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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Toward Edge-Defined Holey Boron Nitride Nanosheets

"Holey" two-dimensional (2D) nanosheets with well-defined holy morphology and edge chemistry are highly desirable for applications such as energy storage, catalysis, sensing, transistors, and molecular transport/separation. For example, holey grapheme is currently under extensive investigation for energy storage applications because of the improvement in ion transport due to through the thickness pathways provided by the holes. Without the holes, the 2D materials have significant limitations for such applications in which efficient ion transport is important. As part of an effort to apply this approach to other 2D nanomaterials, a method to etch geometrically defined pits or holes on the basal plane surface of hexagonal boron nitride (h-BN) nanosheets has been developed. The etching, conducted via heating in ambient air using metal nanoparticles as catalysts, was facile, controllable, and scalable. Starting h-BN layered crystals were etched and subsequently exfoliated into boron nitride nanosheets (BNNSs). The as-etched and exfoliated h-BN nanosheets possessed defined pit and hole shapes that were comprised of regulated nanostructures at the edges. The current finding are the first step toward the bulk preparation of holey BNNSs with defined holes and edges.

Lin, Yi↗
NASA NTRS2016

Latent Hardeners for the Assembly of Epoxy Composites

Large-scale composite structures are commonly joined by secondary bonding of molded-and-cured thermoset components. This approach may result in unpredictable joint strengths. In contrast, assemblies made by co-curing, although limited in size by the mold, result in stable structures, and are certifiable for commercial aviation because of structural continuity through the joints. Multifunctional epoxy resins were prepared that should produce fully-cured subcomponents with uncured joining surfaces, enabling them to be assembled by co-curing in a subsequent out-of-autoclave process. Aromatic diamines were protected by condensation with a ketone or aldehyde to form imines. Properties of the amine-cured epoxy were compared with those of commercially available thermosetting epoxy resins and rheology and thermal analysis were used to demonstrate the efficacy of imine protection. Optimum conditions to reverse the protecting chemistry in the solid state using moisture and acid catalysis were determined. Alternative chemistries were also investigated. For example, chain reaction depolymerization and photoinitiated catalysts would be expected to minimize liberation of volatile organic content upon deprotection and avoid residual reactive species that could damage the resin. Results from the analysis of protected and deprotected resins will be presented.

Palmieri, Frank↗
NASA NTRS2016

Synthesis and Characterization of Cobalt Containing Nanoparticles on Alumina A Potential Catalyst for Gas to Liquid Fuels Production

Fisher-Tröpsch synthesis (FTS) is a century-old gas-to-liquid (GTL) technology that commonly employs cobalt (Co, on an oxide support) or iron (supported or not) species catalysts. It has been well established that the activity of the Co catalyst depends directly upon the number of surface Co atoms. The addition of promoter (mainly noble) metals has been widely utilized to increase the fraction of Co that is available for surface catalysis. Direct synthesis of Co nanoparticles is a possible alternative approach; our preliminary synthesis and characterization efforts are described. Materials were characterized by various transmission microscopies and energy dispersive spectroscopy. Tri-n-octylphosphine oxide (TOPO) and dicobalt octacarbonyl were heated under argon to a temperature of 180 deg with constant stirring for 1 hr. Quenching the reaction in toluene produced Co-containing nanoparticles with a diameter of 5 to 10 nm. Alternatively, an alumina support (SBA-200 Al2O3) was added; the reaction was further stirred and the temperature was decreased to 140 deg to reduce the rate of further growth/ripening of the nucleated Co nanoparticles. A typical size of Co-containing NPs was also found to be in the range of 5 to 10 nm. This can be contrasted with a range of 50 to 200 nm for conventionally-produced Co-Al2O3 Fischer-Tröpsch catalysts. This method shows great potential for production of highly dispersed catalysts that are either supported or unsupported.

