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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Ultra-high temperature testing and performance of L-PBF C103

Additive Manufacturing (AM) of refractory alloys is gaining traction as a materials processing route for components subject to extreme temperature environments. Due to the low oxidation resistance of refractory alloys, novel methods for evaluating their elevated temperature performance must be developed. In this work, a Gleeble® 3800 thermomechanical load frame was modified to evaluate the mechanical properties of laser powder bed fusion (L-PBF) consolidated niobium alloy C103 ranging from room temperature (RT) to 1400 °C. The fixturing and sample geometry were designed to accommodate Joule heating and prevent damage to the test chamber. Oxidation of the samples was minimized via testing in vacuum level of 1E-5 Torr. Ultimate tensile strength (UTS), yield strength (YS), elongation, and strain-hardening behavior were determined as a function of temperature. L-PBF C103 presented an average UTS of ∼650 MPa and over 25 % elongation at RT. Above RT, the UTS and YS dropped then leveled off from 500 °C to 1000 °C with values ranging from ∼400 MPa to ∼460 MPa, which is consistent with dynamic strain aging observed in this class of alloys. The strength rapidly declined after 1200 °C to ∼150 MPa at 1400 °C. Fractography indicated ductile fractures for the C103 at all test temperatures, and Electron Backscatter Diffraction (EBSD) analysis revealed a textured microstructure and the presence of dynamic recrystallization within the necked region of the sample tested at 1400 °C.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Biochemical methane potential (BMP) tests: Reducing test time by early parameter estimation

Highlights: • Early parameters prediction of BMP model is achieved by using sensitivity functions. • Minimum testing time for early parameter estimation is related to kinetic constant. • Balanced regression improves the accuracy of estimated parameters. - Abstract: Biochemical methane potential (BMP) test is a key analytical technique to assess the implementation and optimisation of anaerobic biotechnologies. However, this technique is characterised by long testing times (from 20 to >100 days), which is not suitable for waste utilities, consulting companies or plants operators whose decision-making processes cannot be held for such a long time. This study develops a statistically robust mathematical strategy using sensitivity functions for early prediction of BMP first-order model parameters, i.e. methane yield (B{sub 0}) and kinetic constant rate (k). The minimum testing time for early parameter estimation showed a potential correlation with the k value, where (i) slowly biodegradable substrates (k ≤ 0.1 d{sup −1}) have a minimum testing times of ≥15 days, (ii) moderately biodegradable substrates (0.1 −1 ) have a minimum testing times between 8 and 15 days, and (iii) rapidly biodegradable substrates (k ≥ 0.2 d{sup −1}) have testing times lower than 7 days.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Facile Decomposition of Organophosphonates by Dual Lewis Sites on a Fe 3 O 4 (111) Film

Dimethyl methylphosphonate (DMMP) is used as a simulant for toxic nerve agents and pesticides, rendering the understanding of surface chemistry requisite to design effective materials for organophosphonate (catalytic) decomposition at room temperature. In this work, DMMP surface chemistry is studied on an iron oxide surface in a very well-defined environment using temperature-programmed reaction, isotopic labeling, scanning tunneling microscopy, X-ray photoelectron spectroscopy, and density functional theory. DMMP, (CH 3 O) 2 P(O)(CH 3 ), dissociates to yield methoxy and methyl methylphosphonate, (CH 3 O)P(O) 2 (CH 3 ), on the surface at room temperature. At higher temperatures, dimethyl ether is formed via intramolecular reaction, followed by the formation of formaldehyde and methanol from adsorbed methoxy decomposition during temperature-programmed reaction. Ultimately, stochiometric combustion at 870 K produces CO, H 2 C=O, and CO 2 via reaction with lattice oxygen, with PO x remaining on the surface. Excess oxygen from the bulk is required to drive these higher temperature pathways. Neither hydrolysis nor a photoreaction is observed, when exposing the adsorbed DMMP to water or light above the band gap, respectively. No evolution of P-containing species is detected, indicating efficient trapping of this contaminant. The activity for DMMP decomposition at room temperature is reduced by the accumulation of PO x . However, a significant amount of reaction persists after multiple temperature-programmed reaction experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Coupled LiPF 6 Decomposition and Carbonate Dehydrogenation Enhanced by Highly Covalent Metal Oxides in High-Energy Li-Ion Batteries

