORAGE↗
DOE OSTI2025

Pultrusion and Vitrimer Composites: Emerging Pathways for Sustainable Structural Materials

Pultrusion is a manufacturing process used to produce fiber-reinforced polymer composites with excellent mechanical, thermal, and chemical properties. The resulting materials are lightweight, durable, and corrosion-resistant, making them valuable in aerospace, automotive, construction, and energy sectors. However, conventional thermoset composites remain difficult to recycle due to their infusible and insoluble cross-linked structure. This review explores integrating vitrimer technology a novel class of recyclable thermosets with dynamic covalent adaptive networks into the pultrusion process. As only limited studies have directly reported vitrimer pultrusion to date, this review provides a forward-looking perspective, highlighting fundamental principles, challenges, and opportunities that can guide future development of recyclable high-performance composites. Vitrimers combine the mechanical strength (tensile strength and modulus) of thermosets with the reprocessability and reshaping of thermoplastics through dynamic bond exchange mechanisms. These polymers offer high-temperature reprocessability, self-healing, and closed-loop recyclability, where recycling efficiency can be evaluated by the recovery yield retention of mechanical properties and reuse cycles meeting the demand for sustainable manufacturing. Key aspects discussed include resin formulation, fiber impregnation, curing cycles, and die design for vitrimer systems. The temperature-dependent bond exchange reactions present challenges in achieving optimal curing and strong fiber–matrix adhesion. Recent studies indicate that vitrimer-based composites can maintain structural integrity while enabling recycling and repair, with mechanical performance such as flexural and tensile strength comparable to conventional composites. Incorporating vitrimer materials into pultrusion could enable high-performance, lightweight products for a circular economy. The remaining challenges include optimizing curing kinetics, improving interfacial adhesion, and scaling production for widespread industrial adoption.

Fiber composites↗
DOE OSTI2020

Resilient Autonomous Wind Farms: Preprint

With the advent of an increasing number of control strategies that seek to optimize wind turbine performance on a farm-level, taking account of individual wind turbine information to achieve wind farm-level objectives has become an increasingly important goal. Methods for controlling wind turbines on an individual and farm level have seen significant development, and an abundance of new implementations for gathering and using data from turbines have created potential for novel control mechanisms which can further optimize the performance and delivery characteristics of a wind farm. A key element of making these wind farms more efficient is to develop reliable algorithms that use local sensor information that is already being collected, such as supervisory control and data acquisition (SCADA) data, local meteorological stations, and nearby radars/sodars/lidars. Making use of information from all wind turbines in a wind farm can enable such approaches as determining the atmospheric conditions across the farm, improving fault-finding, and enabling more efficient overall control of farm-wide optimizations through mechanisms such as wake-steering. However, these approaches typically involve a centralized communications and control center. In order to ensure the resilient operation of the farm, it is necessary to develop an approach which distributes the calculation and communication amongst multiple nodes throughout the farm. In this fashion, a redundant, robust, and secure network can be created, which can tolerate faults in calculation, communication, and even external attacks which seek to disrupt the operation of the wind farm. This paper introduces the use of the Raft Byzantine Fault Tolerance algorithm in the implementation of autonomous control of a wind farm. This implementation will allow for fault tolerance for malfunctioning nodes, sensors, transmitters, and connectors. This approach is equally extensible to account for malicious actors. It will be shown to achieve overall consensus, provided the number of faults/malicious nodes is less than 3$n$+1, where $n$ is the number of turbine cluster faults which may occur, and to be robust in the face of multiple arbitrary faults.

autonomous↗
DOE OSTI2025

High and Ultra-High Temperature Reaction Kinetics by Single Nanoparticle Mass Spectrometry