aluminum oxides↗
NASA NTRS2019

Life's Requirements

Life on Earth is molecular in nature, with its lifelike attributes- e.g., information processing and catalysis- emerging as a result of both the specific properties of those molecules and the interactions among them. If this is a general model for life, then life must require (i) a source of energy, with which to build and sustain molecular complexity and information processing; (ii) elemental raw materials, from which to construct molecules having specific properties and reactivity; (iii)a solvent that supports the synthesis of the full range of molecules required by life and properly mediates the full range of necessary interactions among those molecules; and (iv) physicochemical conditions in which life's molecules can be synthesized, are appropriately stable, and can interact as needed for lifelike function. For life on Earth, these general requirements, respectively, take the specific form: (i) light energy in visible-to-near-infrared wavelengths or chemical energy as provided by oxidation–reduction disequilibrium, (ii) the "biogenic "elements (carbon, hydrogen, oxygen, nitrogen, phosphorus, and sulfur) (iii)liquid water, and (iv) specific ranges in temperature, pH, salinity, pressure, and other environmental factors. Our knowledge of these factors relates to cellula rlife as we observe it now or can infer from the fossil or molecular records. Life's origin may be constrained by a more stringent set of requirements that are, as yet,not fully understood.

Habitability↗
NASA NTRS2020

UV/Vis+ Photochemistry Database: Structure, Content and Applications

The “science-softCon UV/Vis+ Photochemistry Database” (www.photochemistry.org) is a large and comprehensive collection of EUV-VUV-UV–Vis-NIR spectral data and other photochemical information assembled from published peer-reviewed papers. The database contains photochemical data including absorption, fluorescence, photoelectron, and circular and linear dichroism spectra, as well as quantum yields and photolysis related data that are critically needed in many scientific disciplines. This manuscript gives an outline regarding the structure and content of the “science-softCon UV/Vis+ Photochemistry Database”. The accurate and reliable molecular level information provided in this database is fundamental in nature and helps in proceeding further to understand photon, electron and ion induced chemistry of molecules of interest not only in spectroscopy, astrochemistry, astrophysics, Earth and planetary sciences, environmental chemistry, plasma physics, combustion chemistry but also in applied fields such as medical diagnostics, pharmaceutical sciences, biochemistry, agriculture, and catalysis. In order to illustrate this, we illustrate the use of the UV/Vis+ Photochemistry Database in four different fields of scientific endeavor.

Photochemistry↗
NASA NTRS2021

Oncogenic Integration of Nucleotide Metabolism via Fatty Acid Synthase in Non-Hodgkin Lymphoma

Metabolic dysfunctions enabling increased nucleotide biosynthesis are necessary for supporting malignant proliferation. Our investigations indicate that upregulation of fatty acid synthase (FASN) and de novo lipogenesis, commonly observed in many cancers, are associated with nucleotide metabolic dysfunction in lymphoma. The results from our experiments showed that ribonucleotide and deoxyribonucleotide pool depletion, suppression of global RNA/DNA synthesis, and cell cycle inhibition occurred in the presence of FASN inhibition. Subsequently, we observed that FASN inhibition caused metabolic blockade in the rate-limiting step of the oxidative branch of the pentose phosphate pathway (oxPPP) catalyzed by phosphogluconate dehydrogenase (PGDH). Furthermore, we determined that FASN inhibitor treatment resulted in NADPH accumulation and inhibition of PGDH enzyme activity. NADPH is a cofactor utilized by FASN, also a known allosteric inhibitor of PGDH. Through cell-free enzyme assays consisting of FASN and PGDH, we delineated that the PGDH-catalyzed ribulose-5-phosphate synthesis is enhanced in the presence of FASN and is suppressed by increasing concentrations of NADPH. Additionally, we observed that FASN and PGDH were colocalized in the cytosol. The results from these experiments led us to conclude that NADP–NADPH turnover and the reciprocal stimulation of FASN and PGDH catalysis are involved in promoting oxPPP and nucleotide biosynthesis in lymphoma. Finally, a transcriptomic analysis of non-Hodgkin’s lymphoma (n = 624) revealed the increased expression of genes associated with metabolic functions interlinked with oxPPP, while the expression of genes participating in oxPPP remained unaltered. Together we conclude that FASN–PGDH enzymatic interactions are involved in enabling oxPPP and nucleotide metabolic dysfunction in lymphoma tumors.

