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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Radiation from a current filament driven by a traveling wave

Solutions are presented for the electromagnetic fields radiated by an arbitrarily oriented current filament located above a perfectly conducting ground plane and excited by a traveling current wave. Both an approximate solution, valid in the fraunhofer region of the filament and predicting the radiation terms in the fields, and an exact solution, which predicts both near and far field components of the electromagnetic fields, are presented. Both solutions apply to current waveforms which propagate along the channel but are valid regardless of the actual waveshape. The exact solution is valid only for waves which propagate at the speed of light, and the approximate solution is formulated for arbitrary velocity of propagation. The spectrum-magnitude of the fourier transform-of the radiated fields is computed by assuming a compound exponential model for the current waveform. The effects of channel orientation and length, as well as velocity of propagation of the current waveform and location of the observer, are discussed. It is shown that both velocity of propagation and an effective channel length are important in determining the shape of the spectrum.

Levine, D. M.↗
NASA NTRS1989

The effect of ionization on the infrared absorption spectra of PAHs: A preliminary report

The emission lines observed in many interstellar IR sources at 3.28, 6.2, 7.7, 8.7, and 11.3 microns are theorized to originate from polycyclic aromatic hydrocarbons (PAHs). These assignments are based on analyses of lab IR spectra of neutral PAHs. However, it is likely that in the interstellar medium that PAHs are ionized, i.e., are positively charged. Besides, as pointed out by Allamandola et al., although the IR emission band spectrum resembles what one might expect from a mixture of PAHs, it does not match in details such as frequency, band profile, or relative intensities predicted from the absorption spectra of any known PAH molecule. One source of more information to test the PAH theory is ab initio molecular orbital theory. It can be used to compute, from first principles, the geometries, vibrational frequencies, and vibrational intensities for model PAH compounds which are difficult to study in the lab. The Gaussian 86 computer program was used to determine the effect of ionization on the infrared absorption spectra of several small PAHs: naphthalene and anthracene. A preliminary report is presented of the results of these calculations.

Defrees, Doug J.↗
NASA NTRSDate not supplied

Characterizing Spatiotemporal Uncertainty in Interpolated Meteorological Data

Interpolated meteorological data invariably contain errors. These errors have structure in time and space, particularly autocorrelation, which can cause the effects of errors to compound when model outputs are aggregated temporally or spatially. One way to account for this uncertainty is with a probabilistic model from which samples can be drawn that are coherent with respect to underlying spatial and temporal covariance structure. This work describes a probabilistic method for spatial interpolation of point-wise meteorological time series. Observational data from weather stations are generally sparse in space and dense in time (but sometimes missing). The method works by projecting time series onto orthogonal basis vectors and spatially interpolating each resulting component independently. Under suitable assumptions, and data transformations to better satisfy those assumptions, Gaussian process regression provides a complete description of the joint predictive distribution over a Gaussian random field. Spatiotemporally coherent realizations are generated as the sum of conditional (spatial) simulations of each orthogonal (temporal) component. Data-derived and generic orthogonal bases are considered. In addition to spatial interpolation, imputation of missing observational data is examined. The method is applied using near-surface air temperature over the Western United States and validated by comparing theoretical versus actual coverage of predictive distributions and analyzing the degree to which spatial and temporal covariance structure is reproduced. Computational considerations, relating to conditional simulation of random fields, are also addressed.

Conor T Doherty↗
DOE OSTI2024

Microwave-Assisted Syngas Cleanup: Catalytic Reforming of Gasifier Tar Using a Low-Cost Iron Catalyst

The microwave-assisted gasification of plastic wastes to produce hydrogen-rich syngas is an attractive energy-saving plastic upcycling route, and the addition of biomass could improve the quality of the syngas produced; however, it could also increase the tar yield, which is an undesired, secondary product in this process. The presence of tars could result in downstream lines blockage, reactor down time and costly maintenance. Therefore, reducing or removing tar is desired. Due to its chemical complexity, toluene, which is one of the main tar constituents, could be used as a model tar compound. In this work, the microwave-assisted catalytic dry reforming of toluene was studied using Fe/Al2O3 as a catalyst, under CO2 at different reaction temperatures. The toluene reforming reaction was conducted using microwave and conventional thermal reactors. The results showed that under microwave irradiation, higher CO2 and toluene conversions, as well as better hydrogen yield can be observed compared to conventional toluene reforming at the same reaction temperature. The catalyst stability test was also investigated. Three reaction pathways were observed during microwave reaction.

