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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Dynamic response of photorespiration in fluctuating light environments

Abstract Photorespiration is a dynamic process that is intimately linked to photosynthetic carbon assimilation. There is a growing interest in understanding carbon assimilation during dynamic conditions, but the role of photorespiration under such conditions is unclear. In this review, we discuss recent work relevant to the function of photorespiration under dynamic conditions, with a special focus on light transients. This work reveals that photorespiration is a fundamental component of the light induction of assimilation where variable diffusive processes limit CO2 exchange with the atmosphere. Additionally, metabolic interactions between photorespiration and the C3 cycle may help balance fluxes under dynamic light conditions. We further discuss how the energy demands of photorespiration present special challenges to energy balancing during dynamic conditions. We finish the review with an overview of why regulation of photorespiration may be important under dynamic conditions to maintain appropriate fluxes through metabolic pathways related to photorespiration such as nitrogen and one-carbon metabolism.

Plant Sciences↗
NASA NTRS1990

Shock waves in mixtures - A re-examination

The structure of normal shock waves in binary mixtures is analyzed, using Monte Carlo direct simulation, and compared with previous experimental data. Previous work by Erwin et al. used a collision method based directly on the intermolecular potential function; the present work extends this approach to binary mixtures, obtaining heteromolecular collision cross sections from the corresponding potentials. Results are presented for helium-argon mixtures, with conditions corresponding to the experiments of Harnett and Muntz (1972).

Erwin, Daniel A.↗
NASA NTRS2000

Optimal Reward Functions in Distributed Reinforcement Learning

We consider the design of multi-agent systems so as to optimize an overall world utility function when (1) those systems lack centralized communication and control, and (2) each agents runs a distinct Reinforcement Learning (RL) algorithm. A crucial issue in such design problems is to initialize/update each agent's private utility function, so as to induce best possible world utility. Traditional 'team game' solutions to this problem sidestep this issue and simply assign to each agent the world utility as its private utility function. In previous work we used the 'Collective Intelligence' framework to derive a better choice of private utility functions, one that results in world utility performance up to orders of magnitude superior to that ensuing from use of the team game utility. In this paper we extend these results. We derive the general class of private utility functions that both are easy for the individual agents to learn and that, if learned well, result in high world utility. We demonstrate experimentally that using these new utility functions can result in significantly improved performance over that of our previously proposed utility, over and above that previous utility's superiority to the conventional team game utility.

Wolpert, David H.↗
NASA NTRS2007

Development of the Functional Flow Block Diagram for the J-2X Rocket Engine System

The J-2X program calls for the upgrade of the Apollo-era Rocketdyne J-2 engine to higher power levels, using new materials and manufacturing techniques, and with more restrictive safety and reliability requirements than prior human-rated engines in NASA history. Such requirements demand a comprehensive systems engineering effort to ensure success. Pratt & Whitney Rocketdyne system engineers performed a functional analysis of the engine to establish the functional architecture. J-2X functions were captured in six major operational blocks. Each block was divided into sub-blocks or states. In each sub-block, functions necessary to perform each state were determined. A functional engine schematic consistent with the fidelity of the system model was defined for this analysis. The blocks, sub-blocks, and functions were sequentially numbered to differentiate the states in which the function were performed and to indicate the sequence of events. The Engine System was functionally partitioned, to provide separate and unique functional operators. Establishing unique functional operators as work output of the System Architecture process is novel in Liquid Propulsion Engine design. Each functional operator was described such that its unique functionality was identified. The decomposed functions were then allocated to the functional operators both of which were the inputs to the subsystem or component performance specifications. PWR also used a novel approach to identify and map the engine functional requirements to customer-specified functions. The final result was a comprehensive Functional Flow Block Diagram (FFBD) for the J-2X Engine System, decomposed to the component level and mapped to all functional requirements. This FFBD greatly facilitates component specification development, providing a well-defined trade space for functional trades at the subsystem and component level. It also provides a framework for function-based failure modes and effects analysis (FMEA), and a rigorous baseline for the functional architecture.

