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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Hydrocarbon production reduces natural methane seeps in the Santa Barbara channel

Abundant natural hydrocarbon seepage in the Santa Barbara Channel includes large amounts of gas, mainly methane. Numerous seeps are focused along a faulted anticlinal axis where in 1982 ARCO placed two large (900 m 2 each) steel gas capture tents on the seabed adjacent to Platform Holly. The seep rate into the tent at high tide is about 5 percent less compared with low tide (2m tidal range). An earthquake in 2013 (M = 4.8) did not affect seepage rates into the steel tents, indicating that gas was not released by fault dilation. The CO 2 and H 2 S content of the captured gas are anomalously low compared to typical Holly gas due to bacterial and sea water-gas interaction at the seep tent. Platform Holly production had an overall effect of reducing gas seepage into the tents over time. Wells beneath the tents at 1-km depth had a much greater influence on the seepage rate than more distal wells. The nearby wells had a direct effect on seepage rate when they were put on production (seepage decreased) versus shut in (seepage increased). The response time was within hours, indicating a direct hydraulic connection between the reservoir at 1 km subsea and the seabed. Permeability of the approximate 1-km fault pathway between the reservoir and the seep tent is calculated to be about 3 × 10 -14 m 2 (30 millidarcys). Gradually, the seep rate declined from peak flow in 1990 (4.5×10 4 m 3 dy-1) to less than 7.1×10 3 m 3 dy -1 in 2013. In June of 2013, a horizontal well was completed high on the structural anticline between Platform Holly and directly beneath the seep tents. Within three weeks of turning on this new well, seepage into the tents completely ceased, ending more than 30 years of natural methane seepage captured by the tents.

58 GEOSCIENCES↗
DOE OSTI2022

Transcriptional networks underlying a primary ovarian insufficiency disorder in alligators naturally exposed to EDCs

Interactions between the endocrine system and environmental contaminants are responsible for impairing reproductive development and function. Despite the taxonomic diversity of affected species and attendant complexity inherent to natural systems, the underlying signaling pathways and cellular consequences are mostly studied in lab models. To resolve the genetic and endocrine pathways that mediate affected ovarian function in organisms exposed to endocrine disrupting contaminants in their natural environments, we assessed broad-scale transcriptional and steroidogenic responses to exogenous gonadotropin stimulation in juvenile alligators (Alligator missippiensis) originating from a lake with well-documented pollution (Lake Apopka, FL) and a nearby reference site (Lake Woodruff, FL). Here, we found that individuals from Lake Apopka are characterized by hyperandrogenism and display hyper-sensitive transcriptional responses to gonadotropin stimulation when compared to individuals from Lake Woodruff. Site-specific transcriptomic divergence appears to be driven by wholly distinct subsets of transcriptional regulators, indicating alterations to fundamental genetic pathways governing ovarian function. Consistent with broad-scale transcriptional differences, ovaries of Lake Apopka alligators displayed impediments to folliculogenesis, with larger germinal beds and decreased numbers of late-stage follicles. After resolving the ovarian transcriptome into clusters of co-expressed genes, most site-associated modules were correlated to ovarian follicule phenotypes across individuals. However, expression of two site-specific clusters were independent of ovarian cellular architecture and are hypothesized to represent alterations to cell-autonomous transcriptional programs. Collectively, our findings provide high resolution mapping of transcriptional patterns to specific reproductive function and advance our mechanistic understanding regarding impaired reproductive health in an established model of environmental endocrine disruption.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Fine-tuned thermally cross-linkable 6FDA-based polyimide membranes for aggressive natural gas separation