Bai, Xinwei↗
DOE OSTI2022

Simple Autoignition Model for the Derived Cetane Number of Oxygenated Compounds and Fuel Blends

A simple four-step autoignition model was used to derive an expression for the ignition delay and derived cetane number (DCN) measured by ignition quality testers (IQT) for oxygenated compounds and blends as a function of each compound’s global initiation and net chain branching rate constants. Expressions for these values were determined assuming they could be related to the functional groups present in a given compound. Measurements for 124 compounds and 94 binary and ternary blends, gathered from the literature and performed at UW-Madison, were used to obtain the explicit dependence of the measured ignition delay on each functional group. The new model was able to successfully describe the ignition behavior of both the compounds and blends, with an average DCN error of 5.0 (22%) and 3.5 (15%), respectively. Additionally, the blend model could naturally be modified into a mixing rule by incorporating existing IQT ignition delay data for each compound. Use of the mixing rule was found to offer improvements over the full prediction, with an average DCN error of 3.2 (14%).

09 BIOMASS FUELS↗
DOE OSTI2021

Diversifying Isoprenoid Platforms via Atypical Carbon Substrates and Non-model Microorganisms

Isoprenoid compounds are biologically ubiquitous, and their characteristic modularity has afforded products ranging from pharmaceuticals to biofuels. Isoprenoid production has been largely successful in Escherichia coli and Saccharomyces cerevisiae with metabolic engineering of the mevalonate (MVA) and methylerythritol phosphate (MEP) pathways coupled with the expression of heterologous terpene synthases. Yet conventional microbial chassis pose several major obstacles to successful commercialization including the affordability of sugar substrates at scale, precursor flux limitations, and intermediate feedback-inhibition. Now, recent studies have challenged typical isoprenoid paradigms by expanding the boundaries of terpene biosynthesis and using non-model organisms including those capable of metabolizing atypical C1 substrates. Conversely, investigations of non-model organisms have historically informed optimization in conventional microbes by tuning heterologous gene expression. Here, we review advances in isoprenoid biosynthesis with specific focus on the synergy between model and non-model organisms that may elevate the commercial viability of isoprenoid platforms by addressing the dichotomy between high titer production and inexpensive substrates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Evaluating Energy Efficiency Opportunities from Connected and Automated Vehicle Deployments Coupled with Shared Mobility in California

Connected and Automated Vehicles (CAVs) can be considered to be a disruptive transportation technology, with the potential to significantly improve overall transportation system efficiency; however, CAVs may increase induce vehicle miles traveled (VMT) and bring on greater energy consumption. Further, shared mobility is another disruptive transportation event that is reshaping our travel patterns. The primary goal of this project was to extensively collect data from vehicles and associated infrastructure equipped with CAV technologies from both real-world experiments and simulation studies mainly deployed in California, and develop a comprehensive framework for evaluating energy efficiency opportunities from large-scale (e.g., statewide) introduction of CAVs and a wide deployment of shared mobility systems in a variety of scenarios. To quantify the combined impact of CAV and shared mobility on travel behavior, traffic performance, and energy efficiency, a unique mesoscopic simulation-based model was developed for mobility and energy efficiency evaluation considering these disruptive transportation technologies. As a complement to existing studies on nationwide evaluation of CAVs’ energy impacts, this project was focused on data collection efforts and CAV applications under congested traffic environments that are frequently experienced on a massive scale across the major metropolitan areas in California. Extensive real-world data collection supplemented with simulation studies were conducted to cover a variety of CAV and shared mobility scenarios, particularly on scenarios less-explored in the existing research. Another key component of this project was to consider the interaction between different CAV technologies and shared mobility models, and the compound effect on energy efficiency. A comprehensive modeling suite was developed to quantify the impact of new mobility technologies on travel behavior and traffic performance. The developed modeling framework includes an energy intensity module, mode choice module and activity generation module that are integrated into an agent-based BEAM simulation platform to perform impact analysis based on a variety of scenarios. In addition, the RouteE model has been upgraded to incorporate the impact of CAVs on traffic flow, VMT and energy intensity, using micro-simulation data collected from both freeways and urban arterials. A novel fundamental influencing factor (FIF) mode choice model was developed to link CAV and shared mobility components with travel behaviors, and adapted into the BEAM-centered model framework. A statewide energy inventory was constructed under various CAV technology deployment scenarios by incorporating datasets and models for predicting vehicle market share and vehicle usage, which are tightly associated with the penetration of shared mobility systems. Based applying this modeling suite to a calibrated network in Riverside California, it was found that cooperative automated driving in general will improve mobility, but automated vehicles, even when deployed in a shared autonomous fleet, will likely bring an increase of VMT (up to 36%) due to mode shifts and deadheading. Ride-hailing vehicles typically have better energy efficiency and a higher share of electric vehicles, which helps offset the negative impact from VMT increases when estimating the system-level energy consumption. In general, simulation results show a 6% increase in energy consumption for the scenarios with an increasing shift to ride-hailing modes. The statewide analysis based on the National Household Travel Survey (NHTS) sample data is consistent with the findings from the Riverside network and validate the developed clustering-prediction modeling methodology. The outcomes from this project will help close the knowledge gap on recognizing the potential performance and energy impacts of a broad deployment of CAV and shared mobility technologies across a wide range of roadway infrastructure with varying levels of congestion. Results from this project: 1) will support policymakers in steering CAV development and deployment towards an energy favorable direction; 2) reduce uncertainties in estimating energy saving opportunities from new mobility technologies and services; 3) increase the confidence of CAV technology investors both on the infrastructure side (i.e., transportation agencies) and on the vehicle side (i.e., OEMs); and 4) expedite the deployment of energy-efficient CAV and shared mobility applications.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1993

