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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Experimental and Numerical Study of Ammonium Perchlorate Counterflow Diffusion Flames

Many solid rocket propellants are based on a composite mixture of ammonium perchlorate (AP) oxidizer and polymeric binder fuels. In these propellants, complex three-dimensional diffusion flame structures between the AP and binder decomposition products, dependent upon the length scales of the heterogeneous mixture, drive the combustion via heat transfer back to the surface. Changing the AP crystal size changes the burn rate of such propellants. Large AP crystals are governed by the cooler AP self-deflagration flame and burn slowly, while small AP crystals are governed more by the hot diffusion flame with the binder and burn faster. This allows control of composite propellant ballistic properties via particle size variation. Previous measurements on these diffusion flames in the planar two-dimensional sandwich configuration yielded insight into controlling flame structure, but there are several drawbacks that make comparison with modeling difficult. First, the flames are two-dimensional and this makes modeling much more complex computationally than with one-dimensional problems, such as RDX self- and laser-supported deflagration. In addition, little is known about the nature, concentration, and evolution rates of the gaseous chemical species produced by the various binders as they decompose. This makes comparison with models quite difficult. Alternatively, counterflow flames provide an excellent geometric configuration within which AP/binder diffusion flames can be studied both experimentally and computationally.

Smooke, M. D.↗
DOE OSTI2024

Implementation of new mixture rules has a substantial impact on combustion predictions for H 2 and NH 3

Complex-forming reactions comprise a substantial fraction of all important combustion reactions and are central to combustion behavior. Despite being often called “pressure-dependent” reactions, their rate constants depend on not only the pressure but also the composition. While modern combustion codes allow arbitrarily high accuracy in treating pressure dependence, recent work has consistently demonstrated dramatic failures of essentially all available treatments of mixture dependence. In situations where mixture dependence is treated at all, it is inevitably treated through specification of pressure-dependent rate constants for a set of pure bath gases, which are then combined to estimate the rate constant in a mixture via a “mixture rule.” While there had been a generally unquestioning confidence in these mixture rules, they had, in reality, been scarcely tested until the last decade, when comparisons against master equation calculations revealed order-of-magnitude errors for important pressure-dependent reactions. New mixture rules, based on the reduced pressure, have recently been proposed and shown to reproduce master equation calculations for broad classes of complex-forming reactions very accurately. Here, in this work, we present an implementation of one such new mixture rule (“LMR-R”) in Cantera and then use it to enable simulations that use new high-accuracy ab initio data for individual bath gases (for the first time, since codes previously could not accommodate the complex bath gas dependence). Demonstrations focus on combustion of H 2 and NH 3 , where (1) high-accuracy ab initio data are available and (2) the impact is expected to be large due to the high fractions of efficient colliders (e.g., H 2 O and NH 3 ) in the burned and unburned gases. Indeed, we find the impact of this treatment to be substantial and may explain previous modeling difficulties for these important carbon-free fuels, particularly for NH 3 , whose extraordinarily high third-body efficiency (~20) is often omitted from kinetic models.

Ammonia↗
DOE OSTI2020

Deep Learning Prediction of Interspecies Interactions from Self-organized Spatiotemporal Patterns of Co-evolving Organisms

Microorganisms colonizing natural habits such as soils co-evolve to form specific spatial patterns through interspecies interactions. These self-organized patterns are a key ecological phenotype, which provides critical information on their interaction mechanisms. However, conventional network inference techniques that analyze species population data in bulk have yet to be extended to account for such spatial heterogeneity. Here we proposed supervised deep learning as a new network inference tool for predicting interspecies interactions from spatiotemporal patterns of microbial evolution. Due to lack of biological imaging data that can be used for training deep learning networks, we used in silico data generated from high-fidelity agent-based models to determine model structure and parameters. Even though networks were trained under simple configurations where interaction coefficients are assumed to be spatially invariant, we demonstrated that the resulting model can be utilized to successfully predict spatial variation of interactions in more complex domains (i.e., configured with a context-dependent mixture of interaction coefficients) as well as in simple domains without further training. In the further test against real biological data obtained through imaging experiments of a binary consortium (Pseudomonas fluorescens and a mutant of Escherichia coli), our model also predicted the dramatic shifts in interactions of the two organisms across different environmental contexts. Through various successful demonstrations in this work, the combined use of the agent-based model and machine learning algorithm provides a means to use new type of data - microscopic images - for extracting microbial interactions, therefore presenting itself as a useful tool for the analysis of more complex microbial community interactions.

