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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Design and testing of a unique randomized gravity, continuous flow bioreactor

A rotating, null gravity simulator, or Couette bioreactor was successfully used for the culture of mammalian cells in a simulated microgravity environment. Two limited studies using Lipomyces starkeyi and Streptomyces clavuligerus were also conducted under conditions of simulated weightlessness. Although these studies with microorganisms showed promising preliminary results, oxygen limitations presented significant limitations in studying the biochemical and cultural characteristics of these cell types. Microbial cell systems such as bacteria and yeast promise significant potential as investigative models to study the effects of microgravity on membrane transport, as well as substrate induction of inactive enzyme systems. Additionally, the smaller size of the microorganisms should further reduce the gravity induced oscillatory particle motion and thereby improve the microgravity simulation on earth. Focus is on the unique conceptual design, and subsequent development of a rotating bioreactor that is compatible with the culture and investigation of microgravity effects on microbial systems. The new reactor design will allow testing of highly aerobic cell types under simulated microgravity conditions. The described reactor affords a mechanism for investigating the long term effects of reduced gravity on cellular respiration, membrane transfer, ion exchange, and substrate conversions. It offers the capability of dynamically altering nutrients, oxygenation, pH, carbon dioxide, and substrate concentration without disturbing the microgravity simulation, or Couette flow, of the reactor. All progeny of the original cell inoculum may be acclimated to the simulated microgravity in the absence of a substrate or nutrient. The reactor has the promise of allowing scientists to probe the long term effects of weightlessness on cell interactions in plants, bacteria, yeast, and fungi. The reactor is designed to have a flow field growth chamber with uniform shear stress, yet transfer high concentrations of oxygen into the culture medium. The system described allows for continuous, on line sampling for production of product without disturbing fluid and particle dynamics in the reaction chamber. It provides for the introduction of substrate, or control substances after cell adaptation to simulated microgravity has been accomplished. The reactor system provides for the nondisruptive, continuous flow replacement of nutrient and removal of product. On line monitoring and control of growth conditions such as pH and nutrient status are provided. A rotating distribution valve allows cessation of growth chamber rotation, thereby preserving the simulated microgravity conditions over longer periods of time.

Lassiter, Carroll B.↗
DOE OSTI2023

Multiple emission components in the Cygnus cocoon detected from Fermi -LAT observations

Star-forming regions may play an important role in the life cycle of Galactic cosmic rays (CRs), notably as home to specific acceleration mechanisms and transport conditions. Gamma-ray observations of Cygnus X have revealed the presence of an excess of hard-spectrum gamma-ray emission, possibly related to a cocoon of freshly accelerated particles. We seek an improved description of the gamma-ray emission from the cocoon using ~13 yr of observations with the Fermi-Large Area Telescope (LAT) and use it to further constrain the processes and objects responsible for the young CR population. We developed an emission model for a large region of interest, including a description of interstellar emission from the background population of CRs and recent models for other gamma-ray sources in the field. Thus, we performed an improved spectro-morphological characterisation of the residual emission including the cocoon. The best-fit model for the cocoon includes two main emission components: an extended component FCES G78.74+1.56, described by a 2D Gaussian of extension r 68 = 4.4° ± 0.1° -0.1° +0.1° and a smooth broken power law spectrum with spectral indices 1.67 ± 0.05 -0.01 +0.02 and 2.12 ± 0.02 -0.01 +0.00 below and above 3.0 ± 0.6 -0.2 +0.0 GeV, respectively; and a central component FCES G80.00+0.50, traced by the distribution of ionised gas within the borders of the photo-dissociation regions and with a power law spectrum of index 2.19 ± 0.03 -0.01 +0.00 that is significantly different from the spectrum of FCES G78.74+1.56. An additional extended emission component FCES G78.83+3.57, located on the edge of the central cavities in Cygnus X and with a spectrum compatible with that of FCES G80.00+0.50, is likely related to the cocoon. For the two brightest components FCES G80.00+0.50 and FCES G78.74+1.56, spectra and radial-azimuthal profiles of the emission can be accounted for in a diffusion-loss framework involving one single population of non-thermal particles with a flat injection spectrum. Particles span the full extent of FCES G78.74+1.56 as a result of diffusion from a central source, and give rise to source FCES G80.00+0.50 by interacting with ionised gas in the innermost region. For this simple diffusion-loss model, viable setups can be very different in terms of energetics, transport conditions, and timescales involved, and both hadronic and leptonic scenarios are possible. The solutions range from long-lasting particle acceleration, possibly in prominent star clusters such as Cyg OB2 and NGC 6910, to a more recent and short-lived release of particles within the last 10–100 kyr, likely from a supernova remnant. The observables extracted from our analysis can be used to perform detailed comparisons with advanced models of particle acceleration and transport in star-forming regions.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