Glassy 6FDA-based polyimides are attractive membrane materials for many industrially important gas separations; however, plasticization in aggressive natural gas often causes significant loss in CO 2 /CH 4 selectivity. In this study, a family of thermally cross-linkable 6FDA-based polyimides containing carboxyl groups were synthesized and cross-linked as dense films via decarboxylation-induced thermal crosslinking. As well as chemical structure, crosslinking temperatures above and below T g are shown to be synergistic tools. Our results demonstrate that structure evolution during the decarboxylation-induced crosslinking process is affected significantly by the 3,5-diaminobenzoic acid (DABA) content in the polymer backbone. Even for a 50/50 CO 2 /CH 4 binary mixture with feed pressure up to 800 psia, decarboxylation-induced crosslinking provides attractive gas separation performance and plasticization resistance. Combined facile structure tunability, crosslinkability and high asymmetric fiber spinnability make the cross-linkable 6FDA-based polyimides a versatile platform for diverse aggressive natural gas feeds encountered in practice. Finally, our study provides insights into material design of thermally cross-linkable polymer membranes for such a broad spectrum of aggressive gas separations.

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

Code validation of SAM using natural-circulation experimental data from the compact integral effects test (CIET) facility

The primary objective of this study is to validate the system analysis code, SAM, using experimental data from the Compact Integral Effects Test (CIET) experimental loop. SAM is a modern system analysis code being developed at Argonne National Laboratory for safety analysis of designs for advanced non-light water reactors (non-LWRs), such as sodium-cooled fast reactors, high-temperature gas-cooled reactors, and fluoride salt-cooled high-temperature reactors (FHRs). To support SAM code development for the wide range of non-LWR applications, it is of paramount importance to validate the code against experiments highly relevant to these reactor concepts. Additionally, the CIET facility, which was designed to reproduce the thermal-hydraulics response of FHRs under both forced- and natural-circulation conditions, has been identified and selected as one of the benchmark test facilities for SAM code validation. In this study, two sets of available CIET tests were selected for SAM code validation purposes, namely, power step change transient tests and steady-state natural-circulation tests. For all selected tests, SAM-predicted results show very good agreement with experimental data. The successful validation of SAM against these selected CIET experiments demonstrates that the computer code is well suited for thermal-hydraulics analysis of FHR designs.

42 ENGINEERING↗
DOE OSTI2020

Identifying the nature of the QCD transition in heavy-ion collisions with deep learning

In this proceeding, we review our recent work using deep convolutional neural network (CNN) to identify the nature of the QCD transition in a hybrid modeling of heavy-ion collisions. Within this hybrid model, a viscous hydrodynamic model is coupled with a hadronic cascade “after-burner”. As a binary classification setup, we employ two different types of equations of state (EoS) of the hot medium in the hydrodynamic evolution. The resulting final-state pion spectra in the transverse momentum and azimuthal angle plane are fed to the neural network as the input data in order to distinguish different EoS. To probe the effects of the fluctuations in the event-by-event spectra, we explore different scenarios for the input data and make a comparison in a systematic way. We observe a clear hierarchy in the predictive power when the network is fed with the event-by-event, cascade-coarse-grained and event-fine-averaged spectra. The carefully-trained neural network can extract high-level features from pion spectra to identify the nature of the QCD transition in a realistic simulation scenario.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Natural top quark condensation (a redux)

The Nambu--Jona-Lasinio (NJL) model involves a pointlike 4-fermion interaction. While it gives a useful description of chiral dynamics (mainly in QCD), it nonetheless omits the crucially important internal wave-function of a two-body bound state, $\phi(r)$. This becomes significant near critical coupling where $\phi(r)$ extends to large distance, leading to dilution and suppression of induced couplings $\propto \phi(0)$, such as the Yukawa and quartic couplings, as well as reduced fine-tuning of a hierarchy. In top quark condensation, where the BEH boson is a $\bar{t}t$ bound state and we have a UV completion such as topcolor, we must go beyond the NJL model and include effects of $\phi(r)$. We provide a formulation of this for the Brout-Englert-Higgs boson, and find that it leads to an extended $\phi(r)$, a significantly reduced and natural composite scale of $M_0 \sim 6$ TeV, a successful prediction for the quartic coupling, $\lambda$, and fine tuning that is reduced to a few percent, providing a compelling candidate solution to the naturalness problem of the BEH boson. The theory is testable and new physics should begin to emerge on the multi-TeV mass scales and possibly accessible to the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Comments on “Failure analysis of corroded hydrogen-blended natural gas pipelines based on finite element analysis and genetic algorithm-back propagation neural network” [262 (2025) 111174]