Lee, Joon-Yong↗
DOE OSTI2024

Selective laser sintering and spark plasma sintering of (Zr,Nb,Ta,Ti,W)C compositionally complex carbide ceramics

Abstract Two advanced manufacturing processes, spark plasma sintering (SPS) and selective laser sintering (SLS), have been developed for synthesis of (Zr,Nb,Ta,Ti,W)C compositionally complex carbide (CCC) via reactive sintering of a powder mixture of constitute monocarbides. X‐ray diffraction analysis confirmed that the single‐phase CCC can be formed by both SPS and SLS. While a homogenous microstructure with uniform metal element distributions was developed during SPS, three‐layer microstructures with a thin TiC‐rich layer and two TaC‐rich layers along with a TiO 2 ‐rich surface layer containing W nanoparticles were formed during SLS. In addition, cellular structures with W, Zr, and Ti element segregation and dislocations on cell boundaries were observed in the SLS‐CCC sample, indicating the effect of nonequilibrium conditions on microstructure formation during laser melting followed by rapid cooling and solidification process. Compared to the SPS‐CCC sample, the SLS‐CCC showed enhanced hardness and reduced thermal conductivity, which may be related to their unique cellular structures.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Method and Apparatus for Measuring Fluid Flow

The invention is a method and apparatus for monitoring the presence, concentration, and the movement of fluids. It is based on utilizing electromagnetic measurements of the complex permittivity of the fluids for detecting and monitoring the fluid. More particularly the apparatus uses one or more microwave probes which are placed at the locations where the measurements are to be made. A radio frequency signal is transmitted to the probe and the reflected signal is phase and amplitude detected at a rapid rate for the purpose of identifying the fluids, based on their dielectric constant at the probe. The apparatus can be used for multiple purposes including measures of flow rates, turbulence, dispersion, fluid identification, and changes in flow conditions of multiple fluids or multiple states of a single fluid in a flowline or a holding container. The apparatus includes a probe consisting of two electrical conductors separated by an insulator. A radio frequency signal is communicated to the probe and is reflected back from the portion of the probe exposed to the fluid. The radio frequency signal also provides a reference signal. An oscillator generates a second signal which combined with each of the reference signal and the reflected signal to produce signals of lower frequencies to facilitate filtering and amplifying those signals. The two signals are then mixed in a detector to produce an output signal that is representative of the phase and amplitude change caused by the reflection of the signal at the probe exposed to the fluid. The detector may be a dual phase detector that provides two such output signals that are in phase quadrature. A phase shifter may be provided for selectively changing the phase of the reference signal to improve the sensitivity of at least one of the output signals for more accurate readings and/or for calibration purposes. The two outputs that are in quadrature with respect to each other may be simultaneously monitored to account for drift errors. The output signals are digitized and provided to a computer at a sample rate which may be very high. The computer is operable to identify the fluid based on its complex permittivity as may be useful for identifying the flow rates, determining the fluid mixture ratio, detecting impurities in the fluid, and so forth. Novelty is believed to reside in the use of the real part of complex permittivity to measure small difference in permittivity of the fluid.

Arndt, G. Dickey↗
DOE OSTI2020

Fast predictions of liquid-phase acid-catalyzed reaction rates using molecular dynamics simulations and convolutional neural networks

The rates of liquid-phase, acid-catalyzed reactions relevant to the upgrading of biomass into high-value chemicals are highly sensitive to solvent composition and identifying suitable solvent mixtures is theoretically and experimentally challenging. We show that the complex atomistic configurations of reactant–solvent environments generated by classical molecular dynamics simulations can be exploited by 3D convolutional neural networks to enable accurate predictions of Brønsted acid-catalyzed reaction rates for model biomass compounds. We develop a 3D convolutional neural network, which we call SolventNet, and train it to predict acid-catalyzed reaction rates using experimental reaction data and corresponding molecular dynamics simulation data for seven biomass-derived oxygenates in water–cosolvent mixtures. We show that SolventNet can predict reaction rates for additional reactants and solvent systems an order of magnitude faster than prior simulation methods. This combination of machine learning with molecular dynamics enables the rapid, high-throughput screening of solvent systems and identification of improved biomass conversion conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Ion Transport in Batteries with Polymer Electrolytes

