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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Multiband Reconfigurable Harmonically Tuned Gallium Nitride (GaN) Solid-State Power Amplifier (SSPA) for Cognitive Radios

The paper presents the architecture of a wideband reconfigurable harmonically-tuned Gallium Nitride (GaN) Solid State Power Amplifier (SSPA) for cognitive radios. When interfaced with the physical layer of a cognitive communication system, this amplifier topology offers broadband high efficiency through the use of multiple tuned input/output matching networks. This feature enables the cognitive radio to reconfigure the operating frequency without sacrificing efficiency. This paper additionally presents as a proof-of-concept the design, fabrication, and test results for a GaN inverse Class-F type amplifier operating at X-band (8.4 GHz) that achieves a maximum output power of 5.14-W, Power Added Efficiency (PAE) of 38.6 percent, and Drain Efficiency (DE) of 48.9 percent under continuous wave (CW) operation.

Cognitive↗
NASA NTRS2021

Midwest Food Security & Agriculture II: Leveraging NASA Earth Observations to Analyze and Display Crop Phenology Data and Weather Conditions to Support Expansion of Small Grain Crops in the Midwest

Agriculture in the Midwest is dominated by monoculture systems that strip the soil of nutrients, decrease yields, and worsen water quality. Crop diversification and cultivating small grains is economically and ecologically advantageous, but limited in practice due to a lack of data about small-grain crop performance as well as monoculture-favoring insurance coverage, economic incentives, and sociocultural traditions. Practical Farmers of Iowa (PFI) strives to create more sustainable agriculture and supports Midwestern farmers in adding small grains into their crop rotations. The DEVELOP team partnered with the USDA Agricultural Research Service and the USA National Phenology Network to assist PFI in applying NASA Earth observation data to track small-grain crop performance. This project developed a Google Earth Engine user interface that enables PFI farmers to compare satellite-assessed vegetation production and climatic conditions of their farm with other PFI farmers. The team assessed the crop performance through Normalized Difference Vegetation Index (NDVI) values derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI). Additionally, the team created a regression model to analyze the predictive properties of vegetation indices and crop yield, ultimately establishing a relationship with mean NDVI from the early growing season. PFI farmers can utilize these products to make informed decisions about their crop production as well as advocate for more expansive insurance policies to protect small-grain crops.

Sophie Barrowman↗
DOE OSTI2019

Biophysical Characterization of a Disabled Double Mutant of Soybean Lipoxygenase: The “Undoing” of Precise Substrate Positioning Relative to Metal Cofactor and an Identified Dynamical Network

Soybean lipoxygenase (SLO) has served as a prototype for understanding the molecular origin of enzymatic rate accelerations. The double mutant (DM) L546A/L754A is considered a dramatic outlier, due to the unprecedented size and near temperature-independence of its primary kinetic isotope effect, low catalytic efficiency, and elevated enthalpy of activation. To uncover the physical basis of these features, we herein apply three structural probes: hydrogen–deuterium exchange mass spectrometry, room-temperature X-ray crystallography and EPR spectroscopy on four SLO variants (wild-type (WT) enzyme, DM, and the two parental single mutants, L546A and L754A). DM is found to incorporate features of each parent, with the perturbation at position 546 predominantly influencing thermally activated motions that connect the active site to a protein–solvent interface, while mutation at position 754 disrupts the ligand field and solvation near the cofactor iron. However, the expanded active site in DM leads to more active site water molecules and their associated hydrogen bond network, and the individual features from L546A and L754A alone cannot explain the aggregate kinetic properties for DM. Lastly, using recently published QM/MM-derived ground-state SLO-substrate complexes for WT and DM, together with the thorough structural analyses presented herein, we propose that the impairment of DM is the combined result of a repositioning of the reactive carbon of linoleic acid substrate with regard to both the iron cofactor and a catalytically linked dynamic region of protein.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Distributed-Memory Sparse Deep Neural Network Inference Using Global Arrays