This is a brief commentary paper to highlight and discuss the determination of hydrogen concentration in pipeline steel, effect of hydrogen embrittlement (HE) on the mechanical properties of the material, burst strength of corroded pipelines using finite element analysis (FEA) simulations, and curve-fit models for assessing remaining strength of X80 corroded pipelines for transporting hydrogen blended natural gas. Recently, Xie et al. [1] proposed a methodology to quantify the impact of HE on material properties and numerically determined burst pressure of X80 corroded pipelines. However, their HE quantification overestimated the degradation of tensile strength for hydrogen blending ratios beyond the original data range, and their FEA results of burst pressure are nonconservative. This work thus recharacterized the hydrogen concentration in the steel pipeline and the effect of HE on tensile strength, and then redetermined burst pressures for a set of typical corrosion defect cases considered by Xie et al. [1] based on an experimentally validated FEA modelling method. With the new FEA results, two empirical corrosion models were proposed for X80 corroded pipelines for hydrogen service. At zero hydrogen blending ratio, the novel empirical models predict burst pressures to be consistent with the industry-accepted corrosion models. Furthermore, both the numerical simulation method and the novel corrosion models are significant contributions to the pipeline industry and the hydrogen community. Application of these results will enhance the safety, reliability, and integrity of natural gas pipelines when used to transport hydrogen.

Burst pressure prediction↗
DOE OSTI2022

Current nature-based biological practices for rare earth elements extraction and recovery: Bioleaching and biosorption

There is a growing demand for advancing products and renewable technologies worldwide that rely on rare earth elements (REEs), including those directly necessary for a low-carbon energy transition, national security applications, and consumer electronics. This study focuses on current nature-based biological methods (i.e., bioleaching and biosorption) for REEs extraction from electronic wastes (e-wastes) and ore deposits. Herein, comprehensive narrative and systematic reviews of bioleaching and biosorption extraction methods are performed to identify their sustainability challenges and benefits, and highlight the potential pathways that would address the existing gaps. From the narrative review, it is evident that biological methods for REEs extraction are more environmentally friendly than conventional methods currently used in the REE mining industry (e.g., acid leaching and solvent extraction). From the systematic review, it is clear that bioleaching and biosorption research has been a rapidly growing field of interest over the last 10 years, particularly for precious metals extraction (e.g., copper and gold). From both reviews, it is apparent that REEs extraction from domestic ore deposits alone is inadequate, and sustainable REEs recovery from e-wastes is also necessary to meet the growing REEs demand. It is concluded that targeted mixed REEs extraction for specific products can be a potential pathway for sustainable REEs extraction from both ore and e-wastes that would reduce separation costs and emissions from the associated use of harsh chemicals. It is further concluded that nature-based biological REE extraction solutions offer an opportunity to generate significant socio-economic and environmental benefits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Graph interpolating activation improves both natural and robust accuracies in data-efficient deep learning

Improving the accuracy and robustness of deep neural nets (DNNs) and adapting them to small training data are primary tasks in deep learning (DL) research. In this paper, we replace the output activation function of DNNs, typically the data-agnostic softmax function, with a graph Laplacian-based high-dimensional interpolating function which, in the continuum limit, converges to the solution of a Laplace–Beltrami equation on a high-dimensional manifold. Furthermore, we propose end-to-end training and testing algorithms for this new architecture. The proposed DNN with graph interpolating activation integrates the advantages of both deep learning and manifold learning. Compared to the conventional DNNs with the softmax function as output activation, the new framework demonstrates the following major advantages: First, it is better applicable to data-efficient learning in which we train high capacity DNNs without using a large number of training data. Second, it remarkably improves both natural accuracy on the clean images and robust accuracy on the adversarial images crafted by both white-box and black-box adversarial attacks. Third, it is a natural choice for semi-supervised learning. This paper is a significant extension of our earlier work published in NeurIPS, 2018. For reproducibility, the code is available at https://github.com/BaoWangMath/DNN-DataDependentActivation .