The (electro)chemical reactions between positive electrodes and electrolytes are not well understood. In this work, we examined the oxidation of a LiPF 6 -based electrolyte with ethylene carbonate (EC) with layered lithium nickel, manganese, and cobalt oxides (NMC). Density functional theory calculations showed that the driving force for EC dehydrogenation on oxides, yielding surface protic species, increased with greater Ni content in NMC. Ex situ infrared and Raman spectroscopy revealed experimental evidence for EC dehydrogenation on charged NMC surfaces. Protic species on charged NMC surfaces from EC dehydrogenation could further react with LiPF 6 to generate less-coordinated F species such as PF 3 O-like and lithium nickel oxyfluoride species on charged NMC particles and HF and PF 2 O 2 – in the electrolyte. Larger degree of salt decomposition was coupled with increasing EC dehydrogenation on charged NMC with increasing Ni or lithium deintercalation. Lastly, an oxide-mediated chemical oxidation of electrolytes was proposed, providing new insights in stabilizing high-energy positive electrodes and improving Li-ion battery cycle life.

36 MATERIALS SCIENCE↗
DOE OSTI2022

How Cooperatively Folding Are Homopolymer Molecular Knots?

Detailed thermodynamic analysis of complex systems with multiple stable configurational states allows for insight into the cooperativity of each individual transition. In this work, we derive a heat capacity decomposition comprising contributions from each individual configurational state, which together sum to a baseline heat capacity, and contributions from each state-to-state transition. We apply this analysis framework to a series of replica exchange molecular dynamics simulations of linear and 1-1 coarse-grained homo-oligomer models, which fold into stable, configurationally well-defined molecular knots, in order to better understand the parameters leading to stable and cooperative folding of these knots. We find that a stiff harmonic backbone bending angle potential is key to achieving knots with specific 3D structures. Tuning the backbone equilibrium angle in small increments yields a variety of knot topologies. Populations of different knotted states as a function of temperature can also be manipulated by tuning the backbone torsion stiffness or by adding side-chain beads. We find that sharp total heat capacity peaks for the homo-oligomer knots are largely due to a coil-to-globule transition rather than a cooperative knotting step. Furthermore, in some cases, the cooperativity of globule-to-knot and coil-to-globule transitions is comparable, suggesting that highly cooperative folding to knotted structures can be achieved by refining the model parameters or adding sequence specificity.

36 MATERIALS SCIENCE↗
DOE OSTI2024

SAGA1 and MITH1 produce matrix-traversing membranes in the CO2-fixing pyrenoid

Abstract Approximately one-third of global CO 2 assimilation is performed by the pyrenoid, a liquid-like organelle found in most algae and some plants. Specialized pyrenoid-traversing membranes are hypothesized to drive CO 2 assimilation in the pyrenoid by delivering concentrated CO 2 , but how these membranes are made to traverse the pyrenoid matrix remains unknown. Here we show that proteins SAGA1 and MITH1 cause membranes to traverse the pyrenoid matrix in the model alga Chlamydomonas reinhardtii . Mutants deficient in SAGA1 or MITH1 lack matrix-traversing membranes and exhibit growth defects under CO 2 -limiting conditions. Expression of SAGA1 and MITH1 together in a heterologous system, the model plant Arabidopsis thaliana , produces matrix-traversing membranes. Both proteins localize to matrix-traversing membranes. SAGA1 binds to the major matrix component, Rubisco, and is necessary to initiate matrix-traversing membranes. MITH1 binds to SAGA1 and is necessary for extension of membranes through the matrix. Our data suggest that SAGA1 and MITH1 cause membranes to traverse the matrix by creating an adhesive interaction between the membrane and matrix. Our study identifies and characterizes key factors in the biogenesis of pyrenoid matrix-traversing membranes, demonstrates the importance of these membranes to pyrenoid function and marks a key milestone toward pyrenoid engineering into crops for improving yields.