Model for the Vaporization of Mixed Organometallic Compounds in the Metalorganic Chemical Vapor Deposition of High Temperature Superconducting Films

A model of the vaporization and mass transport of mixed organometallics from a single source for thin film metalorganic chemical vapor deposition is presented. A stoichiometric gas phase can be obtained from a mixture of the organometallics in the desired mole ratios, in spite of differences in the volatilities of the individual compounds. Proper film composition and growth rates are obtained by controlling the velocity of a carriage containing the organometallics through the heating zone of a vaporizer.

Meng, Guangyao↗
NASA NTRS1999

Molecular Modeling and Experimental Investigations of Nonlinear Optical Compounds Monosubstituted Derivatives of Dicyanovinylbenzene

A search for potential nonlinear optical compounds was performed using the Cambridge Structure Database and molecular modeling. We investigated a series of monosubstituted derivatives of dicyanovinylbenzene, since the nonlinear optical (NLO) properties of such derivatives (o-methoxy-dicyanovinylbenzene, DIVA) were studied earlier. The molecular geometry of these compounds was investigated with x-ray analysis and discussed along with the results of molecular mechanics and ab initio quantum chemical calculations. The influence of crystal packing on the planarity of the molecules of this series has been revealed. Two new compounds from the series studied, ortho-F and para-Cl-dicyanovinylbenzene, according to powder measurements, were found to be NLO compounds in the crystal state about 10 times more active than urea. The peculiarities of crystal structure formation in the framework of balance between van der Waals and electrostatic interactions have been discussed. The crystal shape of DIVA and two new NLO compounds have been calculated on the basis of the known crystal structure.

Timofeeva, Tatiana V.↗
NASA NTRS1998

Modeling Macro- and Micro-Scale Turbulent Mixing and Chemistry in Engine Exhaust Plumes

Simulation of turbulent mixing and chemical processes in the near-field plume and plume-vortex regimes has been successfully carried out recently using a reduced gas phase kinetics mechanism which substantially decreased the computational cost. A detailed mechanism including gas phase HOx, NOx, and SOx chemistry between the aircraft exhaust and the ambient air in near-field aircraft plumes is compiled. A reduced mechanism capturing the major chemical pathways is developed. Predictions by the reduced mechanism are found to be in good agreement with those by the detailed mechanism. With the reduced chemistry, the computer CPU time is saved by a factor of more than 3.5 for the near-field plume modeling. Distributions of major chemical species are obtained and analyzed. The computed sensitivities of major species with respect to reaction step are deduced for identification of the dominant gas phase kinetic reaction pathways in the jet plume. Both the near field plume and the plume-vortex regimes were investigated using advanced mixing models. In the near field, a stand-alone mixing model was used to investigate the impact of turbulent mixing on the micro- and macro-scale mixing processes using a reduced reaction kinetics model. The plume-vortex regime was simulated using a large-eddy simulation model. Vortex plume behind Boeing 737 and 747 aircraft was simulated along with relevant kinetics. Many features of the computed flow field show reasonable agreement with data. The entrainment of the engine plumes into the wing tip vortices and also the partial detrainment of the plume were numerically captured. The impact of fluid mechanics on the chemical processes was also studied. Results show that there are significant differences between spatial and temporal simulations especially in the predicted SO3 concentrations. This has important implications for the prediction of sulfuric acid aerosols in the wake and may partly explain the discrepancy between past numerical studies (that employed parabolic or temporal approximations) and the measured data. Finally to address the major uncertainty in the near-field plume modeling related to the plume processing of sulfur compounds and advanced model was developed to evaluate its impact on the chemical processes in the near wake. A comprehensive aerosol model is developed and it is coupled with chemical kinetics and the axisymmetric turbulent jet flow models. The integrated model is used to simulate microphysical processes in the near-field jet plume, including sulfuric acid and water binary homogeneous nucleation, coagulation, non-equilibrium heteromolecular condensation, and sulfur-induced soot activation. The formation and evolution of aerosols are computed and analyzed. The computed results show that a large number of ultra-fine (0.3--0.6 nm in radius) volatile HSO4 - HO embryos are generated in the near-field plume. These embryos further grow in size by self coagulation and condensation. Soot particles can be activated by both heterogeneous nucleation and scavenging of H2SO4-H2O aerosols. These activated soot particles can serve as water condensation nuclei for contrail formation. Conditions under which ice contrails can form behind aircrafts are studied. The sensitivities of the threshold temperature for contrail formation with respect to aircraft propulsion efficiency, relative humidity, and ambient pressure are evaluated. The computed aerosol properties for different extent of fuel sulfur conversion to S(VI) (SO3 and H2SO4) in engine are examined and the results are found to be sensitive to this conversion fraction.