Mathematics↗
DOE OSTI2023

Natural Abundance Isotope Ratio Measurements of Organic Molecules Using 21 T FTICR MS

Subtle variations in stable isotope ratios at natural abundance are challenging to measure but can yield critical insights into biological, physical, and geochemical processes. Well established methods, particularly multi-collector, gas-source or plasma isotope ratio mass spectrometry (IRMS) are the gold standard for stable isotope measurement but inherent limitations in these approaches make them ill-suited to determining site-specific and multiply substituted isotopic abundances of all but a few compounds, or to characterizing mixtures or larger intact molecules. Additionally, Fourier transform mass spectrometry (FTMS), namely Orbitrap mass spectrometry, has recently demonstrated the ability to measure natural abundance isotope ratios with chemically informative accuracy and precision. Here, we report the first use of Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) for the accurate (<1‰) and precise (<1‰ standard error) simultaneous determination of $δ$ 13 C and $δ$ 15 N in caffeine isotopologues and provide a discussion of the critical instrumental parameters necessary to make such measurements. Finally, we report the ability to make these measurements with online liquid chromatography, expanding the ability of this technique to explore mixtures in the future.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2020

Natural and Anthropogenically Influenced Isoprene Oxidation in Southeastern United States and Central Amazon

Anthropogenic emissions alter secondary organic aerosol (SOA) formation chemistry from naturally emitted isoprene. Here, we use correlations of tracers and tracer ratios to provide new perspectives on sulfate, NO x , and particle acidity influencing isoprene-derived SOA in two isoprene-rich forested environments representing clean to polluted conditions-wet and dry seasons in central Amazonia and Southeastern U.S. summer. We used a semivolatile thermal desorption aerosol gas chromatograph (SV-TAG) and filter samplers to measure SOA tracers indicative of isoprene/HO 2 (2-methyltetrols, C5-alkene triols, 2-methyltetrol organosulfates) and isoprene/NO x (2-methylglyceric acid, 2-methylglyceric acid organosulfate) pathways. Summed concentrations of these tracers correlated with particulate sulfate spanning three orders of magnitude, suggesting that 1 μg m -3 reduction in sulfate corresponds with at least ~0.5 μg m -3 reduction in isoprene-derived SOA. We also find that isoprene/NO x pathway SOA mass primarily comprises organosulfates, ~97% in the Amazon and ~55% in Southeastern United States. We infer under natural conditions in high isoprene emission regions that preindustrial aerosol sulfate was almost exclusively isoprene-derived organosulfates, which are traditionally thought of as representative of an anthropogenic influence. We further report the first field observations showing that particle acidity correlates positively with 2-methylglyceric acid partitioning to the gas phase and negatively with the ratio of 2-methyltetrols to C 5 -alkene triols.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Hypophosphite Is a Naturally Occurring Selective Inhibitor of Syntrophic Methanogenesis

Microbial methanogenesis is a major contributor to global warming, and methane fluxes represent a loss of energy and electrons from industrial ecosystems. The chemical space of methane control strategies is still underexplored. Most known methanogenesis inhibitors target methanogenic archaeal enzymes. However, interference with the exchange of syntrophic electron carriers (H 2 or formate) in methanogenic systems presents an additional target for methane control. Here, we show that hypophosphite (H 2 PO 2 − ), an inorganic formate analogue, is a potent and selective inhibitor of syntrophic methanogenesis versus primary fermentation in rice field sediments and cattle rumens. Hypophosphite is also generally recognized as safe and relatively nontoxic to plants and animals. Genetic screens and physiological assays in the model methanogen Methanococcus maripaludis S2 implicate formate metabolism as the target of hypophosphite inhibition. Currently, there is no known biological pathway for anaerobic hypophosphite oxidation, and hypophosphite is stable in anoxic sediments for weeks to months. Given its widespread natural occurrence, we propose that hypophosphite may modulate the carbon cycle in natural environments. Taken together, our results suggest that hypophosphite could be used as a safe, inexpensive strategy for methane control in syntrophic methanogenic ecosystems.