Partitioned Global Address Space (PGAS) models exhibit tremendous promise in developing efficient and productive distributed-memory parallel applications. They have been used extensively in scientific computations due to conveniently offering a ``shared-memory''-like model and convenient interfaces that separate communication with synchronization. Traditionally, PGAS communication models have been applied to dense/contiguously distributed data, but most modern applications depict varied levels of sparsity. Existing PGAS models require certain adaptations to support distributed sparse computations, since associated computations often require matrix arithmetic, in addition to data movement. The Global Arrays toolkit from Pacific Northwest National Laboratory (PNNL) is one of the earliest PGAS models to combine one-sided data communication and distributed matrix operations and is still used in the popular NWChem quantum chemistry suite. Recently, we have expanded the Global Arrays toolkit to support common sparse operations, like sparse matrix-dense matrix multiplies (SpMM), sparse matrix-sparse matrix multiplication (SpGEMM) and Sampled Dense-Dense Matrix Multiplication (SDDMM). As it turns out, these operations are the bedrock of sparse Deep Learning (DL); sparse deep neural networks and Graph Neural Networks (GNNs) have gained increasing attention recently in achieving speedups on training and inference with reduced memory footprints. Unlike scientific applications in High Performance Computing (HPC), modern (distributed-memory capable) DL toolkits often rely on non-standardized and closed-source vendor software optimizations, creating challenges in software-hardware co-design at scale. Our goal is to support a variety of distributed-memory sparse matrix operations and helper functions in the newly created Sparse Global Arrays (SGA), such that it is possible to build portable and productive Machine Learning scenarios for algorithm/software and hardware codesign purposes. Contemporary data-parallel schemes for training/inference are undergoing a major overhaul since model replication limits scalability and causes resource inefficiencies. As such, we have adopted tensor parallelism in decomposing the model and inputs, to mitigate memory issues. Current implementation is built on top of MPI and uses CPUs to maximize the portability across the platforms.

Distributed computing, machine learning↗
NASA NTRS2003

SpaceWire Driver Software for Special DSPs

A computer program provides a high-level C-language interface to electronics circuitry that controls a SpaceWire interface in a system based on a space qualified version of the ADSP-21020 digital signal processor (DSP). SpaceWire is a spacecraft-oriented standard for packet-switching data-communication networks that comprise nodes connected through bidirectional digital serial links that utilize low-voltage differential signaling (LVDS). The software is tailored to the SMCS-332 application-specific integrated circuit (ASIC) (also available as the TSS901E), which provides three highspeed (150 Mbps) serial point-to-point links compliant with the proposed Institute of Electrical and Electronics Engineers (IEEE) Standard 1355.2 and equivalent European Space Agency (ESA) Standard ECSS-E-50-12. In the specific application of this software, the SpaceWire ASIC was combined with the DSP processor, memory, and control logic in a Multi-Chip Module DSP (MCM-DSP). The software is a collection of low-level driver routines that provide a simple message-passing application programming interface (API) for software running on the DSP. Routines are provided for interrupt-driven access to the two styles of interface provided by the SMCS: (1) the "word at a time" conventional host interface (HOCI); and (2) a higher performance "dual port memory" style interface (COMI).

Clark, Douglas↗
NASA NTRS1994

Towards a Comprehensive Computational Simulation System for Turbomachinery

The objective of this work is to develop algorithms associated with a comprehensive computational simulation system for turbomachinery flow fields. This development is accomplished in a modular fashion. These modules includes grid generation, visualization, network, simulation, toolbox, and flow modules. An interactive grid generation module is customized to facilitate the grid generation process associated with complicated turbomachinery configurations. With its user-friendly graphical user interface, the user may interactively manipulate the default settings to obtain a quality grid within a fraction of time that is usually required for building a grid about the same geometry with a general-purpose grid generation code. Non-Uniform Rational B-Spline formulations are utilized in the algorithm to maintain geometry fidelity while redistributing grid points on the solid surfaces. Bezier curve formulation is used to allow interactive construction of inner boundaries. It is also utilized to allow interactive point distribution. Cascade surfaces are transformed from three-dimensional surfaces of revolution into two-dimensional parametric planes for easy manipulation. Such a transformation allows these manipulated plane grids to be mapped to surfaces of revolution by any generatrix definition. A sophisticated visualization module is developed to al-low visualization for both grid and flow solution, steady or unsteady. A network module is built to allow data transferring in the heterogeneous environment. A flow module is integrated into this system, using an existing turbomachinery flow code. A simulation module is developed to combine the network, flow, and visualization module to achieve near real-time flow simulation about turbomachinery geometries. A toolbox module is developed to support the overall task. A batch version of the grid generation module is developed to allow portability and has been extended to allow dynamic grid generation for pitch changing turbomachinery configurations. Various applications with different characteristics are presented to demonstrate the success of this system.

