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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 145 records · Page 8

Boron Nitride Nanotube: Synthesis and Applications

Scientists have predicted that carbon's immediate neighbors on the periodic chart, boron and nitrogen, may also form perfect nanotubes, since the advent of carbon nanotubes (CNTs) in 1991. First proposed then synthesized by researchers at UC Berkeley in the mid 1990's, the boron nitride nanotube (BNNT) has proven very difficult to make until now. Herein we provide an update on a catalyst-free method for synthesizing highly crystalline, small diameter BNNTs with a high aspect ratio using a high power laser under a high pressure and high temperature environment first discovered jointly by NASA/NIA JSA. Progress in purification methods, dispersion studies, BNNT mat and composite formation, and modeling and diagnostics will also be presented. The white BNNTs offer extraordinary properties including neutron radiation shielding, piezoelectricity, thermal oxidative stability (> 800 C in air), mechanical strength, and toughness. The characteristics of the novel BNNTs and BNNT polymer composites and their potential applications are discussed.

Tiano, Amanda L.↗

Evaluating causal‐based feature selection for fuel property prediction models

Abstract In‐silico screening of novel biofuel molecules based on chemical and fuel properties is a critical first step in the biofuel evaluation process due to the significant volumes of samples required for experimental testing, the destructive nature of engine tests, and the costs associated with bench‐scale synthesis of novel fuels. Predictive models are limited by training sets of few existing measurements, often containing similar classes of molecules that represent just a subset of the potential molecular fuel space. Software tools can be used to generate every possible molecular descriptor for use as input features, but most of these features are largely irrelevant and training models on datasets with higher dimensionality than size tends to yield poor predictive performance. Feature selection has been shown to improve machine learning models, but correlation‐based feature selection fails to provide scientific insight into the underlying mechanisms that determine structure–property relationships. The implementation of causal discovery in feature selection could potentially inform the biofuel design process while also improving model prediction accuracy and robustness to new data. In this study, we investigate the benefits causal‐based feature selection might have on both model performance and identification of key molecular substructures. We found that causal‐based feature selection performed on par with alternative filtration methods, and that a structural causal model provides valuable scientific insights into the relationships between molecular substructures and fuel properties.

Nguyen, Bernard↗

Mechanistic insight of KBiQ 2 (Q = S, Se) using panoramic synthesis towards synthesis-by-design

Solid-state synthesis has historically focused on reactants and end products; however, knowledge of reaction pathways, intermediate phases and their formation may provide mechanistic insight of solid-state reactions. With an increased understanding of reaction progressions, design principles can be deduced, affording more predictive power in materials synthesis. In pursuit of this goal, in situ powder X-ray diffraction is employed to observe crystalline phase evolution over the course of the reaction, thereby constructing a “panoramic” view of the reaction from beginning to end. We conducted in situ diffraction studies in the K–Bi–Q (Q = S, Se) system to understand the formation of phases occurring in this system in the course of their reactions. Powder mixtures of K 2 Q to Bi 2 Q 3 in 1:1 and 1.5:1 ratios were heated to 800 °C or 650 °C, while simultaneously collecting diffraction data. Three new phases, K 3 BiS 3 , β-KBiS 2 , and β-KBiSe 2 , were discovered. Panoramic synthesis showed that K 3 BiQ 3 serves an important mechanistic role as a structural intermediate in both chalcogen systems (Q = S, Se) in the path to form the KBiQ 2 structure. Thermal analysis and calculations at the density functional theory (DFT) level show that the cation-ordered β-KBiQ 2 polymorphs are the thermodynamically stable phase in this compositional space, while Pair Distribution Function (PDF) analysis shows that all α-KBiQ 2 structures have local disorder due to stereochemically active lone pair expression of the bismuth atoms. The formation of the β-KBiQ 2 structures, both of which crystallize in the α-NaFeO 2 structure type, show a boundary where the structure can be disordered or ordered with regards to the alkali metal and bismuth. A cation radius tolerance for six-coordinate cation site sharing of ($\frac{r^+}{r^{3+}}$) ~ 1.3 is proposed. The mechanistic insight the panoramic synthesis technique provides in the K–Bi–Q system is progress towards the overarching goal of synthesis-by-design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Materials synthesis at terapascal static pressures