Hennacy, Jessica H.↗
DOE OSTI2021

Tandem synthesis of tetrahydroquinolines and identification of the reaction network by operando NMR

The study of the reaction mechanism and complex network for heterogeneously catalyzed tandem reactions is challenging but can guide reaction design and optimization. Here, we describe a case study using bifunctional metal–organic framework supported Pd nanoparticles (Pd/UiO-66(HCl)) for the one-pot tandem synthesis of substituted tetrahydroquinolines via the Claisen–Schmidt condensation and reductive intramolecular cyclization. The directly observed evolution of intermediates and products, including reactive species containing hydroxylamine group and unstable intermediate 2-phenyl-3,4-dihydroquinoline, was enabled by operando magic angle spinning nuclear magnetic resonance studies under 50 bar H 2 . The reaction network of the tandem reaction is deduced based on reaction kinetic information obtained from the operando study. The optimized procedure was applied to various acetophenone and nitrobenzaldehyde derivatives carrying different functional groups, and eight valuable substituted tetrahydroquinolines were obtained in moderate to good yields. This work provides a molecular-level understanding of the catalytic system and brings up new opportunities for efficient and sustainable synthesis of medicinally relevant building blocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Accurate double excitations from ensemble density functional calculations

The recent use of a new ensemble in density functional theory (DFT) to produce direct corrections to the Kohn-Sham transitions yields the elusive double excitations that are missed by time-dependent DFT (TDDFT) with the standard adiabatic approximation. But accuracies are lower than for single excitations, and formal arguments about TDDFT suggest that a correction kernel is needed. In principle, ensemble DFT with direct corrections at the exchange level must yield accurate doubles in the weakly correlated limit. We illustrate with exact calculations and analytic results on the Hubbard dimer. Lastly, we also explain the error in formal arguments in TDDFT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

The pH-dependent orientation of N3 dye on a gold substrate is revealed using heterodyne-detected vibrational sum frequency generation spectroscopy

We report on systematic changes to the adsorption geometry of the dye N3 {[cis-bis(isothiocyanato)bis(2,2' -bipyridyl-4,4' -dicarboxylato ruthenium(II)]} on a gold substrate as the pH of the deposition environment is altered. The protonation states of the four --COOH groups of the N3 dye change according to the modified pH conditions, thus affecting the number of --COOH and --NCS functional groups that participate in the adsorption to gold. Here, we use heterodyne detected vibrational sum frequency generation (HD-VSFG) spectroscopy to obtain surface specific vibrational information on both --COOH and --NCS groups as a function of pH of the deposition conditions. Polarization-dependent HD-VSFG yields sets of complex χ (2) spectra, enabling us to perform a simultaneous fitting procedure to the polarization-dependent real and imaginary components and thus extract detailed structural information of the N3/gold interface. Overall, our results show that N3 preferentially adsorbs to gold either with two --COOH groups and one --NCS group in more acidic conditions or with one --COOH group and two --NCS groups in more basic conditions.

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

Phylogenetic distribution and experimental characterization of corrinoid production and dependence in soil bacterial isolates

Abstract Soil microbial communities impact carbon sequestration and release, biogeochemical cycling, and agricultural yields. These global effects rely on metabolic interactions that modulate community composition and function. However, the physicochemical and taxonomic complexity of soil and the scarcity of available isolates for phenotypic testing are significant barriers to studying soil microbial interactions. Corrinoids—the vitamin B12 family of cofactors—are critical for microbial metabolism, yet they are synthesized by only a subset of microbiome members. Here, we evaluated corrinoid production and dependence in soil bacteria as a model to investigate the ecological roles of microorganisms involved in metabolic interactions. We isolated and characterized a taxonomically diverse collection of 161 soil bacteria from a single study site. Most corrinoid-dependent bacteria in the collection prefer B12 over other corrinoids, while all tested producers synthesize B12, indicating metabolic compatibility between producers and dependents in the collection. Furthermore, a subset of producers release B12 at levels sufficient to support dependent isolates in laboratory culture at estimated ratios of up to 1000 dependents per producer. Within our isolate collection, we did not find strong phylogenetic patterns in corrinoid production or dependence. Upon investigating trends in the phylogenetic dispersion of corrinoid metabolism categories across sequenced bacteria from various environments, we found that these traits are conserved in 47 out of 85 genera. Together, these phenotypic and genomic results provide evidence for corrinoid-based metabolic interactions among bacteria and provide a framework for the study of nutrient-sharing ecological interactions in microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Emulating galaxy clustering and galaxy–galaxy lensing into the deeply non-linear regime: methodology, information, and forecasts