White, Thomas↗
DOE OSTI2020

Interplay between Intrinsic Thermal Stability and Expansion Properties of Functionalized UiO-67 Metal–Organic Frameworks

The UiO family of metal-organic frameworks (MOFs) has been extensively studied for several applications owing to their high stability rendered by their robust secondary building units. The efficient design and use of these materials require a fundamental understanding of their thermal stability and its impact on chemical and structural functionality. In this work, we provide a detailed characterization of the intrinsic thermal behavior of the UiO-67 and functional analogues, UiO-67-NH 2 and UiO-67-CH 3 . Using in situ temperature-programmed X-ray diffraction, we find that distortion of the carboxylate group on the organic linker leads to negative thermal expansion (NTE) of the UiO-67 MOFs during heating. This NTE behavior is correlated with rich and reversible thermal changes observed in the MOF infrared spectral signature as samples are heated to the sample activation temperature (473 K). We find that in the absence of oxygen, activated UiO-67 samples show higher thermal stability compared to ambient or inert environments, with temperature-programmed desorption revealing an overall stability trend: UiO-67 > UiO-67- CH 3 > UiO-67-NH 2 . Two stages of change are observed during thermal treatment above 473 K, which are directly related to deformation of the inorganic node and the isotropic NTE behavior of these materials. Ultimately, these results provide a real-time interpretation of the fundamental thermoresponsive behavior of UiO-67 MOFs and offer a foundation for accurate interpretation of MOF interactions with guest molecules and their temperature dependence.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Irreversible oxygen poisoning: Modeling the initial water dissociation kinetics on δ-Pu(111) and δ-Pu(100) through density functional theory

In this work, the initial kinetics of water dissociation on two facets of δ-plutonium, δ-Pu(111) and δ-Pu(100), are explored through density functional theory in order to understand how water dissociation occurs on these facets. We explored the dissociation of water via the formation of hydroxyls, atomic hydrogen, and atomic oxygen species on each facet. We calculate low energetic barriers for water to split to adsorbed hydrogen and hydroxyl species at 0.19 eV for δ-Pu(111) and 0.07 eV for δ-Pu(100). The hydroxyl has a barrier of 0.64 and 0.37 eV to cleave the hydrogen–oxygen bond on δ-Pu(111) and δ-Pu(100), respectively. Due to the highly exergonic adsorption free energy of atomic oxygen of −2.10 eV, the metallic surfaces are found to be fully covered in oxygen, even with the inclusion of oxygen lateral interactions. When combined with the reaction thermodynamics, this free energy of adsorption forms a molecular oxygen desorption barrier greater than 9.51 eV (918 kJ/mol). These results, combined with simulated temperature programed desorption spectra, indicate that oxygen formed via water dissociation on δ-Pu (111) and (100) facets induces an irreversible poison that prevents further reaction of water directly on metallic plutonium surfaces, most likely due to the strong hybridization of the Pu and O valence states. Therefore, these results imply that another mechanism is responsible for the continuously experimentally measured water dissociation, which is most likely due to the Pu oxide.

36 MATERIALS SCIENCE↗
NASA NTRS1986

Space station science lab module

The Science Lab Module (SLM), a key component of the proposed Space Station (SS) orbiting complex, is undergoing intensive study during the project design phase which is currently underway. The SLM is one of the two laboratory modules which, together with two habitation modules, comprise the core elements of the SS reference configurations. Current project emphasis is to configure the SLM as a national science laboratory module facility which would have four major functions: maximize life sciences research potential, support operations of attached payloads, provide shirtsleeve environment for other payload instrument servicing, and support other science requirements. The design studies are focusing on outfitting a common module basic design to accommodate the four specific functions. Although design work for outfitting the SLM for life sciences research is underway, science requirements for the other sciences and functions are not as well developed.

Devincenzi, D. L.↗
DOE OSTI2021

Electronic structure of chromium trihalides beyond density functional theory

In this work, we explore the electronic band structure of freestanding monolayers of chromium trihalides Cr X 3 , X = Cl, Br, I, within an advanced ab initio theoretical approach based on the use of Green's function functionals. We compare the local density approximation with the quasiparticle self-consistent GW (QS GW ) approximation and its self-consistent extension ( QS G W ^ ) by solving the particle-hole ladder Bethe-Salpeter equations to improve the effective interaction W . We show that, at all levels of theory, the valence band consistently changes shape in the sequence Cl → Br → I , and the valence band maximum shifts from the M point to the Γ point. By analyzing the dynamic and momentum-dependent self-energy, we show that QS G W ^ adds to the localization of the systems in comparison with QS GW , thereby leading to a narrower band and reduced amount of halogens in the valence band manifold. Further analysis shows that X = Cl is most strongly correlated, and X = I is least correlated (most bandlike) as the hybridization between Cr d and X p enhances in the direction Cl → Br → I . For CrBr 3 and CrI 3 , we observe remarkable differences between the QS GW and QS G W ^ valence band structures, while their eigenfunctions are very similar. We show that weak perturbations, like moderate strain, weak changes to the d - p hybridization, and adding small U , can flip the valence band structures between these two solutions in these materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Direct comparison of using a Z -transformation instead of the traditional $Q^2$ for extraction of the proton radius from $e-p$ scattering data