The giant impact produced a precipitated Moon

The author's current simulations of Giant Impacts on the protoearth show the development of large hot rock vapor atmospheres. The Balbus-Hawley mechanism will pump mass and angular momentum outwards in the equatorial plane; upon cooling and expansion the rock vapor will condense refractory material beyond the Roche distance, where it is available for lunar formation. During the last seven years, the author together with several colleagues has carried out a series of numerical investigations of the Giant Impact theory for the origin of the Moon. These involved three-dimensional simulations of the impact and its aftermath using Smooth Particle Hydrodynamics (SPH), in which the matter in the system is divided into discrete particles whose motions and internal energies are determined as a result of the imposed initial conditions. Densities and pressures are determined from the combined overlaps of the particles, which have a bell-shaped density distribution characterized by a smoothing length. In the original series of runs all particle masses and smoothing lengths had the same values; the matter in the colliding bodies consisted of initial iron cores and rock (dunite) mantles. Each of 41 runs used 3,008 particles, took several weeks of continuous computation, and gave fairly good representations of the ultimate state of the post-collision body or bodies but at best crude and qualitative information about individual particles in orbit. During the last two years an improved SPH program was used in which the masses and smoothing lengths of the particles are variable, and the intent of the current series of computations is to investigate the behavior of the matter exterior to the main parts of the body or bodies subsequent to the collisions. These runs are taking times comparable to a year of continuous computation in each case; they use 10,000 particles with 5,000 particles in the target and 5,000 in the impactor, and the particles thus have variable masses and smoothing lengths (the latter are dynamically adjusted so that a particle typically overlaps a few tens of its neighbors). Since the matter in the impactor provides the majority of the mass left in orbit after the collision, and since the masses of the particles that originated in the impactor are smaller than those in the target, the mass resolution in the exterior parts of the problem is greatly improved and the exterior particles properly simulate atmospheres in hydrostatic equilibrium.

Cameron, A. G. W.↗
NASA NTRS1986

Development of passive radiation detectors of improved sensitivity

The future development of a solid track high energy particle detector is discussed. The goal is to improve the sensitivity and lower the threshold of the detector. One most widely used material for such purpose is a plastic commercially known as CR-39. A scheme is presented which involves changing the formula of the monomer, diethylene glycol-bis-allyl carbonate. This is to be accomplished by substituting some heteroatoms for H and substituting sulfur atoms for oxygen in the ether linkages. Use of a new plasticizer to make the etched surface clearer than what has been accomplished as of today is suggested. Possible improvement in acquiring better tracks and increasing the ratio of V sub T/V sub B was planned. This is to be accomplished by changing the composition of the etchants, etching time, and etching temperature.