Menon, Suresh↗
NASA NTRS2000

Molecular Modeling and Experimental Study of Nonlinear Optical Compounds: Mono-Substituted Derivatives of Dicyanovinylbenzene

A search for potential nonlinear optical (NLO) compounds has been performed using the Cambridge Structural Database and molecular modeling. We have studied a series of mono-substituted derivatives of dicyanovinylbenzene as the NLO properties of one of its derivatives (o-methoxy-dicyanovinylbenzene, DIVA) were described earlier. The molecular geometry in the series of the compounds studied was investigated with an X- ray analysis and discussed along with results of molecular mechanics and ab initio quantum chemical calculations. The influence of crystal packing on the molecular planarity has been revealed. Two new compounds from the series studied were found to be active for second harmonic generation (SHG) in the powder. The measurements of SHG efficiency have shown that the o-F- and p-Cl-derivatives of dicyanovinylbenzene are about 10 and 20- times more active than urea, respectively. The peculiarities of crystal structure formation in the framework of balance between the van der Waals and electrostatic interactions have been discussed. The crystal morphology of DIVA and two new SHG-active compounds have been calculated on the basis of their known crystal structures.

Timofeeva, Tatyana V.↗
NASA NTRS1975

On the sputtering of binary compounds

A simple physical model is presented to describe some aspects of the sputtering of compound targets. In particular, expressions are developed for the partial sputtering yields for binary systems in terms of the elemental sputtering rates, the stoichiometric concentrations and surface binding energy. The partial yields depend non-linearly on the bulk target concentrations. Comparison of the theoretical predictions with the data on sputtering of PtSi, NiSi and Cu3Au indicates that the general features are well described.

Haff, P. K.↗
NASA NTRS1976

On the sputtering of binary compounds

A simple physical model is presented to describe some aspects of the sputtering of compound targets. In particular, expressions are developed for the partial sputtering yields for binary systems in terms of the elemental sputtering rates, the stoichiometric concentrations, and surface binding energy. The partial yields depend nonlinearly on the bulk target concentrations. Comparison of the theoretical predictions with the data on sputtering of PtSi, NiSi, and Cu3Au indicates that the general features are well described.

Haff, P. K.↗
DOE OSTI2025

Leveraging Natural Language Processing and Generative Models in Molecular Chemistry: Property Prediction and Novel Compound Generation

The accurate prediction of molecular properties is important for the rational design and the advancement of green chemistry and sustainable materials research. However, the predictive power of traditional computational chemistry methods is limited due to computational restrictions. Here, in this study, we examine an alternative approach to the accurate prediction of properties of organic compounds: natural language processing (NLP)-based molecular embedding. Using viscosity, partition coefficient (log P), and enthalpy of vaporization as test properties through a survey of comprehensive datasets comprising 5695 data points for viscosity, 25 870 data points for log P, and 2296 data points for enthalpy of vaporization. These are important properties for the design of greener, safer, and sustainable chemical processes. Models were trained using NLP methods such as Mol2vec and fine-tuned ChemBERTa, and results were compared with traditional input featurization techniques such as Morgan fingerprints and quantum chemistry derived sigma profiles and DFT features. Among the various machine learning models, Mol2vec demonstrated superior predictive capabilities, achieving the highest correlation coefficient (R 2 = 0.945) and lowest RMSE (0.106 mPa s) for viscosity, as well as high accuracy for log P and enthalpy of vaporization predictions. These findings establish the Mol2vec featurization technique, graph-convolutional neural networks (GCNN), and fine-tuned ChemBERTa model as powerful tools for predictive modeling of organic compounds properties, offering a significant improvement over previously used featurization techniques and opening up strategies for very-high-throughput computational screening. Finally, we integrated ML models with hybrid language-model-based generative adversarial networks (LM-GAN) to generate novel molecular sequences with desirable properties for different research applications. The ability to computationally design solvents with lower viscosity, lower log P, and lower enthalpy of vaporization offers a data-driven route to accelerating the discovery of sustainable alternatives to traditionally toxic solvents.