A discrepancy in the determination of the proton’s charge radius, r p , between muonic hydrogen spectroscopy versus classic atomic spectroscopy and electron scattering data has become known as the proton radius puzzle. Extractions of r p from electron scattering data require determination of the slope of the proton’s charge form factor, $G$$^{p}_{E}$, in the limit of Q 2 → 0 through fitting and extrapolation. Some works have presented the Z-transformation fitting technique as the best choice for this type of extraction due to the true functional form of $G$$^{p}_{E}$ being mathematically guaranteed to exist within the parameter-space of the fit function. In this work, we test this claim by examining the mathematical bias and variances introduced by this technique as compared to the more traditional Q 2 fits using statistically sampled $G$$^{p}_{E}$ parameterizations with known input radii. Furthermore, our tests conclude that the quality of the Z-transformation technique depends on the range of data used. In the case of new experiments, the fit function and technique should be selected in advance by generating realistic pseudodata and assessing the power of different techniques.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRSDate not supplied

Machine Learning Methods for Estimating Propeller Source Noise Spheres

In this work, several neural network function approximations are compared for inter- polating, storing, and sampling acoustic source spheres with applications to propeller noise estimation. These methods are compared using an acoustic model of the three bladed GL-10 propeller at different flight conditions, with training data generated using NASA’s ANOPP-PAS module. The source spheres used to train the networks capture the tonal propeller noise due to both the blade thickness and loading. This tonal noise prediction method allows the vehicle noise to be estimated for auralization and acoustic control. Three radial basis function neural network architectures are compared in this work. The first two networks directly estimate the parameters of the source sphere at different flight conditions but differ in the number of layers used. The third network estimates the parameters of the source sphere using a weighted combination of spherical basis functions. These networks are trained on numerically generated source spheres, with operating points given in terms of the propeller rotation rate, freestream speed, and propeller angle of attack. The performance of the neural network is determined using a validation dataset of withheld data points. This performance is quantified in terms of the approximation error, training time, and sample time. The third network, which estimates the weights of the spherical basis functions, performs the best in both average and maximum approximation errors in all cases. This network’s worst case performance is 5.6 % relative dif- ference of a model parameter associated with acoustic pressure. The direct estimation network with a single layer has the worst approximation error in all cases. Additionally, the spherically defined network has the slowest sample time at 0.05 seconds per thousand points. Both direct estimation methods produce a thousand sample points in approximately 0.001 seconds.

Acoustics↗
DOE OSTI2019

New exact anisotropic static spherically symmetric stellar models satisfying the Eiesland condition

In a very recent work (Murad, 2018) one of the present authors represents an algorithm for constructing all the static spherically symmetric exact anisotropic solutions of Einstein’s field equations of embedding class 1 based on a single generating function. In this work we apply the same algorithm to construct stellar models by generalizing some previous and offering some new forms of the generating function. The resulting equation of state and energy density, radial and tangential pressures, pressure anisotropy for a compact star having mass and radius similar to PSR J1614-2230 have been analyzed and the numerical values are found quite in agreement with the authors’ previous works.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Global Diversity and Biogeography of the Zostera marina Mycobiome