Chakrabarty, M. R.↗
DOE OSTI2025

Machine Learning for Anomaly Detection in Neural Network Security and SRF Cavities

This dissertation explores the development and deployment of machine learning approaches to address critical challenges in anomaly detection across two distinct domains: neural network security in federated learning settings and cavity behavior analysis in particle accelerator operations at Jefferson Lab in Newport News, Virginia. Anomaly detection identifies deviations from expected patterns, safeguarding systems in cybersecurity, industry, and research against malicious activities and failures. This dissertation demonstrates how our machine learning approaches enhance detection accuracy and efficiency in both neural network security and industrial applications. First, we investigate vulnerabilities in deep neural networks deployed in federated learning. Although federated learning preserves user privacy by training models locally, it remains vulnerable to backdoor attacks, in which malicious participants embed hidden triggers that induce targeted misbehavior. We propose a self-supervised contrastive learning framework to detect and mitigate such backdoor attacks. In our experiments, this method achieves higher detection accuracy and lower false positive rates than existing defenses, while operating without access to local model updates or original training data and thus preserving the privacy guarantees of the federated setting. Second, we address the operational reliability of superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF). Our research leverages an unsupervised learning approach, combined with Principal Component Analysis (PCA) and k-means clustering, to identify anomalous behaviors in SRF cavities. Our method detects subtle anomalous behavior by analyzing SRF signal data. This knowledge allows for the early detection and resolution of potential faults, significantly improving the efficiency and reliability of operations. Third, we extend these insights to time-series anomaly detection more broadly. We design a contrastive-learning based model tailored to increasingly dynamic environments and academic research. This model improves detection accuracy in settings that require real-time monitoring and predictive maintenance. Our research underscores the broader applicability and impact of advanced machine learning techniques in anomaly detection. By extracting meaningful patterns from complex data, machine learning can significantly enhance security in distributed neural networks and improve the efficiency of particle accelerator operations. This dissertation serves as a stepping stone for future investigations into the vast possibilities of anomaly detection, inspiring further exploration and development of machine learning techniques in this field.

Ferguson, Hal [Old Dominion University]↗
DOE OSTI2020

Improving inference with matrix elements and machine learning

Particle physics processes bring together a high-energy amplitude described by quantum field theory and nonperturbative effects and detector interactions described by complex computer simulations. We review some recently developed multivariate inference techniques that leverage this structure and combine matrix-element information with machine learning. Automated by the MadMiner package, the new techniques have been applied to multiple problems in particle physics, allowing for stronger limits than traditional analysis methods and showing their potential to improve the sensitivity of the LHC legacy measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Calibration of the charge and energy loss per unit length of the MicroBooNE liquid argon time projection chamber using muons and protons

In this paper, we describe a method used to calibrate the position- and time-dependent response of the MicroBooNE liquid argon time projection chamber anode wires to ionization particle energy loss. The method makes use of crossing cosmic-ray muons to partially correct anode wire signals for multiple effects as a function of time and position, including cross-connected TPC wires, space charge effects, electron attachment to impurities, diffusion, and recombination. The overall energy scale is then determined using fully-contained beam-induced muons originating and stopping in the active region of the detector. Using this method, we obtain an absolute energy scale uncertainty of 2% in data. We use stopping protons to further refine the relation between the measured charge and the energy loss for highly-ionizing particles. This data-driven detector calibration improves both the measurement of total deposited energy and particle identification based on energy loss per unit length as a function of residual range. As an example, the proton selection efficiency is increased by 2% after detector calibration.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2007

Photocatalytic/Magnetic Composite Particles

Photocatalytic/magnetic composite particles have been invented as improved means of exploiting established methods of photocatalysis for removal of chemical and biological pollutants from air and water. The photocatalytic components of the composite particles are formulated for high levels of photocatalytic activity, while the magnetic components make it possible to control the movements of the particles through the application of magnetic fields. The combination of photocatalytic and magnetic properties can be exploited in designing improved air- and water treatment reactors.

