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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Resonant X-ray Diffraction Reveals the Location of Counterions in Doped Organic Mixed Ionic Conductors

Organic mixed ionic–electronic conductors (OMIECs) have the potential to enable diverse new technologies, ranging from novel in situ biosensors to flexible energy storage devices and neuromorphic computing platforms. However, their complex behavior in functional films involving electrolyte-induced swelling, ion ingress, and electrochemical doping inhibits rational material design. Of critical importance is an understanding of the specific location of the ions in the volumetrically doped material, yet this information is not readily available. Here, in this report, we present the use of grazing- incidence resonant X-ray diffraction (RXRD, also known as anomalous diffraction) at S and Cl K-edges to determine the structure of a doped, prototypical, semicrystalline polymer OMIEC based on oligo(ethylene glycol) substitution of regioregular polythiophene. The RXRD measurement provides two key insights. Quantitative analysis of the RXRD allows the determination of the position of the ion relative to the polymer backbone in the crystalline regions. We find that the anion is relatively distant from the backbone, nearer to the lamella mid-plane naively in conflict with expected Coulombic attraction between the ion and the doped polymer polaron. Comparison of RXRD to Cl – fluorescence (total Cl – ) allows determination of the relative order of doping between the crystalline and amorphous regions. We find preferential doping of the crystalline regions. Both insights, the preferential doping of crystals at low potential and the specific location of the counterion with respect to the polymer backbone, are critical to developing a microscopic understanding of transport in OMIECs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

(Towards) DNS of a Laboratory Lean CH4/H2 Low-Swirl Flame Impinging on an Inclined Wall

Due to downsizing trends, flame-wall interaction (FWI) is increasingly prominent in gas turbines (GTs). FWI has direct consequences on flame stabilization and pollutant emissions, but it is not well understood in turbulent flows representative of GTs. We present results from a direct numerical simulation (DNS) of a turbulent CH4/H2 model GT low-swirl laboratory-scale flame interacting with an inclined wall. The results from the laboratory flame include simultaneous measurements of velocity using stereo particle imaging velocimetry and OHxCH2O planar laser induced fluorescence. The adaptive-mesh refinement solver PeleLMeX is used, with 24-species, 105-reaction reduced Aramco chemical kinetics mechanism. The premixed fuel-air mixture consists of hydrogen-enriched methane with 70% hydrogen volume fraction and 0.4 equivalence ratio. The inflow is prescribed to match experimental measurements at the burner exit. Karlovitz and turbulent Reynolds numbers are 300 and 400, respectively. The simulation and experimental results show excellent agreement. The flame features a bowl-shape stabilization, with a corrugated, continuous flame front at the leading edge, followed by fragmented reaction zones downstream. A large diffuse cloud of CH2O is formed downstream of the quenching point. The simulation results indicate that the cloud of CH2O is the result of incomplete methane combustion, with CH2O "leaking" from the locally quenched reaction zones.The DNS provides fine-grain resolution of turbulence-flame-wall interaction that cannot be captured with experimental measurements. With access to the entire solution vector at each cell of the computational domain, the local quenching.

flame-wall interactions↗
DOE OSTI2026

Ensemble Federated Machine Learning‐Based Cybersecurity Situational Awareness in Microgrid Network

Cyber-physical microgrids are vulnerable to stealthy cybersecurity threats that disguise their actions through the exploitation of system knowledge. Such actions can severely impacts microgrids deployed in defense bases, slowing the response time of military forces during national emergencies. Several machine-learning algorithms have been proposed to detect intrusions in the grid networks; however, these traditional machine-learning algorithms lack data privacy and are subject to several adversarial machine-learning threats. This paper proposes a novel federated machine learning (FML)-based three-model framework to detect and identify stealthy data-integrity attacks while ensuring data privacy in microgrid networks. The proposed architecture uses a variational mode decomposition technique to extract derived features from incoming measurement and control datasets. The extraction of these derived features allows FML models to learn minute variations in data patterns that allow them to perform significantly better than the models trained with generic datasets consisting of raw features. Our experimental results show the efficient performance of the proposed methodology against different types of data integrity attacks while considering primary and secondary controllers in microgrids. Further, the applied FML-integrated random forest ensemble algorithm outperforms the existing generic FML algorithms during noisy and noise-free datasets with prediction latencies of only 91–134 µs per sample within the 0.1 s sampling interval and requires communication bandwidth of around ∼8.25 KB/s at the control center and ∼2.7 KB/s per edge client for communication.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

District-Scale Analysis of Electricity Load and Strategies to Improve Energy Reliability Using Prototype District Models