Shih, Ming-Hsin↗
DOE OSTI2025

Molecular Interlocking Multidimensional Modulations of Cathode‐Electrolyte Interface for Constructing High Energy Density Quasi‐Solid‐State Batteries

Gel polymers are regarded as a promising candidate electrolyte for lithium-metal quasi-solid-state batteries, primarily due to their high ionic conductivity and solid-liquid synergistic properties. However, challenges such as interfacial side reactions, limitations in Li + transport caused by interfacial issues, and leaching of transition metals from the cathode have yet to be effectively solved. Herein, a novel gel electrolyte modulation strategy based on electrostatic filler assembly is proposed to address the issues of ineffective capacity utilization and inadequate cycling stability of high-energy-density cathode materials in solid-state lithium-ion batteries. It constructs a 3D interpenetrating charge-bridge network that effectively tackles the phase-separation challenge between fillers and electrolytes at the molecular level. Meanwhile, the molecular interlocking structure effectively inhibits the electrolyte erosion. More critically, it optimizes and stabilizes the cathode-electrolyte interface film, which facilitates the conduction of Li + -ions through a size-sieving mechanism. Consequently, this strategy enables effective adaptation across diverse high-energy-density cathode materials with satisfactory capacity performance (170.4 mAh g −1 at 4.5 V/1 C for LiNi 0.6 Co 0.2 Mn 0.2 O 2 and 194.0 mAh g −1 at 4.3 V/1 C for LiNi 0.9 Co 0.08 Mn 0.02 O 2 ). In conclusion, this investigation offers a straightforward and effective reference for addressing the critical challenges of ionic transport and interface stabilization in the design of gel electrolytes.

cathode-electrolyte interface↗
DOE OSTI2023

Improving Frequency Stability and Minimizing Load Shedding Events by Adopting Grid-Scale Energy Storage with Grid Forming Inverters

The upward adoption trend of renewable generation not only means cleaner energy integrated into modern power grids, but also that most new generation sources are based on front-end inverter bridges, used as interfaces to most wind generation and all the solar PV. It is well known that due to their power electronics-based construction rather than rotational shafts, these sources do not provide inertia inherently, nor substantial amounts of short-circuit currents. However, stable energy such as what can be stored in energy storage systems, although interfaced via inverters, can be controlled to respond to system disturbances in a manner that emulates inertial behavior. This paper focuses on the application of such energy storage systems to augment inertia in the island of Puerto Rico. To do so, a user defined inverter model that contains grid forming capabilities and fast frequency response is modeled and integrated into the real transmission system in power flow and dynamics software. Energy storage is then connected to two selected areas so that it not only provides frequency regulation to avoid widespread load shedding events, but also other tangible benefits. The simulated cases suggest that even relatively small energy storage systems can avert load shedding events if adequately placed in the transmission network.

Grid-forming inverters, IBR, Inertia↗
DOE OSTI2026

Deciphering the Conflict Between Ion and Electron Percolating Networks in Solid-State Battery Cathodes

High-energy- and power-density solid state batteries require an optimal cathode composition and microstructural arrangement of cathode active material, solid-state electrolyte, conductive carbon, and binder to simultaneously support lithium-ion transport, electron conduction, and storage capacity. The ion and electron conducting phases in solid-state cathodes counteract each other's percolating networks as their mass ratios increase or decrease relative to each other. Here, we investigate targeted mass ratio variations of argyrodite solid electrolyte and two different types of conductive carbon (particles and fibers) in composite LiNi0.8Mn0.1Co0.1O2 (NMC811) solid-state cathodes to ascertain the ionic-electronic tradeoffs in cathode performance. Through ionic and electronic conductivity measurements on composite cathodes, as well as rate-testing and cycling performance in full cells, it is shown that the conductive carbon fibers form a percolative electronic network within the composite at a lower mass ratio (3-5 wt%) than particulate carbon (>5 wt%). The threshold to achieve electronic percolation coincides with higher accessible capacity in the cathode as the active material particles become electronically connected. However, carbon loadings beyond this percolation threshold lead to increased ion transport resistance, arising from disruptions to ionic conduction pathways and degraded contact at the interface between the electrolyte and active materials. Imaging, spectroscopy, and physics-based models quantitatively describe the relationship between carbon and electrolyte compositions and the cell's capacity and rate performance through percolation theory. This work demonstrates the importance of quantitatively understanding percolating networks in solid-state cells and that strategic engineering of conductive carbon morphologies can further increase the energy- and power-density of solid-state cells.