Methodology is presented for non-destructive, optically-detected single nanoparticle (NP) mass spectrometry, with the goal of extracting surface reaction kinetics for single NPs at high temperatures. Methods for determining the NP charge, mass, and temperature as a function of time are discussed, and the data are used to extract both the absolute kinetics for mass change, as well as the efficiencies of the surface processes that cause them. Factors that contribute to the uncertainties in absolute and relative mass determination, and in the resulting kinetic parameters, are discussed. The method allows the NP-to-NP variations in initial reactivity to be measured directly, along with the time evolution of reactivity resulting from NP structural/compositional changes that occur under reaction conditions. The strengths and limitations of single nanoparticle mass spectrometry as a high temperature surface kinetics tool are discussed in the context of sublimation and O2 oxidation kinetics experiments for single hafnium (Hf) NPs at temperatures ranging above 2400 K. The Hf oxidation kinetics are compared to analogous oxidation experiments for silicon, graphite, and carbon black NPs. In all four cases, the oxidation chemistry was dominated by processes that result in net mass loss, and the distinct mechanisms responsible are discussed. All four NPs also eventually passivated, i.e., the efficiencies for oxidative etching decreased by at least two orders of magnitude, relative to the initial efficiencies. Furthermore, the passivation mechanisms, which are quite different for carbon, compared to silicon or hafnium, are discussed. Carbon NP passivation is attributed to structural isomerization leading to fully coordinated, fullerene-like NP surfaces, while for silicon and hafnium, passivation results from delayed formation of an oxide layer, triggered by accumulation of oxygen in the NP sub-surface region.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Glassoformer: A Query-Sparse Transformer for Post-Fault Power Grid Voltage Prediction

Here, we propose GLassoformer, a novel and efficient transformer architecture leveraging group Lasso regularization to reduce the number of queries of the standard self-attention mechanism. Due to the sparsified queries, GLassoformer is more computationally efficient than the standard transformers. On the power grid post-fault voltage prediction task, GLasso-former shows remarkably better prediction than many existing benchmark algorithms in terms of accuracy and stability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Flexible Zn-MOF with Rare Underlying scu Topology for Effective Separation of C6 Alkane Isomers

Adsorptive separation by porous solids provides an energy-efficient alternative for the purification of important chemical species compared to energy-intensive distillations. Particularly, the separation of linear hexane isomers from its branched counterparts is crucial to produce premium grade gasoline with high research octane number (RON). Herein, we report the synthesis of a new, flexible zinc-based metal-organic framework, [Zn 5 (μ 3 -OH) 2 (adtb) 2 (H 2 O) 5 ·5 DMA] (Zn-adtb), constructed from a butterfly shaped carboxylate linker with underlying (4,8)-connected scu topology capable of separating the C6 isomers nHEX, 3MP, and 23DMB. The sorbate-sorbent interactions and separation mechanisms were investigated and analyzed through in situ FTIR, solid state NMR measurements and computational modeling. Here these studies reveal that Zn-adtb discriminates the nHEX/3MP isomer pair through a kinetic separation mechanism and the nHEX/23DMB isomer pair through a molecular sieving mechanism. Column breakthrough measurements further demonstrate the efficient separation of linear nHEX from the mono- and dibranched isomers.

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

The AGORA High-Resolution Galaxy Simulations Comparison Project

Context. Satellite galaxies experience multiple physical processes when interacting with their host halos, often leading to the quenching of star formation. In the Local Group, satellite quenching has been shown to be highly efficient, affecting nearly all satellites except the most massive ones. While recent surveys study Milky Way-analogs to assess how representative our Local Group is, the dominant physical mechanisms behind satellite quenching in Milky Way-mass halos remain under debate. Aims. We analyze satellite quenching within the same Milky Way-mass halo simulated using various widely used astrophysical codes, each using different hydrodynamic methods and implementing different supernovae feedback recipes. The goal is to determine whether quenched fractions, quenching timescales, and the dominant quenching mechanisms are consistent across codes or if they show sensitivity to the specific hydrodynamic method and supernovae feedback physics employed. Methods. We used a subset of high-resolution cosmological zoom-in simulations of a Milky Way-mass halo from the multiple-code AGORA CosmoRun suite. Our analysis focuses on comparing satellite quenching across the different models and against observational data. We also analyzed the dominant mechanisms driving satellite quenching in each model. Results. We find that the quenched fraction is consistent with the latest SAGA Survey results within its 1σ host-to-host scatter across all the models. Regarding quenching timescales, all the models reproduce the trend observed in the ELVES survey, Local Group observations, and previous simulations: The less massive the satellite, the shorter its quenching timescale. All of our models converge on the dominant quenching mechanisms: Strangulation halts cold gas accretion in all satellites, while ram pressure stripping is the predominant mechanism for gas removal, and it is particularly effective in satellites with M * <10 8 M ⊙ . Nevertheless, the efficiency of the stripping mechanisms differs among the codes, showing a strong sensitivity to the different supernovae feedback implementations and/or hydrodynamic methods employed.