Non-Hodgkin lymphoma↗
NASA NTRS2022

CryoEM Structures of the Nitrogenase Complex During Catalytic Turnover

The enzyme nitrogenase couples adenosine triphosphate (ATP) hydrolysis to the multi-electron reduction of atmospheric dinitrogen into ammonia. Despite extensive research, the mechanistic details of ATP-dependent energy transduction and dinitrogen reduction by nitrogenase are not well understood, requiring new strategies to monitor its structural dynamics during catalytic action. Here we report the cryogenic electron microscopic interrogation of the nitrogenase complex under enzymatic turnover conditions, which has enabled the structural characterization of the nitrogenase reaction intermediates at high resolution for the first time. Our structures show that asymmetry governs all aspects of nitrogenase mechanism including ATP hydrolysis, protein-protein interactions, and catalysis. Furthermore, they reveal several previously unobserved, mechanistically relevant conformational changes near the catalytic iron-molybdenum cofactor that are correlated with the nucleotide-hydrolysis state of the enzyme.

Hannah L. Rutledge↗
NASA NTRS2023

Optimizing Surfactant Templating of Yttria-Stabilized Zirconia Aerogels for High-Temperature Applications: Effect of Anionic and Nonionic Surfactant

Aerogels, mesoporous materials with extreme material properties including high specific surface area, low density, and low thermal conductivity, can be useful for applications including catalysis, sorption media, and drug delivery. The low thermal conductivity and high surface area of aerogels makes them advantageous as thermal management systems, specifically for aerospace or aeronautics applications. However, the pore collapse and subsequent surface area decrease of aerogels following exposure to high temperatures must be mitigated to allow aerogels to be effectively used in thermal management applications. This work investigates the anionic surfactant sodium dodecyl sulfate (SDS) and the nonionic surfactant Pluronic® P-123 as surfactant templates in yttria-stabilized zirconia (YSZ) aerogels. By utilizing surfactant templates, known to influence pore structure, it is anticipated that sintering and densification of the aerogels following high-temperature exposure will be mitigated. It was determined that the addition of SDS and P-123 increased the surface area and pore volume of as-dried aerogels and suppressed crystallite growth at high temperatures. However, the impact of surfactant templates on the surface area and pore volume of heat-treated aerogels was negligible, potentially due to low concentrations of surfactant and the removal of the surfactant following high-temperature exposure.

Yttria-stabilized zirconia aerogels↗
NASA NTRS2022

Structures of the Nitrogenase Complex Prepared Under Catalytic Turnover Conditions

The enzyme nitrogenase couples adenosine triphosphate (ATP) hydrolysis to the multielectron reduction of atmospheric dinitrogen into ammonia. Despite extensive research, the mechanistic details of ATP-dependent energy transduction and dinitrogen reduction by nitrogenase are not well understood, requiring new strategies to monitor its structural dynamics during catalytic action. Here, we report cryo–electron microscopy structures of the nitrogenase complex prepared under enzymatic turnover conditions. We observe that asymmetry governs all aspects of the nitrogenase mechanism, including ATP hydrolysis, protein-protein interactions, and catalysis. Conformational changes near the catalytic iron-molybdenum cofactor are correlated with the nucleotide-hydrolysis state of the enzyme.

Hannah L. Rutledge↗
NASA NTRSDate not supplied

Quantum Hardware-Enabled Molecular Dynamics via Transfer Learning

The ability to perform ab initio molecular dynamics simulations using potential energy surfaces provided by quantum computers would open the door to virtually exact dynamics for a variety of chemical and biochemical systems, with impacts on catalysis and biophysics. Nonetheless, performing molecular dynamics on surfaces produced by quantum hardware has been hampered by the noisy energies typically produced by quantum computers and challenges associated with computing gradients and scaling to large systems interest. A recent set of advances in machine learning, known as transfer learning, provides a new path forward for molecular dynamics simulations on quantum hardware. Transfer learning offers a workaround, where one first trains models on larger, less accurate classical datasets and then refines them on smaller, more accurate quantum datasets. We explore this approach by training machine learning models to predict a molecule's potential energy based on its geometric structure using Behler-Parrinello neural networks. When successfully trained, the model enables energy gradient predictions necessary for dynamic simulations. To reduce the quantum resources needed, the model is initially trained with data derived from classical density functional theory and subsequently refined with a smaller dataset obtained from a variational quantum eigensolver optimization of the unitary coupled cluster ansatz. We show that this approach significantly reduces the size of the needed quantum training dataset while capturing the high accuracies needed within quantum chemistry simulations. The success of this two-step training method opens more opportunities to apply machine learning models on quantum data, a significant stride towards efficient quantum-classical hybrid computational models.