We discuss polymer electrolytes for use in rechargeable lithium batteries. Polymer electrolytes have the potential to enable batteries with lithium metal anodes. These batteries have significantly higher theoretical energy densities than current lithium-ion batteries. We consider binary mixtures of polymers and salts. We also cover more complex systems such as polymer electrolytes swollen with a solvent (gel polymer electrolytes) and microphase separated polymer electrolytes. By covalently attaching the anions to the chains in a polymer solid, one obtains a single-ion conductor. We mainly focus on experiments wherein the polymer electrolyte is placed between two lithium metal electrodes. These experiments enable the determination of three transport parameters, ionic conductivity, salt diffusion coefficient, and transference number, and the thermodynamic factor. The properties of dry polymer electrolytes are contrasted with those of gel polymer electrolytes. The gel systems exhibit higher conductivity while the dry systems exhibit superior mechanical properties. We discuss interfacial impedance when lithium metal is contacted with polymer electrolytes and the importance of coulombic efficiency.

Yu, Xiaopeng↗
DOE OSTI2020

In-situ synthesis of oxides by reactive process atmospheres during L-PBF of stainless steel

Traditionally, reactive gases such as oxygen (O 2 ) and carbon dioxide (CO 2 ) have been avoided during laser powder bed fusion (L-PBF) of metals and alloys based on the notion that it may lead to defect formation and poor properties. Here, in this work, we show that instead, these gases can be used to form sub-μm-sized oxide particles in-situ during the L-PBF process in an Fe-Cr-Al-Ti stainless steel and lead to improved room temperature and high-temperature mechanical properties. We manufactured cube samples using pure Ar and various reactive gas atmospheres, namely an O 2 /Argon (Ar) mixture containing 0.2 % O 2 and CO 2 /Ar mixtures containing up to 100 % CO 2 . Co-axial measurements of infrared radiation emitted from the melt pool showed correlation to the presence of O 2 or CO 2 in the gas mixture. Builds produced under CO 2 -containing atmosphere contained complex oxides with an average diameter of ~40 nm, an Al-rich core and a Ti-rich shell. Due to the high cooling rates typical to L-PBF, agglomeration of oxides and slag formation on the surface of the samples could almost be entirely avoided. Compression tests at temperatures up to 800 °C showed that the samples produced in 100 % CO 2 have about 20 % higher yield stress compared to samples produced in Ar. The paper concludes with a discussion of the formation mechanism of the observed oxides. Our results show that in-situ reactions during additive manufacturing processes are a promising pathway to the synthesis of particle-reinforced alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Techno-Economic and life cycle assessment of standalone Single-Stream material recovery facilities in the United states

Material Recovery Facilities (MRFs) are crucial players in achieving a circular economy. MRFs receive complex waste streams and separate valuable recyclables from these mixtures. This study conducts techno-economic analysis (TEA) to estimate the net present value (NPV) and life cycle assessment (LCA) to estimate different environmental impacts of a commercial scale standalone, single-stream MRF to assess the economic feasibility and environmental impacts of recovering valuable recyclables from an MRF processing 120,000 tonnes per year (t/y). The TEA employs a discounted cash flow rate of return (DCFROR) analysis over a 20-year facility lifetime, along with a sensitivity analysis on the impact of different operating and economic parameters. Results show that the total fixed cost of building the MRF facility is $\$ $23 MM, and the operating cost is $\$ $45.48/tonne. Further the NPV of the MRF can vary from $\$ $3.57 MM to $\$ $60 MM, while 100-year global warming potential can range from 5.98 to 8.53 kg carbon dioxide equivalents (CO2-eq) per tonne of MSW. We have also found that MSW composition (arising from regional effects) significantly impacts costs, 100-year global warming potential, and other impact categories such as acidification potential, eutrophication potential, ecotoxicity, ozone depletion, photochemical oxidation, carcinogenic effects, and non-carcinogenic effects. Sensitivity and uncertainty analysis indicate that waste composition and market prices significantly impact the profitability of the MRF, and the waste composition mostly impacts global warming potential. Our analysis also indicates that facility capacity, fixed capital cost, and waste tipping fees are vital parameters that affect the economic viability of MRF operations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Unraveling Local Structure of Molten Salts via X-ray Scattering, Raman Spectroscopy, and Ab Initio Molecular Dynamics