Local Group↗
DOE OSTI2020

Advances in Singlet Fission Chromophore Design Enabled by Vibrational Spectroscopies

Singlet fission leads to the formation of two separate triplet T 1 excitons from an initial singlet S1 exciton through 1 (TT) and 1 (T...T), multiexcitonic intermediates that retain singlet character. Its ability to achieve external quantum efficiencies higher than 100% made it an attractive candidate for optoelectronic device applications. However, singlet fission has not been applied widely despite having been investigated by a myriad of spectroscopic methods, in part due to our poor understanding of how to optimize molecular structure and packing in chromophores well-suited to large-scale production. Vibrational spectroscopies provide a solution, because they directly probe nuclear motions, allowing us to monitor evolving structural changes in molecules undergoing singlet fission, thus providing us with roadmaps to design molecules suitable for optoelectronic applications. Furthermore, this Perspective reviews the contributions and analyzes the future directions of vibrational spectroscopies to the advancement in our knowledge about the mechanisms and rational designing of chromophores undergoing efficient singlet fission.

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

Machine learning for photovoltaic single axis tracker fault detection and classification

More than 81% of the annual capacity of utility-scale photovoltaic (PV) power plants in the U.S. use single-axis trackers (SATs) due to SATs delivering 4% in capacity factor on average over fixed-array systems. However, SATs are subject to faults, such as software misconfigurations and mechanical failures, resulting in suboptimal tracking. If left undetected, the overall power yield of the PV power plant is reduced significantly. Minimizing downtime and ensuring efficient operation of SATs requires robust detection and diagnosis mechanisms for SAT faults. We present a machine learning framework for implementing real-time SAT fault detection and classification. Our implementation of the proposed framework reliably identifies measurements taken from a test PV system undergoing emulated SAT faults relative to state-of-the-art algorithms and produces nearly zero false positives on our testing days. Code and data are available at https://pvpmc.sandia.gov/tools.

Fault classification↗
DOE OSTI2021

Bacterial Efflux Pumps and Their Inhibitors

Bacterial multidrug efflux transporters have distinct molecular features and mechanisms that enable their impressive substrate polyspecificity. These transporters are involved in all physiological processes where nonspecific but active transport across membranes is critical for survival and proliferation. Importantly, efflux pumps contribute to bacterial virulence and pathogenesis, as well as the spread of antibiotic resistance in clinics. Transporters belonging to several protein superfamilies have been selected for polyspecificity by evolution and augmented with accessory proteins that extend and couple transport reactions across the inner and outer membranes of the bacterium. As a result, bacteria are equipped with diverse efflux machines that protect cells from a broad variety of toxic compounds including antibiotics and other small molecule therapeutics. The inhibition of such polyspecific biomolecular machines is a challenging task, which still awaits an efficient solution. Here, we review the molecular mechanisms of efflux pumps from Gram-negative bacteria and recent advances and challenges associated with the discovery of effective inhibitors of these pumps.

Zgurskaya, Helen↗
DOE OSTI2024

Mechanism-Guided Kinetic Analysis of Electrocatalytic Proton Reduction Mediated by a Cobalt Catalyst Bearing a Pendant Basic Site