Theoretical modelling predicts very unusual structures and properties of materials at extreme pressure and temperature conditions. Hitherto, their synthesis and investigation above 200 gigapascals have been hindered both by the technical complexity of ultrahigh-pressure experiments and by the absence of relevant in situ methods of materials analysis. Here we report on a methodology developed to enable experiments at static compression in the terapascal regime with laser heating. We apply this method to realize pressures of about 600 and 900 gigapascals in a laser-heated double-stage diamond anvil cell, producing a rhenium–nitrogen alloy and achieving the synthesis of rhenium nitride Re 7 N 3 —which, as our theoretical analysis shows, is only stable under extreme compression. Full chemical and structural characterization of the materials, realized using synchrotron single-crystal X-ray diffraction on microcrystals in situ, demonstrates the capabilities of the methodology to extend high-pressure crystallography to the terapascal regime.

36 MATERIALS SCIENCE↗

Microkinetic insights into the role of catalyst and water activity on the nucleation, growth, and dissolution during COF-5 synthesis

The chemical pathway for synthesizing covalent organic frameworks (COFs) involves a complex medley of reaction sequences over a rippling energy landscape that cannot be adequately described using existing theories. Even with the development of state-of-the-art experimental and computational tools, identifying primary mechanisms of nucleation and growth of COFs remains elusive. Other than empirically, little is known about how the catalyst composition and water activity affect the kinetics of the reaction pathway. In this work, for the first time, we employ time-resolved in situ Fourier transform infrared spectroscopy (FT-IR) coupled with a six-parameter microkinetic model consisting of ~10 million reactions and over 20 000 species. The integrated approach elucidates previously unrecognized roles of catalyst pK a on COF yield and water on growth rate and size distribution. COF crystalline yield increases with decreasing pK a of the catalysts, whereas the effect of water is to reduce the growth rate of COF and broaden the size distribution. The microkinetic model reproduces the experimental data and quantitatively predicts the role of synthesis conditions such as temperature, catalyst, and precursor concentration on the nucleation and growth rates. Furthermore, the model also validates the second-order reaction mechanism of COF-5 and predicts the activation barriers for classical and non-classical growth of COF-5 crystals. The microkinetic model developed here is generalizable to different COFs and other multicomponent systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identification of structural interface characteristics using component mode synthesis

The inability to adequately model connections has limited the ability to predict overall system dynamic response. Connections between structural components are often mechanically complex and difficult to accurately model analytically. Improved analytical models for connections are needed to improve system dynamic predictions. This study explores combining Component Mode synthesis methods for coupling structural components with Parameter Identification procedures for improving the analytical modeling of the connections. Improvements in the connection properties are computed in terms of physical parameters so the physical characteristics of the connections can be better understood, in addition to providing improved input for the system model. Two sample problems, one utilizing simulated data, the other using experimental data from a rotor dynamic test rig are presented.

Huckelbridge, A. A.↗

Identification of structural interface characteristics using component mode synthesis

The inability to adequately model connections has limited the ability to predict overall system dynamic response. Connections between structural components are often mechanically complex and difficult to accurately model analytically. Improved analytical models for connections are needed to improve system dynamic predictions. This study explores combining Component Mode synthesis methods for coupling structural components with Parameter Identification procedures for improving the analytical modeling of the connections. Improvements in the connection properties are computed in terms of physical parameters so the physical characteristics of the connections can be better understood, in addition to providing improved input for the system model. Two sample problems, one utilizing simulated data, the other using experimental data from a rotor dynamic test rig, are presented.