chemical inhibitor↗
DOE OSTI2020

Impact of natural organic matter on plutonium vadose zone migration from an NH4Pu(V)O2CO3(s) source

Large amounts of plutonium produced at the Savannah River Site (SRS) in the latter half of the last century led to the release of plutonium to the subsurface. Low-level waste containing plutonium has also been disposed of in the SRS vadose zone. The mobility and risk posed by these plutonium sources is not well understood, in part, because of unknown interactions of the various mobile plutonium species with natural organic matter (NOM). This study investigated the influence of NOM on the behavior of plutonium(V) in the vadose zone through a combination of field lysimeter and laboratory studies. Well-defined solid sources of NH4PuVO2CO3(s) placed in 5-L lysimeters containing vadose zone soils NOM-amended or unamended were exposed to natural SRS meteorological conditions for three years. These lysimeters were removed from the field and analyzed using wet chemistry methods and X-ray absorption spectroscopy (XAS). Plutonium desorption from soils recovered from the lysimeters and laboratory batch sorption experiments using Pu-free soils both indicated that surface mediated reduction of Pu(V) to Pu(IV) was influencing Pu sorption behavior. For both lysimeters (amended and unamended with NOM), Pu migrated slowly through the lysimeter core, with > 95% of the Pu remaining within 2 cm of the source. However, without the NOM amendments, Pu was transported significantly farther than in the presence of NOM. Thus, the presence of NOM appeared to decrease the mobility. Working hypotheses to explain this behavior are that 1) formation of ternary surface-NOM-Pu complexes enhanced Pu sorption affinity causing less mobility and/or 2) formation of these ternary surface-NOM-Pu complexes prevented reoxidaiton of Pu(IV) to more mobile Pu(V) in the pore water.

plutonium, organic matter↗
DOE OSTI2026

Cation Site Occupancy in Natural Ferroan Double Carbonates via Mössbauer and Fe K-Edge X-ray Absorption Spectroscopy

Double carbonates are minerals with a calcite type structure with alternating cation layers composed of Ca and Mg/Fe coordinated by carbonate groups. While the perfectly ordered AB-stacked crystal is the thermodynamically most stable configuration, natural mineral formation pathways can leave signatures through kinetically trapped disorder such as AB antisite cation substitutions. This study probes the degree of cation ordering in naturally occurring double carbonate samples.in particular, the distribution of Fe A and B crystallographic sites (A site is Ca layer and B site is Mg/Fe layer). Mössbauer, X-ray diffraction, X-ray absorption fine structure (both X-ray absorption near edge structure, XANES, and extended x-ray absorption fine structure, EXAFS), and energy dispersive X-ray spectroscopies were used to collect a comprehensive experimental data set, which we interpret using density functional theory to elucidate the structural effects of cation disorder. Our results show that the A (nominally Ca) site can host a relatively high Fe fraction. We discuss the implications in terms of mineral formation.

Boglaienko, Daria (ORCID:0000000160943877)↗
DOE OSTI2020

Garcinoic Acid Is a Natural and Selective Agonist of Pregnane X Receptor

Pregnane X receptor (PXR) is a master xenobiotic-sensing transcription factor and a validated target for immune and inflammatory diseases. The identification of chemical probes to investigate the therapeutic relevance of the receptor is still highly desired. In fact, currently available PXR ligands are not highly selective and can exhibit toxicity and/or potential off-target effects. In this study, we have identified garcinoic acid as a selective and efficient PXR agonist. The properties of this natural molecule as a specific PXR agonist were demonstrated by the screening on a panel of nuclear receptors, the assessment of the physical and thermodynamic binding affinity, and the determination of the PXR-garcinoic acid complex crystal structure. Cytotoxicity, transcriptional, and functional properties were investigated in human liver cells, and compound activity and target engagement were confirmed in vivo in mouse liver and gut tissue. In conclusion, garcinoic acid is a selective natural agonist of PXR and a promising lead compound toward the development of new PXR-regulating modulators.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Quasielastic and Inelastic Neutron Scattering Study of Ultraconfined Water in Natural Mordenite ((Ca,Na 2 ,K 2 )Al 2 Si 10 O 24 ·7H 2 O)