In this work, we resolve a long-standing issue concerning the local structure of molten MgCl 2 by employing a multimodal approach, including X-ray scattering and Raman spectroscopy, along with the theoretical modeling of the experimental spectra based on ab initio molecular dynamics (AIMD) simulations utilizing several density functional theory (DFT) methods. We demonstrate the reliability of AIMD simulations in achieving excellent agreement between the experimental and simulated spectra for MgCl 2 and 50 mol % MgCl 2 + 50 mol % KCl, and ZnCl 2 , thus allowing structural insights not directly available from experiment alone. A thorough computational analysis using five DFT methods provides a convergent view that octahedrally coordinated magnesium in pure MgCl 2 upon melting preferentially coordinates with five chloride anions to form distorted square pyramidal polyhedra that are connected via corners and to a lesser degree via edges. This is contrasted with the results for ZnCl 2 , which does not change its tetrahedral coordination on melting. Although the five-coordinate MgCl 5 3– complex was not considered in the early literature, together with an increasing tendency to form a tetrahedrally coordinated complex with decreasing the MgCl 2 content in the mixture with alkali metal chloride systems, current work reconciles the results of most previous seemingly contradictory experimental studies.

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

Unraveling pH-Dependent Changes in Adsorption Structure of Uranyl on Alumina (012)

Mitigating uranium transport in groundwater is imperative for ensuring access to clean water across the globe. Here, in situ resonant anomalous X-ray reflectivity is used to investigate the adsorption of uranyl on alumina (012) in acidic aqueous solutions, representing typical U VI concentrations of contaminated water near mining sites. The analyses reveal that U VI adsorbs at two distinct heights of 2.4-3.2 and 5-5.3 angstrom from the surface terminal oxygens. The former is interpreted as the mixture of inner-sphere and outer-sphere complexes that adsorb closest to the surface. The latter is interpreted as an outer-sphere complex that shares one equatorial H 2 O with the terminal surface oxygen. With increasing pH, we observe an increasing prevalence of these outer-sphere complexes, indicating the enhanced role of the hydrogen bond that stabilizes adsorbed uranyl species. Finally, the presented work provides a molecular-scale understanding of sorption of uranyl on Al-based-oxide surfaces that has implications for environmental chemistry and materials science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Studies on the Fundamental Mechanisms of Niobium Electropolishing

To improve the superconducting performance of niobium SRF cavities, electropolishing (EP) with a sulfuric and hydroflouric acid mixture is used. The chemistry of this reaction is complex due to the interactions between diffusion mechanisms, surface oxide structure, and multiple chemical species. Past studies on the EP process have produced a certain set of optimum parameters that have been used successfully for a long time. However, two recent developments have called the efficacy of the existing EP process into question. Since the introduction of nitrogen doping the surface quality of some cavities has been very poor. Also, EP performed at colder than standard temperatures leads to an increase in the cavity performance. To understand these questions, we perform a multivariate study on the EP process using niobium test samples electropolished at different temperatures and potentials. We find that electropolishing at lower potentials leads to rough surface features such as pitting and grain etching. Some of the surface features show similarities to features seen in niobium cavities. The effect of electropolishing temperature is not clear based on the results of this study.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Applying novel analytical tools for analyzing multidimensional secondary organic aerosol measurements