Huckelbridge, A. A.↗

Identification of structural interface characteristics using component mode synthesis

The inability to adequately model connections has limited the ability to predict overall system dynamic response. Connections between structural components are often mechanically complex and difficult to accurately model analytically. Improved analytical models for connections are needed to improve system dynamic predictions. This study explores combining Component Mode synthesis methods for coupling structural components with Parameter Identification procedures for improving the analytical modeling of the connections. Improvements in the connection properties are computed in terms of physical parameters so the physical characteristics of the connections can be better understood, in addition to providing improved input for the system model. Two sample problems, one utilizing simulated data, the other using experimental data from a rotor dynamic test rig, are presented.

Huckelbridge, A. A.↗

Hot Hydride Superconductivity Above 550 K

The search for room temperature superconductivity has accelerated in the last few years driven by experimentally accessible theoretical predictions that indicated alloying dense hydrogen with other elements could produce conventional superconductivity at high temperatures and pressures. These predictions helped inform the synthesis of simple binary hydrides that culminated in the discovery of the superhydride LaH 10 with a superconducting transition temperature T c of 260 K at 180 GPa. We have now successfully synthesized a metallic La-based superhydride with an initial T c of 294 K. When subjected to subsequent thermal excursions that promoted a chemical reaction to a higher order system, the Tc onset was driven irreversibly to 556 K. X-ray characterization confirmed the formation of a distorted LaH 10 based backbone that suggests the formation of ternary or quaternary compounds with substitution at the La and/or H sites. The results provide evidence for hot superconductivity, aligning with recent predictions for higher order hydrides under pressure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Titrating Controlled Defects into Si-LTA Zeolite Crystals Using Multiple Organic Structure-Directing Agents

Controlling defects in zeolites is crucial for tuning their adsorption and catalytic properties. In this work, we have performed an integrated zeolite synthesis, spectroscopy, and density functional theory study to test the limit of F– as a charge-balancing agent that mitigates defects in siliceous zeolites. We focused on the synthesis of siliceous zeolite LTA at 150 °C with 1,2-dimethyl-3-(4-methylbenzyl) imidazolium as the primary organic structure-directing agent (OSDA) and tetramethyl ammonium (TMA) as the secondary OSDA. By varying the amount of TMA in the synthesis gel, positive charges were titrated into the resulting as-made Si-LTA. Surprisingly, we found that greater TMA concentration does not induce more F– to enter into the zeolite. 29Si solid-state MAS NMR, Raman spectroscopy, and density functional theory suggest that this system has surpassed its capacity for F– to balance OSDA charge, and additional positive charge is balanced by Si–O– framework defects. The number of defects in the as-made Si-LTA can be precisely titrated by the amount of TMA in the zeolite structures. For the Si-LTA synthesized without TMA, framework defects formed in the early stage of crystal growth were found to heal during later crystallization, leading to defect-free Si-LTA. However, for the Si-LTA synthesized with TMA, the defects formed in early stages do not heal. A DFT thermodynamic analysis explains that crowding of Si-LTA pores by TMA impedes defect healing; this prediction is corroborated by synthesis experiments at an elevated temperature (170 °C). These results indicate that F– can have a limited capacity to balance OSDA charge in zeolite synthesis, opening up a third route to zeolite synthesis intermediate between the fluoride and hydroxide routes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CoordNet: Data Generation and Visualization Generation for Time-Varying Volumes via a Coordinate-Based Neural Network

Although deep learning has demonstrated its capability in solving diverse scientific visualization problems, it still lacks generalization power across different tasks. To address this challenge, we propose CoordNet, a single coordinate-based framework that tackles various tasks relevant to time-varying volumetric data visualization without modifying the network architecture. The core idea of our approach is to decompose diverse task inputs and outputs into a unified representation (i.e., coordinates and values) and learn a function from coordinates to their corresponding values. We achieve this goal using a residual block-based implicit neural representation architecture with periodic activation functions. We evaluate CoordNet on data generation (i.e., temporal super-resolution and spatial super-resolution) and visualization generation (i.e., view synthesis and ambient occlusion prediction) tasks using time-varying volumetric data sets of various characteristics. Here, the experimental results indicate that CoordNet achieves better quantitative and qualitative results than the state-of-the-art approaches across all the evaluated tasks. Source code and pre-trained models are available at https://github.com/stevenhan1991/CoordNet.