Mordenite ((Ca,Na 2 ,K 2 )Al 2 Si 10 O 24 ·7H 2 O) is a natural and synthetic nanoporous zeolite containing several channels of different sizes in its structure. Because of this, its structure provides an important opportunity to study the relationship between confined and ultraconfined water as these channels have sizes between those typical of these water environments. In this study, the properties of water molecules in these environments were analyzed using inelastic and quasielastic neutron spectroscopy of a natural mordenite. The quasielastic spectra showed the presence of nonfreezing, mobile water molecules through the entire temperature range of the measurements, but very little anisotropy of the dynamics measured along and perpendicular to the channels. Faster and slower quasi-elastic neutron scattering (QENS) components may be consistent with the presence of two separate classes of water molecules in mordenite. Inelastic neutron spectroscopy also found no evidence of directional anisotropy. In conclusion, the strong intensity characteristic of neutron recoil on protons from highly mobile water molecules at low temperature (5 K), along with a significant shift of water librational band to lower energies and the O–H stretching modes to high energies, indicate that the hydrogen bonds acting on these water molecules in mordenite resemble those in liquid water rather than ice.

Crystal structure↗
DOE OSTI2025

Machine Learning-Guided Identification of PET Hydrolases from Natural Diversity

The enzymatic depolymerization of poly(ethylene terephthalate) (PET) is emerging as a leading chemical recycling technology for waste polyester. As part of this endeavor, new candidate enzymes identified from natural diversity can serve as useful starting points for enzyme evolution and engineering. In this study, we improved upon HMM searches by applying an iterative machine learning strategy to identify 400 putative PET-degrading enzymes (PET hydrolases) from naturally occurring homologs. Using high-throughput (HTP) experimental techniques, we successfully expressed and purified >200 enzyme candidates and assayed them for PET hydrolysis activity as a function of pH, temperature, and substrate crystallinity. From this library, we discovered 91 previously unknown PET hydrolases, 35 of which retain activity at pH 4.5 on crystalline material, which are conditions relevant to developing more efficient commercial processes. Notably, four enzymes showed equal to or higher activity than LCC-ICCG, a benchmark PET hydrolase, at this challenging condition in our screening assay, and 11 of which have pH optima <7. Using these data, we identified regions of PETases statistically correlated to activity at lower pH. We additionally investigated the effect of condition-specific activity data on trained machine learning predictors and found a precision (putative hit rate) improvement of up to 30% compared to a Hidden Markov Model alone. Our findings show that by pointing enzyme discovery toward conditions of interest with multiple rounds of experimental and machine learning, we can discover large sets of active enzymes and explore factors associated with activity at those conditions.

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

Room-Temperature Optical Detection of 14 CO 2 below the Natural Abundance with Two-Color Cavity Ring-Down Spectroscopy

Radiocarbon’s natural production, radiative decay, and isotopic rarity make it a unique tool to probe carbonaceous systems in the life and earth sciences. However, the difficulty of current radiocarbon ( 14 C) detection methods limits scientific adoption. Here, two-color cavity ring-down spectroscopy detects 14 CO 2 in room-temperature samples with an accuracy of one-tenth the natural abundance in 3 min. The intracavity pump–probe measurement uses two cavity-enhanced lasers to cancel out cavity ring-down rate fluctuations and strong one-photon absorption interference (>10 000 1/s) from hot-band transitions of CO 2 isotopologues. Selective, room-temperature detection of small 14 CO 2 absorption signals (<1 1/s) reduces the technical and operational burdens for cavity-enhanced measurements of radiocarbon, which can benefit a wide range of applications like biomedical research and field-detection of combusted fossil fuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