Projected increases in electricity demand in the U.S. highlight the urgent need for effective load management to ensure grid reliability. As the building sector accounts for approximately 75% of electricity usage, enhancing energy efficiency and flexibility in this sector is crucial. Adopting district-level approaches offers significant advantages over traditional individual building analyses by enabling shared infrastructure and economies of scale. To navigate the data and computational challenges associated with modeling energy at the district level, prototype district models have been proposed as holistic, system-level solutions that capture complex interactions within typical configurations. This study presents these models as a reference tool for analyzing district-scale energy systems across various climate zones in the U.S. Developed with input from stakeholders, these models integrate varied building characteristics, inter-building connections, and energy system interactions. A case study utilizing the Urban Edge prototype district model, implemented on the URBANopt™ platform, evaluates multiple demand scenarios and the impact of distributed energy resources such as fuel-fired backup generators, photovoltaic systems, and batteries. Findings suggest that while new electric systems can significantly reduce annual energy use, they may also elevate peak electricity loads, with a notable 43% increase in heating-dominant climate zone 5B. The optimal backup power solutions vary based on location, influenced by factors such as utility rates and incentives. For example, PV and batteries perform well in high-cost regions like New York City, while diesel backup generators are more suitable for backup needs in climate zone 3A, such as Atlanta. Thus, this research highlights the importance of prototype district models for future district-scale energy planning.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Defect Properties, Anion Ordering, and Photochromic Mechanism in Yttrium Oxyhydride

Yttrium oxyhydride (YHO) undergoes a reversible photochromic transition when exposed to ultraviolet light. However, the mechanism for this transformation is not fully understood, and the structure and precise chemical composition of YHO remain under debate. Here, we use first-principles density functional theory calculations with a hybrid functional to study the structure, chemical stability, and point defect properties of YHO. As experiments have shown, we find that YHO prefers a cubic structure, with H and O anions present in equal concentrations and located on tetrahedral sites. Stoichiometric and ordered YHO is chemically stable, but it has a wide band gap of 5.01 eV, considerably larger than that measured in experiments (2.4–3.8 eV). On the other hand, Y4H10O has a smaller band gap of 2.97 eV and also has a region of chemical stability; thus, the actual material may include some fraction of this H-rich structure. The defect chemistry of YHO is dominated by anionic antisite species (H O and O H ), with hydrogen interstitials (H i ) and vacancies (V H ) also present in reasonably high concentrations. We show that antisite disorder lowers the band gap relative to the perfectly ordered structure, bringing the magnitude of the gap into closer agreement with experiment. Based on our calculations of defect migration and the positions of defect states relative to the band edges, we link the onset of photochromic behavior to the reaction H O – → V O 0 + H i – , which follows photoexcitation of a H O + defect. H i – can subsequently migrate away and be trapped by additional H O + defects, contributing to the persistence of the reaction, while the resultant oxygen vacancy, V O 0 , introduces an occupied defect state that leads to optical absorption at visible wavelengths. Our results can explain reported discrepancies between experimental and computational results for YHO, and they allow us to propose specific atomic-scale processes that can lead to photochromism. In conclusion, understanding these mechanisms is key for unlocking YHO’s application in devices ranging from smart windows and optoelectronics to electrochemical synapses for neural networks.

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

Growth of Well-Defined Model Catalysts for Electrochemistry: From Surface Science Studies to Electrocatalytic CO2 Conversion

We combined ultrahigh vacuum (UHV) surface science techniques, electrochemical measurements, and computational modeling to investigate electrocatalytic systems that are crucial components of the carbon management effort, including oxygen evolution reactions (OER) and CO2 reduction reactions (CO2RR). Well-defined Model catalysts were grown on substrates in the UHV chamber and characterized with X-ray photoelectron spectroscopy (XPS) and scanning tunneling microscopy (STM). Selected model electrocatalysts were then tested in electrochemical cells to establish the structure-property relationships in OER and CO2RR. Our results showed that the edge sites of Fe2O3 grown on Au(111) were the most active toward OER and incorporation of Ni at the edge sites (NiFeOx) further boosted their OER activity. We also resolved the size-dependent electrocatalytic CO2-to-CO conversion of the Ag nanoparticle electrocatalysts with average particle diameter between 2 to 6 nm: smaller diameter (< 3 nm) particles favored H2 evolution reaction (HER) due to a high population of Ag edge sites, whereas larger diameter particles favored CO2RR as the population of Ag(100) surface sites grew. We further discovered that electronic interactions between small diameter Ag particles and highly defective carbon supports could break the size-dependent CO2RR selectivity, resulting in highly selective (CO Faradaic Efficiency > 90%) and active Ag nanoparticle electrocatalysts with sizes < 2 nm diameter.