ChemBERTa↗
DOE OSTI2023

Small molecules disaggregate alpha-synuclein and prevent seeding from patient brain-derived fibrils

The amyloid aggregation of alpha-synuclein within the brain is associated with the pathogenesis of Parkinson’s disease (PD) and other related synucleinopathies, including multiple system atrophy (MSA). Alpha-synuclein aggregates are a major therapeutic target for treatment of these diseases. We identify two small molecules capable of disassembling preformed alpha-synuclein fibrils. The compounds, termed CNS-11 and CNS-11g, disaggregate recombinant alpha-synuclein fibrils in vitro, prevent the intracellular seeded aggregation of alpha-synuclein fibrils, and mitigate alpha-synuclein fibril cytotoxicity in neuronal cells. Furthermore, we demonstrate that both compounds disassemble fibrils extracted from MSA patient brains and prevent their intracellular seeding. They also reduce in vivo alpha-synuclein aggregates in C. elegans . Both compounds also penetrate brain tissue in mice. A molecular dynamics–based computational model suggests the compounds may exert their disaggregating effects on the N terminus of the fibril core. These compounds appear to be promising therapeutic leads for targeting alpha-synuclein for the treatment of synucleinopathies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Coupling strongly correlated electron systems to a tunable electronic reservoir

Here, we study the effect of coupling an electronic reservoir to a Hubbard model and to a dimer Hubbard model. This is motivated by recent experiments on the effect of illumination on the insulator-metal transition in a vanadium oxides and photoconductive cadmium sulfide heterostructure. We model the system as an electronic reservoir hybridized to the correlated system. We assume that the light intensity controls the hybridization coupling strength. We find that the light intensity acts similarly as the temperature in the weak interaction regime. This is consistent with the role played by electronic reservoirs in out-of-equilibrium systems. In contrast, qualitative differences appear at strong coupling. We show that modeling the V 2 ⁢O 3 compound with a Hubbard model, our results describe qualitatively well the observed illumination-driven suppression of the insulator-metal transition. In contrast, in the DHM results fail to capture the mild suppression observed in the case of VO 2 . This indicates that the lattice may play an important role in this case.

Materials Science↗
NASA NTRS1987

Degradation mechanisms of sulfur and nitrogen containing compounds during thermal stability testing of model fuels

The degradation behavior of n-dodecane (singly or in combination with S- and N-containing dopants) was studied using a modified Jet Fuel Thermal Oxidation Tester facility between 200 and 400 C. The products were analyzed by gas chromatography and mass spectrometry. The soluble products consisted mainly of n-alkanes and 1-alkenes, aldehydes, tetrahydrofuran derivatives, dodecanol and dodecanone isomers, C21-C24 alkane isomers, and dodecylhydroperoxide (ROOH) decomposition products. The major products were always the same, with and without dopants, but their distributions varied considerably. The 3,4-dimercaptotoluene and dibutylsulfide dopants added individually to n-dodecane interferred with the hydrocarbon oxidation at the alkylperoxy radical and the alkylhydroperoxide link, respectively, while the 2,5-dimethylpyrrole dopant inhibited ROOH formation. Pyridine, pyrrole, and dibenzothiophene added individually showed few significant effects.

Reddy, K. T.↗
NASA NTRS2017

Thermal Studies of Ammonium Cyanide Reactions: A Model for Thermal Alteration of Prebiotic Compounds in Meteorite Parent Bodies

Organic compounds in carbonaceous chondrites were likely transformed by a variety of parent body processes including thermal and aqueous processing. Here, we analyzed ammonium cyanide reactions that were heated at different temperatures and times by multiple analytical techniques. The goal of this study is to better understand the effect of hydrothermal alteration on cyanide chemistry, which is believed to be responsible for the abiotic synthesis of purine nucleobases and their structural analogs detected in carbonaceous chondrites.

Hammer, P. G.↗