quantum computing↗
NASA NTRSDate not supplied

A Green’s Function Sensor Fusion Approach for Evaluating Spacecraft Entry Heating From on-Board Thermal Instrumentation

During atmospheric entry, distributed thermal measurements are critical to enable the evaluation of heat loads on spacecraft thermal protection systems (TPS). In recent space exploration missions, Schmidt-Boelter-type heat flux gauges have been integrated into the TPS alongside conventional temperature measurement instrumentation to measure total (convective and radiative) and radiative heat transfer rates1,2. While direct heat flux sensors (HFS) are able to provide valuable information detailing the thermal loads experienced by spacecraft, the interpretation of these measurements in unsteady, convective environments requires a correction factor to account for local heating augmentations at the cold wall HFS surface2,3. Current efforts to estimate cold wall correction factors, and thus recover the hot wall TPS heat flux, rely on time-marching computational fluid dynamics (CFD) simulations2. Simulation-based methods are susceptible to large uncertainties, however, as they require estimations of vehicle trajectory, gas kinetics, wall catalysis models, and other flight conditions as input parameters2,4. Furthermore, CFD simulations are computationally expensive and cannot efficiently survey all possible entry scenarios, exacerbating the uncertainty of reconstructed hot wall heat flux values. These drawbacks motivate the development of alternative hot wall heat flux reconstruction methods that are not reliant on CFD-based correction factors.

Kenneth McAfee↗
NASA NTRS2024

Future of the Search for Life: Workshop Report

The 2-week, virtual Future of the Search for Life science and engineering workshop brought together more than 100 scientists, engineers, and technologists in March and April 2022 to provide their expert opinion on the interconnections between life-detection science and technology. Participants identified the advances in measurement and sampling technologies they believed to be necessary to perform in situ searches for life elsewhere in our Solar System, 20 years or more in the future. Among suggested measurements for these searches, those pertaining to three potential indicators of life termed “dynamic disequilibrium,” “catalysis,” and “informational polymers” were identified as particularly promising avenues for further exploration. For these three indicators, small breakout groups of participants identified measurement needs and knowledge gaps, along with corresponding constraints on sample handling (acquisition and processing) approaches for a variety of environments on Enceladus, Europa, Mars, and Titan. Despite the diversity of these environments, sample processing approaches all tend to be more complex than those that have been implemented on missions or envisioned for mission concepts to date. The approaches considered by workshop breakout groups progress from nondestructive to destructive measurement techniques, and most involve the need for fluid (especially liquid) sample processing. Sample processing needs were identified as technology gaps. These gaps include technology and associated sampling strategies that allow the preservation of the thermal, mechanical, and chemical integrity of the samples upon acquisition; and to optimize the sample information obtained by operating suites of instruments on common samples. Crucially, the interplay between science-driven life-detection strategies and their technological implementation highlights the need for an unprecedented level of payload integration and extensive collaboration between scientists and engineers, starting from concept formulation through mission deployment of life-detection instruments and sample processing systems.