25 ENERGY STORAGE↗
DOE OSTI2024

Tough and circular glass fiber composites via a tailored dynamic boronic ester interface

Glass fiber reinforced polymer (GFRP) composites are valued for their strength and cost-effectiveness. However, traditional GFRPs often face challenges for end-of-life recycling due to their non-depolymerizable thermoset matrices, and long-term performance due to inadequate interfacial adhesion, which can lead to fiber–matrix delamination. Here, in this work, we have designed dynamic fiber–matrix interfaces to allow tough and closed-loop recyclable GFRPs by utilizing a vitrimer, derived from upcycled polystyrene-b-poly(ethylene-co-butylene)-b-polystyrene (SEBS) with boronic ester (S-Bpin) and amine-based diol crosslinker. The boronic ester groups in S-Bpin form dynamic covalent bonds with the naturally present hydroxyl groups on the unsized GF surface, which eliminates the need for fiber sizing and enables facile closed-loop recyclability of both the fibers and the vitrimer matrix. The resulting strong fiber–matrix interface, depicted by the Raman mapping, leads to a 552% increase in-plane shear toughness (6.2 ± 0.3 MJ m -3 ) and 27% ultimate tensile strength (361 ± 89.2 MPa) compared to those of the conventional epoxy-based matrix (0.95 ± 0.05 MJ m -3 and 264 ± 59.7 MPa, respectively). The network rearrangement through dynamic boronic ester exchange enables fast thermoformability and repairability of micro-cracks at elevated temperatures. Additionally, both the matrix and composite demonstrate strong adhesion to various surfaces including steel and glasses exhibiting ≥6 MPa lap shear strength, which expands their suitability for diverse industrial applications. The readily created dynamic interface between boronic ester functionalized vitrimer and neat GFs presents a promising strategy for developing closed-loop recyclable, multifunctional structural materials, offering a sustainable alternative to non-recyclable thermoset GFRPs and contributes to a circular economy in composite materials.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Copyright Ownership in a Networked Multimedia Environment

The explosion of computer communications in the United States has spurred the development of many new technologies. One of these new technologies is Mosaic and the World-Wide Web. Mosaic is a user interface that uses the internet as a backbone for communications. The Mosaic interface enables a user to manipulate text, images and graphics produced by different authors. The flexibility that Mosaic offers raises significant copyright issues. This paper attempts to analyze these issues using current copyright law as a framework. The author then goes on to offer a different analysis that may result from future developments in copyright law.

Williams, Vernon E.↗
DOE OSTI2026

Deterministic Fabrication of Large-Area, High-Crystallinity Oxide Moiré Superlattices

Oxide twistronics extends moiré engineering beyond van der Waals materials, offering a promising platform for accessing emergent interfacial phenomena arising from the strong coupling of lattice, charge, and orbital degrees of freedom in complex oxides. However, deterministic fabrication of high-crystallinity oxide moiré superlattices over large lateral dimensions remains challenging due to the three-dimensional bonding network of oxides. Here, we demonstrate a scalable, generalized fabrication strategy that enables the formation of high-crystallinity oxide moiré superlattices with clean, chemically bonded interfaces and precisely controlled twist angles down to nominal values of 0.1°, achieving subdegree twist-angle accuracy across large contiguous lateral dimensions approaching the millimeter scale. Using NaNbO3 as a model system, we show that the resulting interlayer coupling drives pronounced structural reconstruction that modifies both the phase structure and ferroelectric domain configuration. Synchrotron-based X-ray 3D reciprocal space mapping reveals the emergence of a single-phase state in twisted bilayers, in contrast to the mixed-phase structure observed in single-layer membranes prior to twist assembly. The structural signatures are further consistent with gradual lattice rotation distributed along the thickness direction that may accommodate interfacial shear strain, distinct from reconstruction observed in van der Waals moiré systems which primarily occurs through in-plane stacking rearrangement. This collective lattice response is correlated with twist-dependent nanoscale electromechanical modulations observed by piezoresponse force microscopy. These results establish a scalable materials platform for oxide twistronics and support the implementation of twist-engineered functionalities in practical, macroscale device architectures.