Cobalt polypyridyl complexes stand out as efficient catalysts for electrochemical proton reduction, but investigations into their operating mechanisms, with broad-reaching implications in catalyst design, have been limited. Herein, we investigate the catalytic activity of a cobalt(II) polypyridyl complex bearing a pendant pyridyl base with a series of organic acids spanning 20 pKa units in acetonitrile. Structural analysis, as well as electrochemical studies, reveals that the Co(III) hydride intermediate is formed through reduction of the Co(II) catalyst followed by direct metal protonation in the initial EC step despite the presence of the pendant base, which is commonly thought of as a more kinetically accessible protonation site. Protonation of the pendant base occurs after the Co(III) hydride intermediate is further reduced in the overall ECEC pathway. Additionally, when the acid used is sufficiently strong, the Co(II) catalyst can be protonated, and the Co(III) hydride can react directly with acid to release H 2 . With thorough mechanistic understanding, the appropriate electroanalytical methods were identified to extract rate constants for the elementary steps over a range of conditions. Thermodynamic square schemes relating catalytic intermediates proposed in the three electrocatalytic HER mechanisms were constructed. Furthermore, these findings reveal a full description of the HER electrocatalysis mediated by this molecular system and provide insights into strategies to improve synthetic fuel-forming catalysts operative through metal hydride intermediates.

08 HYDROGEN↗
DOE OSTI2023

Preparation of Macroscopic Low-Density Gold Foams with Good Machinability

Uniform, macroscopic monoliths (ranging from a few millimeters to a centimeter) of low-density gold foams with ~95% porosity and ~10-μm-diameter pores were prepared by the casting of gold-coated polystyrene core-shell particles followed by the thermal removal of the polymer core. The Au foams were composed of unique hollow gold spheres and showed superior mechanical integrity and resilience compared to the foams we previously reported. Highly efficient seeding and electroless gold-plating methods in this study caused a significant morphological transition in the gold coatings from coarse particles to fine particles, and finally, to a continuous layer. A modified, scalable casting approach to form large uniform monoliths (up to ~1-cm diameter) and a gentle baking condition to minimize undesirable densification of the final foams enabled us to develop a simple, efficient synthetic route to nanostructured macroscopic low-density gold foams. To demonstrate the improved mechanical stability and machinability, a representative monolithic Au foam (~0.9 g/cm 3 ) was carefully cut into the hollow cylinder of gold foams by a series of machining and processing steps. Finally, we tried to understand the unique mechanical behaviors and properties of this gold foam by nanoindentation measurement.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Impact of the LiPF6 Concentration on the Interfacial Charge Transfer and Fast-charging Capabilities of Lithium-Ion Batteries

Fast-charging lithium-ion batteries (LIB) demand optimized electrolyte formulations to balance ionic conductivity, viscosity, and interfacial charge transfer kinetics. This study examines how LiPF 6 concentration shapes solvation structure, desolvation energy, charge transfer activation energy, and solid electrolyte interphase (SEI) properties, which are critical for fast-charging performance. Using Raman spectroscopy, electrochemical cycling, X-ray photoelectron spectroscopy, and atomistic modeling, we analyze how varying LiPF 6 concentrations impact interfacial and bulk transport properties. Our findings show that increasing LiPF 6 concentration alters lithium solvation structures, reduces desolvation energy, and accelerates charge transfer at the electrode interface. Higher concentrations lower the activation energy for charge transfer and suppress excessive SEI growth, improving interfacial kinetics. However, concentrations above a certain threshold increase viscosity and reduce ionic conductivity, limiting transport efficiency. These results offer insights into electrolyte solvation and interfacial charge transfer mechanisms, providing guidelines for designing next-generation fast-charging LIB electrolytes with enhanced efficiency, stability, and longevity.

Son, Seoung-Bum [Argonne National Laboratory (ANL)↗
DOE OSTI2020

Anisotropic Dynamics and Mechanics of Macromolecular Crystals Containing Lattice-Patterned Polymer Networks

The mechanical and functional properties of many crystalline materials depend on cooperative changes in lattice arrangements in response to external perturbations. However, the flexibility and adaptiveness of crystalline materials are limited. Additionally, the bottom-up, molecular-level design of crystals with desired dynamic and mechanical properties at the macroscopic level remains a considerable challenge. To address these challenges, we had previously integrated mesoporous, cubic ferritin crystals with hydrogel networks, resulting in hybrid materials (polymer integrated crystals or PIX) which could undergo dramatic structural changes while maintaining crystalline periodicity and display efficient self-healing. Here, the dynamics and mechanics of these ferritin-PIX were devoid of directionality, which is an important attribute of many molecular and macroscopic materials/devices. In this study, we report that such directionality can be achieved through the use of ferritin crystals with anisotropic symmetries (rhombohedral or trigonal), which enable the templated formation of patterned hydrogel networks in crystallo. The resulting PIX expand and contract anisotropically without losing crystallinity, undergo prompt bending motions in response to stimuli, and self-heal efficiently, capturing some of the essential features of sophisticated biological devices like skeletal muscles.