97 MATHEMATICS AND COMPUTING↗

Allometric Trophic Networks From Individuals to Socio-Ecosystems: Consumer–Resource Theory of the Ecological Elephant in the Room

A well-known parable is that of the blind men studying an elephant each of which assert the elephant is the part they first hold in their hands, e.g., “rope!” says the tail holder while the leg holder asserts “tree!” The various subdisciplines of ecology appear similar in that we each engage in our enthusiastic but at least somewhat myopic study with remarkably limited agreement or even discussion about the overall system which we all study. Allometric trophic network (ATN) theory offers a path out of this dilemma by integrating across scales, taxa, habitats and organizational levels from physiology to ecosystems based on consumer-resource interactions among co-existing organisms. The network architecture and the metabolic and behavioral processes that determine the structure and dynamics of these interactions form the first principles of ATN theory, which in turn provides a synthetic overview and powerfully predictive framework for ecology from organisms to ecosystems. Beyond ecology, ATN theory also synthesizes eco-evolutionary and socio-ecological research still largely based on consumer-resource mechanisms but respectively integrated with different processes including natural selection and market mechanisms. This paper briefly describes foundations, advances, and future directions of ATN theory including predicting an ecosystem’s phenotype from its community’s genotype in order to accelerate more predictive and unified understanding of the complex systems studied by ecologists and other environmental scientists.

54 ENVIRONMENTAL SCIENCES↗

Infrared photometry of the semistellar nucleus of M31

New broad-band infrared JHK data and narrow-band CO and H2O indices for the semistellar nucleus of M31 are presented. The data were obtained specifically to test a prediction of a recent synthesis model by Faber and French in which the ratio of dwarf-to-giant light increases strongly in going from the bulge to the nucleus of M31. The new infrared data do not support such a model. Some alternative explanations for the behavior of the various indices are given, but the apparent conflict between the Faber-French interpretation of the strength of the Na I 8190 A feature and our data is not satisfactorily resolved.

Persson, S. E.↗

Hypersonic Airbreathing Vehicles/Technologies

Hypersonic airbreathing horizontal takeoff and landing (HTOL) vehicles are highly integrated systems involving many advanced technologies. The design environment is variable rich, intricately networked, and sensitivity intensive; as such, it represents a tremendous challenge. Creating a viable design requires addressing three main elements: (1) an understanding of the 'figures of merit' and their relationship, (2) the development of sophisticated configuration discipline prediction methods and a synthesis procedure, and (3) the synergistic integration of advanced technologies across the discipline spectrum. This paper will focus on the vision for hypersonic airbreathing vehicles and the advanced technologies that forge the designs. Airbreathing hypersonics encompass endoatmospheric (airplanes...missiles are a part of the matrix but will not be included in this paper since they are an air force focus) and space access vehicles with speed from Mach 4 up to Mach 25 (orbital). These vehicles can be divided into two classes...cruisers and accelerators. The cruiser designs reflect high lift-to-drag whereas the accelerators reflect low drag per unit inlet capture; thus, the cross section of the accelerator attributes a much larger percentage to propulsion. One of the more design influencing items is fuel. The hydrogen fueled vehicles must be very volumetric efficient to contain the low density fuel and thus tend to be a bit bulgy (more conducive to lifting bodies or wing bodies) whereas with hydrocarbon fueled vehicles, the concern is loading because of the high density fuel; thus, they may tend to be more towards waveriders which are not usually very volumetric efficient. Hydrocarbon fuels (endothermic) are limited in their engine cooling capacity to below Mach 8.