Wu, Chang-Yu↗
DOE OSTI2024

Enhanced Methanol Synthesis from CO 2 Hydrogenation Achieved by Tuning the Cu–ZnO Interaction in ZnO/Cu 2 O Nanocube Catalysts Supported on ZrO 2 and SiO 2

The nature of the Cu–Zn interaction and especially the role of Zn in Cu/ZnO catalysts used for methanol synthesis from CO 2 hydrogenation are still debated. Migration of Zn onto the Cu surface during reaction results in a Cu–ZnO interface, which is crucial for the catalytic activity. However, whether a Cu–Zn alloy or a Cu–ZnO structure is formed and the transformation of this interface under working conditions demand further investigation. Here, ZnO/Cu 2 O core–shell cubic nanoparticles with various ZnO shell thicknesses, supported on SiO 2 or ZrO 2 were prepared to create an intimate contact between Cu and ZnO. The evolution of the catalyst’s structure and composition during and after the CO 2 hydrogenation reaction were investigated by means of operando spectroscopy, diffraction, and ex situ microscopy methods. The Zn loading has a direct effect on the oxidation state of Zn, which, in turn, affects the catalytic performance. High Zn loadings, resulting in a stable ZnO catalyst shell, lead to increased methanol production when compared to Zn-free particles. Low Zn loadings, in contrast, leading to the presence of metallic Zn species during reaction, showed no significant improvement over the bare Cu particles. Therefore, our work highlights that there is a minimum content of Zn (or optimum ZnO shell thickness) needed to activate the Cu catalyst. Furthermore, in order to minimize catalyst deactivation, the Zn species must be present as ZnO x and not metallic Zn or Cu–Zn alloy, which is undesirably formed during the reaction when the precatalyst ZnO overlayer is too thin.

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

Structural and chemical evolutions of a magnesium vanadium oxide cathode under electrochemical cycling in magnesium batteries

The design of cathode materials that remain chemically and structurally stable during repetitive ion insertion and extraction poses a significant challenge in developing multivalent batteries. The cycling stability of traditional metal oxide-based cathode is challenged by sluggish diffusion of multivalent cations and parasitic reactivity at interfacial regimes, including the cathode electrolyte interphase layer (CEI). Understanding the reactions at the cathode-electrolyte interface, particularly those induced by non-stoichiometric surface layers, is a crucial design parameter for both cathode materials and electrolytes. Here, in this study, we employed multimodal analysis, including in situ and ex situ X-ray photoelectron spectroscopy (XPS), high resolution transmission electron microscopy (TEM) and electrochemical impedance spectroscopy (EIS) to examine the surface reactions and subsequent structural and chemical evolutions of the CEI on high voltage magnesium vanadium oxide (MgV 2 O 4 ) spinel cathode during the Mg 2+ insertion/extraction processes. The results revealed that the presence of non-stoichiometric surface layers in the magnesium vanadium oxide cathode drive the decomposition of bis(trifluoromethanesulfonyl)imide (TFSI - ) anion, leading to the formation of the CEI layer. The CEI layer could inhibit the Mg 2+ ion transfer processes. Accompanying this reactivity-driven degradation, the magnesium vanadium oxide cathode undergoes pulverization, forming clusters of nanosized particles. This process likely improves cycling ability by creating new intercalation sites and shortening the diffusion pathway for the Mg 2+ cations. This study demonstrates that controlling surface stoichiometry and engineering morphological properties are critical design parameters for high performance cathodes for multivalent batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

Weather aging effects on modified asphalt with rubber-polyethylene composites

Weather aging may cause more severe degradation on asphalt than thermal-oxidative aging due to the synergistic effect among oxygen, heat, ultraviolet (UV) radiation, and moisture. This study aimed to investigate weather aging effects and anti-aging mechanisms on asphalt modified with rubber-polyethylene (PE) composites. The modified binder blends and asphalt mixtures were subjected to outdoor weather aging. Dynamic shear rheometer (DSR), Fourier transform infrared spectroscopy (FTIR), Gel permeation chromatography (GPC), and optical microscopy tests were adopted to characterize the rheological properties, aging resistance, polymer degradation, and anti-aging mechanisms of modified binder blends, respectively. Mixture performance tests including Asphalt Pavement Analyzer (APA) and Ideal-CT tests were used to evaluate rutting and cracking resistance of asphalt mixtures. Results showed that weather aging can cause more severe aging to asphalt binders than pressure aging vessel (PAV) due to the severe degradation of PE particles. Rubber-PE composites alloyed with an extruder proved to stabilize PE particles in asphalt and significantly improve the aging resistance of modified binder blends. Furthermore, the enhanced aging resistance is attributed to the dispersion of PE particles and carbon black released by soluble rubbers.