Seagrasses are marine flowering plants that provide critical ecosystem services in coastal environments worldwide. Marine fungi are often overlooked in microbiome and seagrass studies, despite terrestrial fungi having critical functional roles as decomposers, pathogens, or endophytes in global ecosystems. Here, we characterize the distribution of fungi associated with the seagrass Zostera marina, using leaves, roots, and rhizosphere sediment from 16 locations across its full biogeographic range. Using high-throughput sequencing of the ribosomal internal transcribed spacer (ITS) region and 18S rRNA gene, we first measured fungal community composition and diversity. We then tested hypotheses of neutral community assembly theory and the degree to which deviations suggested that amplicon sequence variants (ASVs) were plant selected or dispersal limited. Finally, we identified a core mycobiome and investigated the global distribution of differentially abundant ASVs. We found that the fungal community is significantly different between sites and that the leaf mycobiome follows a weak but significant pattern of distance decay in the Pacific Ocean. Generally, there was evidence for both deterministic and stochastic factors contributing to community assembly of the mycobiome, with most taxa assembling through stochastic processes. The Z. marina core leaf and root mycobiomes were dominated by unclassified Sordariomycetes spp., unclassified Chytridiomycota lineages (including Lobulomycetaceae spp.), unclassified Capnodiales spp., and Saccharomyces sp. It is clear from the many unclassified fungal ASVs and fungal functional guilds that knowledge of marine fungi is still rudimentary. Further studies characterizing seagrass-associated fungi are needed to understand the roles of these microorganisms generally and when associated with seagrasses. Fungi have important functional roles when associated with land plants, yet very little is known about the roles of fungi associated with marine plants, like seagrasses. In this study, we report the results of a global effort to characterize the fungi associated with the seagrass Zostera marina across its full biogeographic range. Although we defined a putative global core fungal community, it is apparent from the many fungal sequences and predicted functional guilds that had no matches to existing databases that general knowledge of seagrass-associated fungi and marine fungi is lacking. This work serves as an important foundational step toward future work investigating the functional ramifications of fungi in the marine ecosystem.

ITS2↗
DOE OSTI2022

Ab-Initio Investigation of Finite Size Effects in Rutile Titania Nanoparticles with Semilocal and Nonlocal Density Functionals

In this work, we employ hybrid and generalized gradient approximation (GGA) level density functional theory (DFT) calculations to investigate the convergence of surface properties and electronic gap of rutile titania nanoparticles with particle size. The surface energies and electronic gaps are calculated for cuboidal particles with minimum dimension ranging from 3.7 Angstrom (24 atoms) to 10.3 Angstrom (384 atoms) using a highly-parallel real-space DFT code to enable hybrid level DFT calculations of larger nanoparticles than are typically practical. We deconvolute the geometric and electronic finite size effects in surface energy, and evaluate the influence of defects on electronic gap and density of states (DOS). The electronic finite size effects in surface energy vanish when the minimum length scale of the nanoparticles becomes greater than 10 Angstrom. We show that this length scale is consistent with a computationally efficient numerical analysis of the characteristic length scale of electronic interactions. The surface energy of nanoparticles having minimum dimension beyond this characteristic length can be approximated using slab calculations that account for the geometric defects. In contrast, the finite size effects on the electronic gap and DOS is highly dependent on the shape and size of these particles. Furthermore, the DOS for cuboidal particles and more realistic particles constructed using the Wulff algorithm reveal that defect states within the electronic gap play a key role in determining the eigen value distribution of nanoparticles and the electronic gap does not converge to the bulk limit for the particle sizes investigated.

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

Understanding the effect of density functional choice and van der Waals treatment on predicting the binding configuration, loading, and stability of amine-grafted metal organic frameworks

Metal organic frameworks (MOFs) are crystalline, three-dimensional structures with high surface areas and tunable porosities. Made from metal nodes connected by organic linkers, the exact properties of a given MOF are determined by node and linker choice. MOFs hold promise for numerous applications, including gas capture and storage. M2(4,4′-dioxidobiphenyl-3,3′-dicarboxylate)—henceforth simply M2(dobpdc), with M = Mg, Mn, Fe, Co, Ni, Cu, or Zn—is regarded as one of the most promising structures for CO2 capture applications. Further modification of the MOF with diamines or tetramines can significantly boost gas species selectivity, a necessity for the ultra-dilute CO2 concentrations in the direct-air capture of CO2. There are countless potential diamines and tetramines, paving the way for a vast number of potential sorbents to be probed for CO2 adsorption properties. The number of amines and their configuration in the MOF pore are key drivers of CO2 adsorption capacity and kinetics, and so a validation of computational prediction of these quantities is required to suitably use computational methods in the discovery and screening of amine-functionalized sorbents. In this work, we study the predictive accuracy of density functional theory and related calculations on amine loading and configuration for one diamine and two tetramines. In particular, we explore the Perdew–Burke–Ernzerhof (PBE) functional and its formulation for solids (PBEsol) with and without the Grimme-D2 and Grimme-D3 pairwise corrections (PBE+D2/3 and PBEsol+D2/3), two revised PBE functionals with the Grimme-D2 and Grimme-D3 pairwise corrections (RPBE+D2/3 and revPBE+D2/3), and the nonlocal van der Waals correlation (vdW-DF2) functional. We also investigate a universal graph deep learning interatomic potential’s (M3GNet) predictive accuracy for loading and configuration. These results allow us to identify a useful screening procedure for configuration prediction that has a coarse component for quick evaluation and a higher accuracy component for detailed analysis. Our general observation is that the neural network-based potential can be used as a high-level and rapid screening tool, whereas PBEsol+D3 gives a completely qualitatively predictive picture across all systems studied, and can thus be used for high accuracy motif predictions. We close by briefly exploring the predictions of relative thermal stability for the different functionals and dispersion corrections.