Marc Neveu↗
NASA NTRS2024

Reliable and Efficient Electrochemical Recovery of O 2 from Metabolic CO 2 at the International Space Station (ISS)

Maximum O 2 recovery from metabolic carbon dioxide (CO 2 ) is desired for future long-duration missions beyond Low Earth Orbit (LEO). The O 2 recovery for the Environmental Control and Life Support System (ECLSS) at the International Space Station (ISS), presently limited to 50% (Sabatier), must be highly reliable and efficient and recover a minimum of 75% oxygen (O 2 ) from metabolic CO 2 . An alternative technology development effort currently underway at NASA Marshall Space Flight Center (MSFC) via a Microfluidic Electrochemical Reactor (MFECR) approach has the potential to increase O 2 recovery significantly and reduce the complexity of the ECLSS O 2 recovery at the ISS as it would replace three pieces, the CO 2 Reduction Assembly (CRA) (Sabatier reactor), the Oxygen Generation Assembly (OGA), and the Plasma Pyrolysis Assembly (PPA). The MFECR's electrochemical process generates ethylene (C 2 H 4 ) and carbon moxide (CO) instead of methane (CH 4 ) (Sabatier) as a byproduct, eliminating the need for further dehydrogenation through the PPA. As in the OGA, the MFECR's electrochemical process generates O 2 and hydrogen (H 2 ) from the water electrolysis process. MSFC and the University of Texas in Arlington (UTA) have jointly designed and fabricated an MFECR's single cell that operates at ambient conditions and utilizes a proprietary catalysis highly selective on reducing CO 2 to C 2 H 4 and CO at the cathode. This MFECR's single cell consists of gas diffusion layers at the cathode and anode for respective intake of CO 2 and output of O 2 from the catalytic layer. This approach is expected to substantially improve the ISS ECLSS sustainability and reduce power and weight requirements as the MFECR would replace three units currently installed in the ISS. In this paper, the authors discuss the outcome of preliminary tests, the current development, and the evaluation efforts on different alternatives for the cathode and the anode configurations, the setup of the MFECR at an engineering development unit (EDU) scale, and the O 2 recovery performance, and evaluation efforts on different alternatives on not only the configuration and setup of the MFECR at an Engineering Design Unit (EDU) scale but also the selection of component materials.

Jesus A Dominguez↗
NASA NTRSDate not supplied

A Green’s Function Sensor Fusion Approach for Evaluating Spacecraft Entry Heating From on-Board Thermal Instrumentation

During atmospheric entry, distributed thermal measurements are critical to enable the evaluation of heat loads on spacecraft thermal protection systems (TPS). In recent space exploration missions, Schmidt-Boelter-type heat flux gauges have been integrated into the TPS alongside conventional temperature measurement instrumentation to measure total (convective and radiative) and radiative heat transfer rates1,2. While direct heat flux sensors (HFS) are able to provide valuable information detailing the thermal loads experienced by spacecraft, the interpretation of these measurements in unsteady, convective environments requires a correction factor to account for local heating augmentations at the cold wall HFS surface2,3. Current efforts to estimate cold wall correction factors, and thus recover the hot wall TPS heat flux, rely on time-marching computational fluid dynamics (CFD) simulations2. Simulation-based methods are susceptible to large uncertainties, however, as they require estimations of vehicle trajectory, gas kinetics, wall catalysis models, and other flight conditions as input parameters2,4. Furthermore, CFD simulations are computationally expensive and cannot efficiently survey all possible entry scenarios, exacerbating the uncertainty of reconstructed hot wall heat flux values. These drawbacks motivate the development of alternative hot wall heat flux reconstruction methods that are not reliant on CFD-based correction factors.

Kenneth McAfee↗
NASA NTRSDate not supplied

A Green’s Function Sensor Fusion Approach for Evaluating Spacecraft Entry Heating From on-Board Thermal Instrumentation

During atmospheric entry, distributed thermal measurements are critical to enable the evaluation of heat loads on spacecraft thermal protection systems (TPS). In recent space exploration missions, Schmidt-Boelter-type heat flux gauges have been integrated into the TPS alongside conventional temperature measurement instrumentation to measure total (convective and radiative) and radiative heat transfer rates1,2. While direct heat flux sensors (HFS) are able to provide valuable information detailing the thermal loads experienced by spacecraft, the interpretation of these measurements in unsteady, convective environments requires a correction factor to account for local heating augmentations at the cold wall HFS surface2,3. Current efforts to estimate cold wall correction factors, and thus recover the hot wall TPS heat flux, rely on time-marching computational fluid dynamics (CFD) simulations2. Simulation-based methods are susceptible to large uncertainties, however, as they require estimations of vehicle trajectory, gas kinetics, wall catalysis models, and other flight conditions as input parameters2,4. Furthermore, CFD simulations are computationally expensive and cannot efficiently survey all possible entry scenarios, exacerbating the uncertainty of reconstructed hot wall heat flux values. These drawbacks motivate the development of alternative hot wall heat flux reconstruction methods that are not reliant on CFD-based correction factors.