In the atmosphere, secondary organic aerosols (SOA) are often the major components of fine particulate matter and interact with clouds and radiation. SOA comprises a mixture of thousands of organic compounds. There is tremendous complexity and uncertainty in understanding SOA formation, since it is formed by oxidation and gas to particle conversion of a variety of sources: natural biogenic, anthropogenic (vehicles, cooking coal combustion) and biomass burning. The Aerosol Mass Spectrometer (AMS) produces multidimensional chemical information about SOA but analyzing this data to understand SOA sources relies on time consuming analyses (~months to years) such as the positive matrix factorization (PMF). PMF also becomes difficult for aircraft data where signal to noise ratio is weaker. There is a critical need to develop fast machine learning techniques that can analytically provide information about SOA sources using AMS data on the same timescales as the data is being collected (~minutes). We apply a machine learning supervised classification approach: the multinomial logistic regression to rapidly classify AMS data obtained from aircraft measurements.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Synthesis of Novel Hybrid Nanostructures Employing Advanced Structural Characterization Techniques

This proposal was for carrying out research on creating novel hybrid nanostructures with novel and interesting functional properties with the help of advanced structural on adding 0.001, 0.01 and 0.02 mg of Au nanoparticles. From the reflectivity measurements, and the intensities of the various order diffraction peaks from the multilayers, we were able to reconstruct the electron density profiles of the films normal to their surfaces. characterization techniques. There were 3 components to the research: (1) seeing if new hybrid nanostructures could be synthesized from Au nanoparticles and lipid multilayers (2) making artificial cells from Galactopyranose-Derived Single-Chain Amphiphiles and sponge phases of lipid/amphiphile mixtures, and (3) characterizing the pair distribution function for complex nanoparticles of melanin to understand/predict the structural colors seen in aggregates of such nanoparticles.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS1982

Some properties of RF sputtered hafnium nitride coatings

Hafnium nitride coatings were deposited by reactive RF sputtering from a hafnium target in nitrogen and argon gas mixtures. The rate of deposition, composition, electrical resistivity and complex index of refraction were investigated as a function of target substrate distance and the fraction nitrogen, (fN2) in the sputtering atmosphere. The relative composition of the coatings is independent on fN2 for values above 0.1. The electric resistivity of the hafnium nitride films changes over 8 orders of magnitude when fN2 changes from 0.10 to 0.85. The index of refraction is almost constant at 2.8(1-0.3i) up to fN2 = 0.40 then decreases to 2.1(1 - 0.01i) for higher values of fN2.

Aron, P. R.↗
NASA NTRS1989

Aircraft microwave observations and simulations of deep convection at 18-183 GHz

A radiative transfer model is used to simulate the aircraft multichannel microwave observations and to study a storm system observed on June 29, 1986 during the Cohmex program. The model, which is a revision of the model used by Wilheit et al. (1982), is described. The microwave upwelling brightness temperatures at the top of the atmosphere are calculated from hydrometeor profiles derived from ground-based radar data. The model is used to study various vertical hydrometeor phase profiles and particle size distributions. The results are compared with aircraft data from the Multispectral Cloud Radiometer and the Microwave Precipitation Radiometer. The results show that the brightness temperatures are directly influenced by the complex nature of hydrometeors, including size distribution and the mixture of ice and water phases.

Adler, R. F.↗
NASA NTRS1997

A Study of the Electrical Properties and Mineralogy of the Surface of Venus

This annual progress report is a list of papers on a study of the electrical properties and mineralogy of the surface of Venus. These papers were written by P. I. Wood and C. A. Robinson. Titles include: Subduction on the margins of coronae on Venus: Evidence from radiothermal emissivity measurements; The weathering process on Venus takes 2-3 hundred million years: Evidence from radiothermal emissivity signatures at coronae; SO2 and CH4 levels in the Venusian atmosphere, measured by Pioneer Venus: Caused by plinian-style volcanic activity at Maat Mons; Magellan reveals Venus; Recent volcanic activity on Venus: Evidence from radiothermal emissivity signatures; Occurrences of low-emissivity surface material at low altitudes on Venus: A window to the past; Must the Venus surface material contain hematite; Rock weathering on the surface of Venus; Comment on "The Rate of Pyrite Decomposition on the Surface of Venus-by J. A. Wood, and R. Brett; and Complex dielectric constants and magnetic permeabilities of mineral mixtures-by De Roo, R.D, C.A. Robinson, F.T. Ulaby, and J.A. Wood.

Wood, John A.↗