Chemistry↗
NASA NTRS1984

ECUT: Energy Conversion and Utilization Technologies program - Biocatalysis research activity

The activities of the Biocatalysis Research Activity are organized into the Biocatalysis and Molecular Modeling work elements and a supporting planning and analysis function. In the Biocatalysis work element, progress is made in developing a method for stabilizing genetically engineered traits in microorganisms, refining a technique for monitoring cells that are genetically engineered, and identifying strains of fungi for highly efficient preprocessing of biomass for optimizing the efficiency of bioreactors. In the Molecular Modeling work element, a preliminary model of the behavior of enzymes is developed. A preliminary investigation of the potential for synthesizing enzymes for use in electrochemical processes is completed. Contact with industry and universities is made to define key biocatalysis technical issues and to broaden the range of potential participants in the activity. Analyses are conducted to identify and evaluate potential concepts for future research funding.

Wilcox, R.↗
DOE OSTI2021

High Interfacial-Energy and Lithiophilic Janus Interphase Enables Stable Lithium Metal Anodes

The stability of solid electrolyte interphase (SEI) layers is critical for developing lithium (Li) metal batteries. However, the fabrication of stable SEI layers is plagued by un-controlled structures, properties, and functions. In this work a controllable design of an ordered LiF-rich and lithiophilic hybrid Janus interphase (LiF-HJI) is reported using organic fluorination reagent as a functional SEI precursor. The LiF-HJI with a lower crystalline LiF layer and an upper Li organosulfide layer provides high interfacial energy with the Li metal and strong Li-ion affinity, allows homogenous Li-ion distribution, fast and uniform Li-ion transport, and excellent mechanical and passivation properties, enabling stable Li metal anodes under harsh conditions, such as high deposition capacities (6 mA h cm -2 ), current densities (10 mA cm -2 ), and rates (5 C). Stable LiF-HJI@Li greatly improves cycling stability and capacity retention (80.1% after 300 cycles) of Li||LiNi 0.8 Co 0.1 Mn 0.1 O 2 cells at a commercial-level areal capacity (≈4.2 mA h cm -2 ). Even under a lean-electrolyte condition of 3 g Ah -1 , 80% capacity retention can be maintained after 100 cycles, demonstrating excellent cycling performance under such harsh conditions.

25 ENERGY STORAGE↗
DOE OSTI2025

Working with Bézier Curves as bases for Functional Expansion Tallies

Functional expansion tallies (FETs) are powerful tools for getting more information per history from Monte Carlo simulations, but in the past they have been constrained to orthogonal bases. Bézier curves are used widely in computer aided design (CAD) geometry kernels and could be well-suited for FETs due to their ability to assume many arbitrary shapes, but they use nonorthogonal bases. Recent developments in 2021 have made nonorthogonal FETs possible. The convergence of Bézier curve FETs in both polynomial order and number of samples is explored in this work. It is shown that these bases are well-suited for representing normal distributions and this opens the door to the possibility of other CAD-derived FET bases.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Surface functionality and formation mechanisms of carbon and graphene quantum dots

Graphene quantum dots (GQDs) and Carbon dots (C-dots) have been widely studied in recent years due to their structural and optoelectrical properties. These properties have prompted the exploration of the role of these carbon-based materials in many potential applications. This includes solar cells, photodetectors, bioimaging, sensors, batteries and drug delivery. These properties and applications of GQDs and C-dots are highly dependent on their size, shape and surface functionality. In this work, GQDs and C-dots mixtures have been synthesized by an inexpensive wet chemical method by varying the synthesis temperature from 85°, 100° to 115 °C. The surface functionalities of the synthesized carbon-based materials were investigated by several analytical methods. We discovered a higher degree of oxidation at higher temperatures. The mechanism of formation of different sized GQDs and C-dots with different functionalities have been explained with the help of XPS and NEXAFS analysis. The influence of size and surface functionalities on the optical properties of these nanomaterials is analyzed by UV–Vis and PL spectroscopic techniques. Furthermore, this study demonstrates that physicochemical properties of GQDs and C-dots can be controlled by changing the synthesis temperature.

36 MATERIALS SCIENCE↗