Deng, Xingyi↗
DOE OSTI2020

Almost-Rigidity of Frameworks

Here, we extend the mathematical theory of rigidity of frameworks (graphs embedded in d-dimensional space) to consider nonlocal rigidity and flexibility properties. We provide conditions on a framework under which (I) as the framework flexes continuously it must remain inside a small ball, a property we call “almost-rigidity”; (II) any other framework with the same edge lengths must lie outside a much larger ball; (III) if the framework deforms by some given amount, its edge lengths change by a minimum amount; (IV) there is a nearby framework that is prestress stable, and thus rigid. The conditions can be tested efficiently using semidefinite programming. The test is a slight extension of the test for prestress stability of a framework, and gives analytic expressions for the radii of the balls and the edge length changes. Examples illustrate how the theory may be applied in practice, and we provide an algorithm to test for rigidity or almost-rigidity. We briefly discuss how the theory may be applied to tensegrities. © 2020 Wiley Periodicals LLC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Advances in Clayff Molecular Simulation of Layered and Nanoporous Materials and Their Aqueous Interfaces

As a general-purpose force field for molecular simulations of layered materials and their fluid interfaces, Clayff continues to see broad usage in atomistic computational modeling for numerous geoscience and materials science applications due to its (1) success in predicting properties of bulk nanoporous materials and their interfaces, (2) transferability to a range of layered and nanoporous materials, and (3) simple functional form which facilitates incorporation into a variety of simulation codes. Here, we review applications of Clayff to model bulk phases and interfaces not included in the original parameter set and recent modifications for modeling surface terminations such as hydroxylated nanoparticle edges. Overall, we conclude with a discussion of expectations for future developments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Gyrokinetic understanding of the edge pedestal transport driven by resonant magnetic perturbations in a realistic divertor geometry

Self-consistent simulations of neoclassical and electrostatic turbulent transport in a DIII-D H-mode edge plasma under resonant magnetic perturbations (RMPs) have been performed using the global total-f gyrokinetic particle-in-cell code x-point gyrokinetic code (XGC), in order to study density pump-out and electron heat confinement. The RMP field is imported from the extended magneto-hydrodynamics code M3D-C1, taking into account the linear two-fluid plasma response. With both neoclassical and turbulence physics considered together, the XGC simulation reproduces two key features of experimentally observed edge transport under RMPs: increased radial particle transport in the pedestal region that is sufficient to account for the experimental pump-out rate and suppression of the electron heat flux in the steepest part of the edge pedestal. In the simulation, the density fluctuation amplitude of modes moving in the electron diamagnetic direction increases due to interaction with RMPs in the pedestal shoulder and outward, while the electron temperature fluctuation amplitude decreases.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

A fluid-structure interaction solver for investigating torsional galloping in solar-tracking photovoltaic panel arrays

Solar-tracking photovoltaic arrays are susceptible to aeroelastic fluttering during high-wind events. This dynamic fluttering behavior can grow in amplitude until the panels enter an unstable mode known as torsional galloping which can lead to panel failure or total array destruction. To better understand the physics of the torsional galloping phenomenon and to inform the discussion around panel design and recommended panel stow positions during high wind events, a fluid-structure interaction solver composed of a simulated atmospheric boundary layer with simplified panel structural responses was designed. The simulation choices and features of this solver were informed by the geometry and physical properties of an experimental panel array known to exhibit torsional galloping behavior during hind-wind events. Furthermore, these simulations revealed that the torsional galloping instability is driven by a combination of cyclic vortex shedding from the sun-facing side of the panel and the elastic properties of the torque tube linking the panel assemblies. Testing different stow angles across a range of wind speeds indicates that panels are generally more stable when stowed at negative angles where the leading edge is closer to the ground, hypothesized to be due to ground-blocking effects. These results are supplemented by a discussion of stability trends noted during testing and possible implications when considering multi-row array interactions.