Hunt, James L.↗

An Overview of Virtual Acoustic Simulation of Aircraft Flyover Noise

Methods for testing human subject response to aircraft flyover noise have greatly advanced in recent years as a result of advances in simulation technology. Capabilities have been developed which now allow subjects to be immersed both visually and aurally in a three-dimensional, virtual environment. While suitable for displaying recorded aircraft noise, the true potential is found when synthesizing aircraft flyover noise because it allows the flexibility and freedom to study sounds from aircraft not yet flown. A virtual acoustic simulation method is described which is built upon prediction-based source noise synthesis, engineering-based propagation modeling, and empirically-based receiver modeling. This source-path-receiver paradigm allows complete control over all aspects of flyover auralization. With this capability, it is now possible to assess human response to flyover noise by systematically evaluating source noise reductions within the context of a system level simulation. Examples of auralized flyover noise and movie clips representative of an immersive aircraft flyover environment are made in the presentation.

Rizzi, Stephen A.↗

FUV Emission from AGB Stars: Modeling Accretion Activity Associated with a Binary Companion

It is widely believed that the late stages of evolution for Asymptotic Giant Branch (AGB) stars are influenced by the presence of binary companions. Unfortunately, there is a lack of direct observational evidence of binarity. However, more recently, strong indirect evidence comes from the discovery of UV emission in a subsample of these objects (fuvAGB stars). AGB stars are comparatively cool objects (< or =3000 K), thus their fluxes falls off drastically for wavelengths 3000 Angstroms and shorter. Therefore, ultraviolet observations offer an important, new technique for detecting the binary companions and/or associated accretion activity. We develop new models of UV emission from fuvAGB stars constrained by GALEX photometry and spectroscopy of these objects. We compare the GALEX UV grism spectra of the AGB M7 star EY Hya to predictions using the spectral synthesis code Cloudy, specifically investigating the ultraviolet wavelength range (1344-2831 Angstroms). We investigate models composed of contributions from a photoionized "hot spot" due to accretion activity around the companion, and "chromospheric" emission from collisionally ionized plasma, to fit the UV observations.

ultraviolet emission↗

The NuSTAR Extragalactic Surveys: The Number Counts Of Active Galactic Nuclei And The Resolved Fraction Of The Cosmic X-ray Background

We present the 3-8 kiloelectronvolts and 8-24 kiloelectronvolts number counts of active galactic nuclei (AGNs) identified in the Nuclear Spectroscopic Telescope Array (NuSTAR) extragalactic surveys. NuSTAR has now resolved 33 percent -39 percent of the X-ray background in the 8-24 kiloelectronvolts band, directly identifying AGNs with obscuring columns up to approximately 10 (exp 25) per square centimeter. In the softer 3-8 kiloelectronvolts band the number counts are in general agreement with those measured by XMM-Newton and Chandra over the flux range 5 times 10 (exp -15) less than or approximately equal to S (3-8 kiloelectronvolts) divided by ergs per second per square centimeter less than or approximately equal to 10 (exp -12) probed by NuSTAR. In the hard 8-24 kiloelectronvolts band NuSTAR probes fluxes over the range 2 times 10 (exp -14) less than or approximately equal to S (8-24 kiloelectronvolts) divided by ergs per second per square centimeter less than or approximately equal to 10 (exp -12), a factor approximately 100 times fainter than previous measurements. The 8-24 kiloelectronvolts number counts match predictions from AGN population synthesis models, directly confirming the existence of a population of obscured and/or hard X-ray sources inferred from the shape of the integrated cosmic X-ray background. The measured NuSTAR counts lie significantly above simple extrapolation with a Euclidian slope to low flux of the Swift/BAT15-55 kiloelectronvolts number counts measured at higher fluxes (S (15-55 kiloelectronvolts) less than or approximately equal to 10 (exp -11) ergs per second per square centimeter), reflecting the evolution of the AGN population between the Swift/BAT local (redshift is less than 0.1) sample and NuSTAR's redshift approximately equal to 1 sample. CXB (Cosmic X-ray Background) synthesis models, which account for AGN evolution, lie above the Swift/BAT measurements, suggesting that they do not fully capture the evolution of obscured AGNs at low redshifts

nucle↗