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

Developing reliable machine learning interatomic potential for Fe–Cr–Ni austenitic alloys

Gaining atomistic understanding of mechanical behavior of heat-resistant structural materials such as Fe–Cr–Ni-based alloys requires an approach with an accuracy close to density functional theory (DFT) that considers the intrinsic properties of the bulk lattice and important defects such as stacking faults, grain boundaries, and surfaces. This work aims to develop reliable machine learning interatomic potential (MLIAP) at cross-scale for Fe–Cr–Ni ternary alloys with a focus on the face-centered-cubic (fcc) solid solution structure. Leveraging the advantages of moment tensor potentials, which typically necessitate a relatively small training dataset and enable rapid calculations using the large-scale atomic/molecular massively parallel simulator package, we ensure the stability and accuracy of the trained potentials. Important defects such as stacking faults, grain boundaries, and surfaces for wide-range compositions are investigated. Structural, thermal, elastic, and defect properties are determined from molecular dynamics simulations comprising several thousand atoms, generated via canonical Monte Carlo simulations guided by the trained potential. The trained potential allows efficient atomic simulations of structural, thermal, and mechanical properties of fcc Fe–Cr–Ni solid solution alloys as a function of composition and temperature. Therefore, the MLIAP approach represents a major advancement from DFT calculations that are limited to small simulation sizes and traditional molecular dynamics simulations using relatively low accuracy potentials. Furthermore, this work outlines a practical foundation for further investigating the structural evolution and mechanical behavior of austenitic stainless steel and nickel-based alloys in a wide array of applications in extreme environments.

Crystal structure↗
DOE OSTI2026

Impacts of Pasture Conversion to Sugarcane on Water Fluxes and Water Use Efficiency in the Southeastern US

The expansion of sugarcane (cane), a high-yielding perennial crop, will likely reshape the bioenergy landscape in the Southeastern US. However, its ecohydrological implications, particularly following conversion from grazed pastures, a dominant land use in the region, remain highly uncertain. We investigated the impact of cane expansion on evapotranspiration (ET) and its partitioning, and the mechanisms influencing both ET components and water use efficiency (WUE) across multiple scales and growth cycles in subtropical Florida. We combined eddy covariance, biometric measurements, and process-based stomatal conductance (g s ) models. ET was 1.7% lower in cane than in improved pasture (IMP) but exceeded that in semi-native pasture (SN) by 21%. Transpiration (T) followed a similar pattern, consistent with lower g s in cane relative to IMP. Cane had more conservative water use and greater sensitivity of g s to vapor pressure deficit (VPD) compared to IMP pasture, suggesting cane may be more tolerant of increasing atmospheric water demand. In contrast, SN showed lower g s and weaker stomatal sensitivity to VPD compared to cane, resulting in lower T. In cane, stomatal regulation and T varied across growth cycles, with stomata becoming less water conservative as stands matured, highlighting the importance of incorporating stand age-dependent stomatal regulation into hydrological models. Evaporation (E) was higher in cane than pastures (19%–26%), partially offsetting WUE gains. Cane exhibited higher intrinsic WUE (GPP/g s ; Gross Primary Productivity), ecosystem WUE (GPP/ET), and harvest WUE (harvest/ET) than both pasture types. Large-scale pasture-to-cane conversion could produce widely contrasting hydrological outcomes. The net regional impact will depend on the proportion of each pasture type converted and on cane's high g s sensitivity to VPD, which triggers tight stomatal regulation and conservative water use, both of which will become increasingly consequential under intensifying atmospheric water demand.

bioenergy↗