The combination of galaxy–galaxy lensing (GGL) with galaxy clustering is one of the most promising routes to determining the amplitude of matter clustering at low redshifts. Here, we show that extending clustering+GGL analyses from the linear regime down to |${\sim } 0.5 \, h^{-1}$| Mpc scales increases their constraining power considerably, even after marginalizing over a flexible model of non-linear galaxy bias. Using a grid of cosmological N -body simulations, we construct a Taylor-expansion emulator that predicts the galaxy autocorrelation ξ gg ( r ) and galaxy-matter cross-correlation ξ gm ( r ) as a function of σ 8 , Ω m , and halo occupation distribution (HOD) parameters, which are allowed to vary with large-scale environment to represent possible effects of galaxy assembly bias. We present forecasts for a fiducial case that corresponds to BOSS LOWZ galaxy clustering and SDSS-depth weak lensing (effective source density ~0.3 arcmin -2 ). Using tangential shear and projected correlation function measurements over |$0.5 \le r_\mathrm{ p} \le 30 \, h^{-1}$| Mpc yields a 2 per cent constraint on the parameter combination |$\sigma _8\Omega _\mathrm{ m}^{0.6}$| , a factor of two better than a constraint that excludes non-linear scales ( |$r_\mathrm{ p} \gt 2 \, h^{-1}$| Mpc, |$4 \, h^{-1}$| Mpc for γ t , |$w$| p ). Much of this improvement comes from the non-linear clustering information, which breaks degeneracies among HOD parameters. Increasing the effective source density to 3 arcmin -2 sharpens the constraint on |$\sigma _8\Omega _\mathrm{ m}^{0.6}$| by a further factor of two. With robust modelling into the non-linear regime, low-redshift measurements of matter clustering at the 1-per cent level with clustering+GGL alone are well within reach of current data sets such as those provided by the Dark Energy Survey.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Magnetic excitations in the bulk multiferroic two-dimensional triangular lattice antiferromagnet ( Lu , Sc ) FeO 3

Noncollinear two-dimensional triangular lattice antiferromagnets (2D TLAFs) are currently an area of very active research due to their unique magnetic properties, which lead to nontrivial quantum effects that experimentally manifest themselves in the spin excitation spectra. Recent examples of such insulating 2D TLAFs include (Y, Lu) MnO 3 , LiCrO 2 , and CuCrO 2 . Hexagonal LuFeO 3 is a recently synthesized 2D TLAF which exhibits properties of an ideal multiferroic material, partially because of the high spin (S = 5/2) and strong magnetic superexchange interactions. We report the full range of spin dynamics in a bulk single crystal of (Lu 0.6 Sc 0.4 )FeO 3 (Sc doping to stabilize the hexagonal structure) measured via time-of-flight inelastic neutron scattering. Modeling with linear spin-wave theory yields a nearest-neighbor exchange coupling of J = 4.0(2) meV (density functional theory calculations for h – LuFeO 3 predicted a value of 6.31 meV) and anisotropy values of K D = 0.17(1) meV (easy plane) and K A = – 0.05(1) meV (local easy axis). Furthermore, it is observed that the magnon bandwidth of the spin-wave spectra is twice as large for h – (Lu,Sc)FeO 3 as it is for h – LuMnO 3 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Structure refinement and anisotropic atomic displacement parameters of 1M Illite: Rietveld and pair distribution function analysis using synchrotron X-ray radiation

Illite, a widespread clay mineral, plays a pivotal role in geological processes, notably as an indicator in diagenetic and hydrothermal alteration environments, and possesses significant industrial relevance in applications including ceramics, construction and catalysis. However, challenges including its nanoscale crystallinity, structural disorder and frequent interstratification with other clay minerals have hindered detailed structural characterization using conventional X-ray diffraction (XRD) techniques. This study employs integrated synchrotron XRD and pair distribution function (PDF) analysis to elucidate the crystal structure of the 1M illite polytype, yielding the first determination of its anisotropic atomic displacement parameters (U aniso ). TheseU aniso parameters provide critical insights into atomic dynamics and static disorder within the structure, enabling a more refined understanding of structure–property relationships. This integrated approach, combining synchrotron XRD, Rietveld refinement and PDF analysis, yields a comprehensive structural characterization, capturing both average crystallographic and local atomic arrangements. Considering illite's widespread geological occurrence and industrial importance, this high-precision structural dataset, especially the determinedU aniso values, provides a crucial benchmark for future modeling and simulation efforts targeting accurate prediction of its physicochemical behavior.