Aging resistance↗
DOE OSTI2021

Characterization of hot-pressed von Alpen type NASICON ceramic electrolytes

The Na-ion conducting solid electrolyte NASICON is a promising solid state electrolyte (SSE) for use in Na based electrochemical systems. The effects of particle morphology and synthesis of von Alpen type NASICON via hot-pressing were investigated. Spray dried particles were shown to improve mechanical and electrochemical properties. X-ray diffraction, scanning electron microscopy, impulse excitation measurements, Vickers hardness, and impedance spectroscopy were used to correlate relationships between phase purity, microstructure, mechanical properties, and electrochemical properties. Scanning electron microscopy showed the presence of a glass phase as between 19.08% and 28.23% area percentage and a ZrO 2 phase between 0.46% and 3.51% area percentage in the hot-pressed samples. Impulse excitation showed elastic modulus varying from 83.65 to 97.65 GPa. The first values of Poisson's ratio and shear modulus of NASICON are reported as between 0.23 and 0.26 and 33.87 to 38.79 GPa, respectively. Vickers hardness and fracture toughness measurements showed Vickers hardness ranging from 4.30 to 4.68 GPa and fracture toughness ranging from 1.05 to 1.09 MPa m ½ . Impedance spectroscopy showed grain conductivities ranging from 1.023 to 1.287 mS/cm, with grain boundary resistance percentages between 73.22 and 47.5%. Total conductivities ranged from 0.292 to 0.596 mS/cm, with 0.596 mS/cm being achieved at room temperature for the spray dried powders with lower grain boundary resistance percentages.

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

Synthetic antibodies against BRIL as universal fiducial marks for single-particle cryoEM structure determination of membrane proteins

We propose the concept of universal fiducials based on a set of pre-made semi-synthetic antibodies (sABs) generated by customized phage display selections against the fusion protein BRIL, an engineered variant of apocytochrome b562a. These sABs can bind to BRIL fused either into the loops or termini of different GPCRs, ion channels, receptors and transporters without disrupting their structure. A crystal structure of BRIL in complex with an affinity-matured sAB (BAG2) that bound to all systems tested delineates the footprint of interaction. Negative stain and cryoEM data of several examples of BRIL-membrane protein chimera highlight the effectiveness of the sABs as universal fiducial marks. Taken together with a cryoEM structure of sAB bound human nicotinic acetylcholine receptor, this work demonstrates that these anti-BRIL sABs can greatly enhance the particle properties leading to improved cryoEM outcomes, especially for challenging membrane proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Fluid and gyrokinetic turbulence in open field-line, helical plasmas

Two-fluid Braginskii codes have simulated open-field line turbulence for over a decade, and only recently, it has become possible to study these systems with continuum gyrokinetic codes. This work presents a first-of-its-kind comparison between fluid and (long-wavelength) gyrokinetic models in open field-lines, using the GDB and Gkeyll codes to simulate interchange turbulence in the Helimak device at the University of Texas [T. N. Bernard et al., Phys. Plasmas 26, 042301 (2019)]. Partial agreement is attained in a number of diagnostic channels when the GDB sources and sheath boundary conditions (BCs) are selected carefully, especially the heat-flux BCs that can drastically alter the temperature. The radial profile of the fluctuation levels is qualitatively similar and quantitatively comparable on the low-field side, although statistics such as moments of the probability density function and the high-frequency spectrum show greater differences. This comparison indicates areas for future improvement in both simulations, such as sheath BCs, and improvements in GDB like particle conservation and spatially varying thermal conductivity, in order to achieve better fluid-gyrokinetic agreement and increase fidelity when simulating experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Exotic Meson Photoproduction at GlueX – Search for the hybrid candidate Y