Kenneth McAfee↗
NASA NTRS2024

Two mechanisms for the spontaneous emergence, execution, and reprogramming of chemical logic circuits

A key question in origin-of-life research is how primitive life or life-like systems obtained reusable and reprogrammable machinery of processing information to respond to various environmental and internal stimuli. One strategy to approach this question is to view living systems as universal chemical computers. This approach focuses upon uncovering how reusable and reprogrammable chemical NOT, AND, and OR logic gates could appear under prebiotically possible scenarios where simple chemicals and second- or lower-order reactions are more frequent than macromolecules and higher-order reactions. In this article, we theoretically model two generic mechanisms of forming Boolean gates based on geochemically plausible reaction systems that could have preceded complex biopolymers. The mechanisms exploit simple bistable autocatalytic systems to encode binary variables and use heterogeneous dilution rates to differentially activate or deactivate autocatalysis in different reactors. We found that NOT, AND, and OR gates, as well as more complex logic circuits, can spontaneously arise from connected, well-mixed flow reactors based on (i) catalysis by a heterodimer between mutually inhibitory autocatalysts or (ii) selectively permeable tunnels connecting reactors. Our results suggest that simple machinery can support the prebiotic emergence of complex chemical logic circuits and provide new guides for experimentally actualizing chemical computation.

Zhen Peng↗
NASA NTRS2002

Modeling of the HiPco process for carbon nanotube production. II. Reactor-scale analysis

The high-pressure carbon monoxide (HiPco) process, developed at Rice University, has been reported to produce single-walled carbon nanotubes from gas-phase reactions of iron carbonyl in carbon monoxide at high pressures (10-100 atm). Computational modeling is used here to develop an understanding of the HiPco process. A detailed kinetic model of the HiPco process that includes of the precursor, decomposition metal cluster formation and growth, and carbon nanotube growth was developed in the previous article (Part I). Decomposition of precursor molecules is necessary to initiate metal cluster formation. The metal clusters serve as catalysts for carbon nanotube growth. The diameter of metal clusters and number of atoms in these clusters are some of the essential information for predicting carbon nanotube formation and growth, which is then modeled by the Boudouard reaction with metal catalysts. Based on the detailed model simulations, a reduced kinetic model was also developed in Part I for use in reactor-scale flowfield calculations. Here this reduced kinetic model is integrated with a two-dimensional axisymmetric reactor flow model to predict reactor performance. Carbon nanotube growth is examined with respect to several process variables (peripheral jet temperature, reactor pressure, and Fe(CO)5 concentration) with the use of the axisymmetric model, and the computed results are compared with existing experimental data. The model yields most of the qualitative trends observed in the experiments and helps to understanding the fundamental processes in HiPco carbon nanotube production.

Validation Studies↗
NASA NTRS2002

Modeling of the HiPco process for carbon nanotube production. I. Chemical kinetics

A chemical kinetic model is developed to help understand and optimize the production of single-walled carbon nanotubes via the high-pressure carbon monoxide (HiPco) process, which employs iron pentacarbonyl as the catalyst precursor and carbon monoxide as the carbon feedstock. The model separates the HiPco process into three steps, precursor decomposition, catalyst growth and evaporation, and carbon nanotube production resulting from the catalyst-enhanced disproportionation of carbon monoxide, known as the Boudouard reaction: 2 CO(g)-->C(s) + CO2(g). The resulting detailed model contains 971 species and 1948 chemical reactions. A second model with a reduced reaction set containing 14 species and 22 chemical reactions is developed on the basis of the detailed model and reproduces the chemistry of the major species. Results showing the parametric dependence of temperature, total pressure, and initial precursor partial pressures are presented, with comparison between the two models. The reduced model is more amenable to coupled reacting flow-field simulations, presented in the following article.

Evaluation Studies↗