14 SOLAR ENERGY↗
DOE OSTI2022

An automated fast neutron computed tomography instrument with on-line focusing for non-destructive evaluation

A fast neutron tomography imaging instrument has been designed, built, and tested at The Ohio State University 500 kW Research Reactor on a fast neutron beamline with a peak neutron flux ≈5.4 × 107 n·cm−2·s−1 at 1.6 MeV median neutron energy. The instrument and beamline are also configurable for thermal neutron imaging. The imaging apparatus is composed of a lens coupled, water-cooled Electron Multiplying Charge Coupled Device camera, a front-surface mirror, and a high light yield plastic Polyvinyl toluene scintillator. The instrument sits on a mobile cart. A total of 5 motion-control stages are built into the system for XYZ and rotational degrees of freedom for sample positioning; the fifth stage fine tunes the focal distance between the camera and the scintillator to achieve on-line focusing. A Python code with a user-friendly graphical user interface controls the fully automated image acquisition, not requiring user interaction, yet facilitating tracking of the image acquisition. A complete fast neutron computed tomography dataset with 360 projections requires less than 3 h, with 30 s per projection. On-line focusing is accomplished with a commercial, off-the-shelf, dielectrically actuated liquid lens. Finally, tomographic reconstructions are visualized using the Livermore Tomography Tools software package. The effective pixel size (width and height) is ≈0.1058 mm, yielding a minimum voxel size of 0.1058 × 0.1058 × 0.1058 mm3, and produces a spatial resolution of 231 μm when calculated from knife-edge measurements.

Bisbee, M. G. (ORCID:0000000313466697)↗
DOE OSTI2020

Neuromorphic Graph Algorithms: Extracting Longest Shortest Paths and Minimum Spanning Trees

Neuromorphic computing is poised to become a promising computing paradigm in the post Moore's law era due to its extremely low power usage and inherent parallelism. Traditionally speaking, a majority of the use cases for neuromorphic systems have been in the field of machine learning. In order to expand their usability, it is imperative that neuromorphic systems be used for non-machine learning tasks as well. The structural aspects of neuromorphic systems (i.e., neurons and synapses) are similar to those of graphs (i.e., nodes and edges), However, it is not obvious how graph algorithms would translate to their neuromorphic counterparts. In this work, we propose a preprocessing technique that introduces fractional offsets on the synaptic delays of neuromorphic graphs in order to break ties. This technique, in turn, enables two graph algorithms: longest shortest path extraction and minimum spanning trees.

Kay, Bill↗
DOE OSTI2023

Efficient QAOA Optimization using Directed Restarts and Graph Lookup

Variational Quantum Algorithms (VQA) aim to enhance the capabilities of Noisy Intermediate-Scale Quantum (NISQ) devices. These algorithms utilize parameterized circuits and classical optimizers to iteratively execute circuits with varying parameters. However, VQA faces computational overheads due to repeated iterations and random restarts. Prior work suggests using basic sub-graphs to transfer parameters for the input graph, reducing optimizer overheads but limiting applicability to structured regular graphs. In real-world applications, random irregular graphs are common, and existing methods are not scalable or practical for such graphs. This paper presents a framework that aims to improve random irregular graphs in VQA. The framework uses graph similarity and important features like total edge counts, average edge counts, and variance. It follows an iterative process to choose basis sub-graphs from a small database and adjust parameters accordingly. Classical optimizers then utilize these parameters to determine when to restart and perform gradient descent. This approach increases the chances of reaching global maximum points.

Wang, Meng↗
DOE OSTI2025

Simulations of Radiation Hydrodynamics in Strongly Coupled Plasmas (Final Report)

Radiation propagates throughout the Universe and is often the only information we have from distant astronomical objects. Additionally, radiation plays a key role in systems ranging from the interior of stars to the establishment of shocks at the edges of forming galaxies to neutron star mergers. Here radiative processes, absorption, emission, and scattering, are fundamental to transport of momentum and energy, as well as, the overall evolution of these and other astrophysical systems. In some cases, radiation-dominant systems are also sufficiently dense and ionized, such that, the ions are strongly coupled (ie electrostatic energy >> thermal energy or Γ >> 1), which will affect radiative processes and the transport of radiation. During this project, we developed a computational ray-tracing algorithm to study radiation transport through a simulated neutron star capsule implosion under conditions relevant to Omega-60 laser experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The Other Artificial Intelligence Hardware Problem

The consolidation of leading-edge semiconductor manufacturing in one company in one country poses two problems: a short-term strategic risk and a long-term innovation risk. Furthermore, both problems remain underexplored because advances in artificial intelligence (AI) algorithms have compensated for a relative lack of advances in AI hardware.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Trajectory Optimization via Unsupervised Probabilistic Learning On Manifolds