Ghanbari, Reza [North Carolina State University (N↗
DOE OSTI2022

MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks

Abstract We report a workflow and the output of a natural language processing (NLP)-based procedure to mine the extant metal–organic framework (MOF) literature describing structurally characterized MOFs and their solvent removal and thermal stabilities. We obtain over 2,000 solvent removal stability measures from text mining and 3,000 thermal decomposition temperatures from thermogravimetric analysis data. We assess the validity of our NLP methods and the accuracy of our extracted data by comparing to a hand-labeled subset. Machine learning (ML, i.e. artificial neural network) models trained on this data using graph- and pore-geometry-based representations enable prediction of stability on new MOFs with quantified uncertainty. Our web interface, MOFSimplify, provides users access to our curated data and enables them to harness that data for predictions on new MOFs. MOFSimplify also encourages community feedback on existing data and on ML model predictions for community-based active learning for improved MOF stability models.

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

Making coordination networks ionic: a unique strategy to achieve solution-processable hybrid semiconductors

The development of high-performance, solution-processable semiconducting materials is crucial for the advancement of emerging clean-energy technologies such as light-emitting diodes and photovoltaics. While hybrid perovskites have shown considerable promise for implementation in these technologies, their reliance on toxic metals and relatively low stability towards moisture and chemical environments remain to be addressed. In this Chemistry Frontiers article, we describe a unique strategy to build nontoxic, robust and solution-processable hybrid semiconductors based on copper halide by incorporating ionic bonds in coordination complexes (molecular or extended network structures). Specifically, these compounds are made of anionic copper(I) halide and cationic organic ligands that form both coordinate and ionic bonds at the inorganic/organic interfaces and are referred to as all-in-one (AIO)-type structures. Here, the unique bonding nature renders the AIO-type structures with greatly enhanced solubility, excellent optical tunability and remarkable framework stability, all highly desirable for thin-film based optoelectronic devices. We will highlight the most recent progress in the development of this material group, including their design strategies, important properties and potential for clean-energy related applications. We will also briefly discuss the existing challenges and future outlook of these materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Entropic colloidal crystallization pathways via fluid–fluid transitions and multidimensional prenucleation motifs

Complex crystallization pathways are common in protein crystallization, tetrahedrally coordinated systems, and biomineralization, where single or multiple precursors temporarily appear before the formation of the crystal. The emergence of precursors is often explained by a unique property of the system, such as short-range attraction, directional bonding, or ion association. But, structural characteristics of the prenucleation phases found in multistep crystallization remain unclear, and models are needed for testing and expanding the understanding of fluid-to-solid ordering pathways. Here, we report 3 instances of 2-step crystallization of hard-particle fluids. Crystallization in these systems proceeds via a high-density precursor fluid phase with prenucleation motifs in the form of clusters, fibers and layers, and networks, respectively. The density and diffusivity change across the fluid–fluid phase transition increases with motif dimension. We observe crystal nucleation to be catalyzed by the interface between the 2 fluid phases. The crystals that form are complex, including, notably, a crystal with 432 particles in the cubic unit cell. Finally, our results establish the existence of complex crystallization pathways in entropic systems and reveal prenucleation motifs of various dimensions.

2-step crystallization↗
DOE OSTI2020

DiHydrogen

DiHydrogen is the second version of the Hydrogen fork of the well-known distributed linear algebra library, Elemental. DiHydrogen is a GPU-accelerated distributed multilinear algebra interface with a particular emphasis on the needs of the scalable distributed deep learning training and inference. DiHydrogen is part of the Livermore Big Artificial Neural Network (LBANN) software stack.

Maruyama, Naoya↗
DOE OSTI2021

Identification and Testing of Electric Vehicle Fast Charger Cybersecurity Mitigations

Fast-charging infrastructure for electric vehicles (EVs) is needed to enable and achieve the national goals of transitioning the vehicle fleet toward more electrification. Idaho National Laboratory, Oak Ridge National Laboratory, and the National Renewable Energy Laboratory (NREL) have jointly worked to identify, evaluate, and mitigate potential cyber-related consequences associated with fast charger systems. NREL contributed by considering cyberattack scenarios and consequences associated with integrating distributed energy resources (DERs) at fast-charging stations. The dynamic nature of fast-charger load profiles would encourage site operators to incorporate solar for energy cost reduction and energy storage for peak demand cost management at future charging facilities with multiple fast chargers at a site. These energy resources would be monitored and coordinated via a site energy management controller with data exchange between devices and local power metering infrastructure; thus, networking between devices and the design of the system becomes important in the overall cybersecurity posture. In addition, component vendors and system operators might have remote interfaces to any of these systems. It is therefore important to understand the breadth of the cyberattack surface and potential strategies to mitigate impacts. This project has focused on components and protocols expected to be found within a local charging site that includes multiple chargers and DER resources. Our methods and results are summarized in this final report.

42 ENGINEERING↗