Understanding the hadron spectrum is one of the primary goals of non-perturbative QCD. Many predictions have experimentally been confirmed, others still remain under experimental investigation. Of particular interest is how gluonic excitations give rise to states with constituent glue. One class of such states are hybrid mesons that are predicted by theoretical models and Lattice QCD calculations. Searching for and understanding the nature of these states is a primary physics goal of the GlueX experiment at the CEBAF accelerator at Jefferson Lab. A search for a JPC = 1-- hybrid meson candidate, the Y (2175), in phi(1020)pi+pi+ and phi(1020)f0(980) channels in photoproduction on a proton target has been conducted. A first measurement of non-resonant phi(1020)pi+pi+ and phi(1020)f0(980) total cross sections in photoproduction has been performed. An upper limit on the resonance production cross section for the Y (2175) -> phi(1020)pi+pi+ and Y (2175) -> phi(1020)f0(980) channels are estimated. Since the analysis essentially depends on the quality of the charged kaon identification, also an optimization of particle identification through an improvement of the energy loss estimation in the CDC by a truncated mean method has been investigated.

Hamdi, Abdennacer↗
DOE OSTI2021

Secondary Aerosol Formation in an Arctic Oil Field (Campaign Report)

Atmospheric aerosols contribute significantly to arctic warming, yet significant differences in aerosol concentration levels and seasonal cycles often exist between models and observations. Recent studies of cloud properties across the North Slope of Alaska show the significant, regional influence of oil field emissions. Development across the Arctic motivates the need to characterize these oilfield emissions to further predict their roles in changing future arctic climate. Our previous August-September 2016 Atmospheric Radiation Measurement (ARM) user facility field campaign resulted in improved understanding of atmospheric particles emitted within the North Slope of Alaska (NSA) oil fields, as well as the aging of sea spray aerosol. Following Polar Sunrise during arctic spring, chlorine chemistry is active, and we hypothesize that oxidation of oil field hydrocarbons by chlorine atoms (Cl) generates oxygenated volatile organic compounds (OVOCs) leading to springtime arctic secondary organic aerosol (SOA) formation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

3D-Reconstruction of Tau Neutrinos in LArTPC Detectors

The Deep Underground Neutrino Experiment (DUNE) is a next-generation neutrino experiment currently under construction. DUNE will consist of two high-resolution neutrino interaction imaging detectors exposed to the world’s most intense neutrino beam, with the Near Detector at Fermilab and the Far Detector 1,300 km away in the Sanford Underground Research Facility in South Dakota, US. The high statistics and excellent resolution capabilities of DUNE's $^{40}$Ar detector will allow us to make precision studies of oscillation parameters capable of searching for CP violation in the lepton sector, testing interaction models, and studying phenomena that have until now, seemed too complex to measure, like $\nu_\tau$ detection and therefore, providing the completion of the 3-flavor neutrino paradigm. Knowledge of the $\nu_\tau$ detection can impact a broad spectrum of open questions. These include searching for non-standard neutrino interactions, constraining the unitarity of the PMNS matrix, searching for sterile neutrinos, and studying neutrino interactions. In the case of LArTPC data, the detector hits can be considered nodes in a graph, and the edges represent the spatial and temporal relationships between them. By using graph neural networks, it is possible to exploit these relationships and improve the accuracy of particle identification and reconstruction. During my presentation and specifically for tau neutrino reconstruction, I will show the effectiveness and reliability of our in-house developed graph neural network (GNN), NuGraph. This GNN classifies detector hits based on the particle type responsible for their production, assuring that the system accurately identifies and categorizes information based on its unique characteristics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