This report investigates the use of unsupervised probabilistic learning techniques for the analysis of hypersonic trajectories. The algorithm first extracts the intrinsic structure in the data via a diffusion map approach. Using the diffusion coordinates on the graph of training samples, the probabilistic framework augments the original data with samples that are statistically consistent with the original set. The augmented samples are then used to construct conditional statistics that are ultimately assembled in a path-planing algorithm. In this framework the controls are determined stage by stage during the flight to adapt to changing mission objectives in real-time. A 3DOF model was employed to generate optimal hypersonic trajectories that comprise the training datasets. The diffusion map algorithm identfied that data resides on manifolds of much lower dimensionality compared to the high-dimensional state space that describes each trajectory. In addition to the path-planing worflow we also propose an algorithm that utilizes the diffusion map coordinates along the manifold to label and possibly remove outlier samples from the training data. This algorithm can be used to both identify edge cases for further analysis as well as to remove them from the training set to create a more robust set of samples to be used for the path-planing process.

42 ENGINEERING↗
DOE OSTI2026

QPatLib v1.0 — Measurement-based quantum simulation Pauli string unitary pattern collections

This Zenodo record accompanies the paper “Scalable Measurement-Based Quantum Simulation Patterns for Benchmarking” arXiv.2605.12502 and provides QPatLib v1.0 measurement-pattern datasets in human-readable JSONL together with a ZIP archive of OpenQASM 3.0 circuits used for validation and reproducibility. The patterns and circuits implement Pauli string unitaries for benchmark cases. Cases include all possible string combinations for less than 6 qubits and strings used in Hamiltonians for certain diatomic molecules for 6 or more qubits. Format: Each pattern_*.jsonl file is containins measurement patterns for all subsets for a given model/instance and subset strategy: it begins with a preamble containing model metadata, subset definitions, provenance, and (when feasible) full-pattern test results, followed by one pattern entry per subset. Each subset entry includes a required pattern_ascii field storing the measurement pattern in the measurement-calculus/Graphix standard with signal shifting, written left-to-right in the canonical order nodes → edges → measurements (with signal dependencies) → byproduct corrections (X/Z). The circuits are included as circuit_files.zip. Patterns in this record were validated against the corresponding circuits and checked for causal flow. Codes for generating these patterns can be found at QPatLib repository on Github

Graphix↗
DOE OSTI2023

Quantitative relationships between film morphology, charge carrier dynamics, and photovoltaic performance in bulk-heterojunction binary vs. ternary acceptor blends

Addressing pertinent and perplexing questions regarding why nonfullerene acceptors (NFAs) promote higher power conversion efficiencies (PCEs) than traditional fullerenes and how photoactive bulk heterojunction (BHJ) film morphology, charge photogeneration, and recombination dynamics dictate solar cell performance have stimulated many studies of polymer solar cells (PSCs), yet quantitative relationships remain limited. Better understanding in these areas offers the potential to advance materials design and device engineering, afford higher PCEs, and ultimate commercialization. Here we probe quantitative relationships between BHJ film morphology, charge carrier dynamics, and photovoltaic performance in model binary and ternary blend systems having a wide bandgap donor polymer, a fullerene, and a promising NFA. We show that optimal PC 71 BM incorporation in a PBDB-TF:ITIC-Th binary system matrix retains the original π-face-on orientation, ITIC-Th crystallinity and BHJ film crystallite dimensions, and reduces film upper surface ITIC-Th segregation. Such morphology changes together simultaneously increase hole (μ h ) and electron (μ e ) mobilities, facilitate light-activated ITIC-Th to PC 71 BM domain electron delocalization, reduce free charge carrier (FC) bimolecular recombination (BR) within PBDB-TF:ITIC-Th mixed regions, and increase FC extraction pathways viaPBDB-TF:PC 71 BM pairs. The interplay of these effects yields significantly enhanced inverted cell short-circuit current density (J SC ), fill factor (FF), and PCE. Unexpectedly, we also find that excessive PC 71 BM in the PBDB-TF:ITIC-Th binary system alters the PBDB-TF orientation to π-edge-on, increases large scale PC 71 BM-rich aggregations and BHJ upper surface PC 71 BM composition. Further, these morphology changes increase parasitic decay processes such as intersystem crossing from photoexcited PC 71 BM, compromising the J SC , FF, and PCE metrics. ITIC-Th X-ray diffraction reveals a unique sidechain-dominated molecular network with previously unknown sidechain-end group stacking, rationalizing the STEM and GIWAXS results, photophysics, and the high μ e . DFT computation reveals charge transfer networks within ITIC-Th crystallites, supporting excited-state electron delocalization from ITIC-Th to PC 71 BM. This structure–property understanding leads to a newly reported NFA blend with PCE near 17%.

14 SOLAR ENERGY↗