Chemistry↗
DOE OSTI2021

Compressive Neural Representations of Volumetric Scalar Fields

Here, we present an approach for compressing volumetric scalar fields using implicit neural representations. Our approach represents a scalar field as a learned function, wherein a neural network maps a point in the domain to an output scalar value. By setting the number of weights of the neural network to be smaller than the input size, we achieve compressed representations of scalar fields, thus framing compression as a type of function approximation. Combined with carefully quantizing network weights, we show that this approach yields highly compact representations that outperform state-of-the-art volume compression approaches. The conceptual simplicity of our approach enables a number of benefits, such as support for time-varying scalar fields, optimizing to preserve spatial gradients, and random-access field evaluation. We study the impact of network design choices on compression performance, highlighting how simple network architectures are effective for a broad range of volumes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Direct measurements of DOCO isomers in the kinetics of OD + CO

Quantitative and mechanistically detailed kinetics of the reaction of hydroxyl radical (OH) with carbon monoxide (CO) have been a longstanding goal of contemporary chemical kinetics. This fundamental prototype reaction plays an important role in atmospheric and combustion chemistry, motivating studies for accurate determination of the reaction rate coefficient and its pressure and temperature dependence at thermal reaction conditions. This intricate dependence can be traced directly to details of the underlying dynamics (formation, isomerization, and dissociation) involving the reactive intermediates cis- and trans-HOCO, which can only be observed transiently. Using time-resolved frequency comb spectroscopy, comprehensive mechanistic elucidation of the kinetics of the isotopic analog deuteroxyl radical (OD) with CO has been realized. By monitoring the concentrations of reactants, intermediates, and products in real time, the branching and isomerization kinetics and absolute yields of all species in the OD + CO reaction are quantified as a function of pressure and collision partner.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Adjoint-optimized nanoscale light extractor for nitrogen-vacancy centers in diamond

Abstract We designed a nanoscale light extractor (NLE) for the efficient outcoupling and beaming of broadband light emitted by shallow, negatively charged nitrogen-vacancy (NV) centers in bulk diamond. The NLE consists of a patterned silicon layer on diamond and requires no etching of the diamond surface. Our design process is based on adjoint optimization using broadband time-domain simulations and yields structures that are inherently robust to positioning and fabrication errors. Our NLE functions like a transmission antenna for the NV center, enhancing the optical power extracted from an NV center positioned 10 nm below the diamond surface by a factor of more than 35, and beaming the light into a ±30° cone in the far field. This approach to light extraction can be readily adapted to other solid-state color centers.

42 ENGINEERING↗
DOE OSTI2024

Predictive Modeling of NOx Emissions from Lean Direct Injection of Hydrogen and Hydrogen/Natural Gas Blends Using Flame Imaging and Machine Learning

This research paper explores the use of machine learning to relate images of flame structure and luminosity to measured NOx emissions. Images of reactions produced by 16 aero-engine derived injectors for a ground-based turbine operated on a range of fuel compositions, air pressure drops, preheat temperatures and adiabatic flame temperatures were captured and postprocessed. The experimental investigations were conducted under atmospheric conditions, capturing CO, NO and NOx emissions data and OH* chemiluminescence images from 27 test conditions. The injector geometry and test conditions were based on a statistically designed test plan. These results were first analyzed using the traditional analysis approach of analysis of variance (ANOVA). The statistically based test plan yielded 432 data points, leading to a correlation for NOx emissions as a function of injector geometry, test conditions and imaging responses, with 70.2% accuracy. As an alternative approach to predicting emissions using imaging diagnostics as well as injector geometry and test conditions, a random forest machine learning algorithm was also applied to the data and was able to achieve an accuracy of 82.6%. This study offers insights into the factors influencing emissions in ground-based turbines while emphasizing the potential of machine learning algorithms in constructing predictive models for complex systems.

08 HYDROGEN↗