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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Substrate, temperature, and geographical patterns among nearly 2000 natural yeast isolates

Yeasts have broad importance as industrially and clinically relevant microbes and as powerful models for fundamental research, but we are only beginning to understand the roles yeasts play in natural ecosystems. Yeast ecology is often more difficult to study compared to other, more abundant microbes, but growing collections of natural yeast isolates are beginning to shed light on fundamental ecological questions. In this work, we used environmental sampling and isolation to assemble a dataset of 1962 isolates collected from throughout the contiguous United States of America (USA) and Alaska, which were then used to uncover geographic patterns, along with substrate and temperature associations among yeast taxa. We found some taxa, including the common yeasts Torulaspora delbrueckii and Saccharomyces paradoxus, to be repeatedly isolated from multiple sampled regions of the USA, and we classify these as broadly distributed cosmopolitan yeasts. A number of yeast taxon-substrate associations were identified, some of which were novel and some of which support previously reported associations. Further, we found a strong effect of isolation temperature on the phyla of yeasts recovered, as well as for many species. We speculate that substrate and isolation temperature associations reflect the ecological diversity of and niche partitioning by yeast taxa.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Precision Higgs couplings in neutral naturalness models: an effective field theory approach

The Higgs sector in neutral naturalness models provides a portal to the hidden sectors, and thus measurements of Higgs couplings at current and future colliders play a central role in constraining the parameter space of the model. We investigate a class of neutral naturalness models, in which the Higgs boson is a pseudo-Goldstone boson from the universal SO(N)/SO(N - 1) coset structure. Integrating out the radial mode from the spontaneous global symmetry breaking, we obtain various dimension-six operators in the Standard Model effective field theory, and calculate the low energy Higgs effective potential with radiative corrections included. We perform a χ 2 fit to the Higgs coupling precision measurements at current and future colliders and show that the new physics scale could be explored up to 2.3 (2.4) TeV without (with) the Higgs invisible decay channels at future Higgs factories. The limits are comparable to the indirect constraints obtained via electroweak precision measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

The cosmological moduli problem and naturalness

Nowadays, the cosmological moduli problem (CMP) comes in three parts: 1. potential violation of Big-Bang nucleosynthesis (BBN) constraints from late decaying moduli fields, 2. the moduli-induced gravitino problem wherein gravitinos are overproduced and their decays violate BBN or dark matter overproduction bounds and 3. the moduli-induced lightest SUSY particle (LSP) overproduction problem. Also, the CMP may be regarded as either a problem or else a solution to scenarios with dark matter over- or under-production. We examine the cosmological moduli problem and its connection to electroweak naturalness. We calculate the various two-body decay widths of a light modulus field into MSSM particles and gravitinos within general supersymmetric models. We include both phase space and mixing effects. We examine cases without and with helicity suppression of modulus decays to gravitinos (cases 1 & 2) and/or gauginos (cases A & B). For case B1, we evaluate regions of gravitino mass m 3/2 vs. modulus mass mΦ parameter space constrained by BBN, by overproduction of gravitinos and by overproduction of neutralino dark matter, along with connections to naturalness. For this case, essentially all of parameter space is excluded unless mΦ ≳ 2.5 × 10 3 TeV with mΦ< 2m 3/2 For a potentially most propitious case B2 with Φ decay to Higgs and matter turned off, then modulus branching fractions to SUSY and to gravitinos become highly suppressed at large m Φ . But since the modulus number density increases faster than the branching fractions decrease, there is still gross overproduction of neutralino dark matter. We also show that in this scenario the thermally produced gravitino problem is fixed by huge entropy dilution, but non-thermal gravitino production from moduli decay remains a huge problem unless it is kinematically suppressed with m Φ < 2m 3/2 . In a pedagogical appendix, we present detailed calculations of modulus field two-body decay widths.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Towards natural and realistic E 7 GUTs in F-theory

We consider phenomenological aspects of a natural class of Standard Model-like supersymmetric F-theory vacua realized through flux breaking of rigid E 7 gauge factors. Three generations of Standard Model matter are realized in many of these vacua. We further find that many other Standard Model-like features are naturally compatible with these constructions. For example, dimension-4 and 5 terms associated with proton decay are ubiquitously suppressed. Many of these features are due to the group theoretical structure of E 7 and associated F-theory geometry. In particular, a set of approximate global symmetries descends from the E 7 group, leading to exponential suppression of undesired couplings.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Spontaneous CP violation and horizontal symmetry in the MSSM: toward lepton flavor naturalness

We study the contributions of supersymmetric models with a U(1) horizontal symmetry and only spontaneous CP breaking to various lepton flavor observables, such as μ → eγ and the electron electric dipole moment. We show that both a horizontal symmetry and a lack of explicit CP violation can alleviate the existing bounds from such observables. The undetermined \( \mathcal{O} \) (1) coefficients in such mass matrix models muddle the interpretation of the bounds from various flavor observables. To overcome this, we define a new fine-tuning measure for different observables in such setups. This allows us to study how naturally the observed IR flavor observables can emerge from a given mass matrix model. We use our flavor-naturalness measure in study of our supersymmetric models and quantify the degree of fine tuning required by the bounds from various lepton flavor observables at each mass scale of sleptons, neutralinos, and charginos.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Non-intrusive reduced order modeling of natural convection in porous media using convolutional autoencoders: Comparison with linear subspace techniques

Natural convection in porous media is a highly nonlinear multiphysical problem relevant to many engineering applications (e.g., the process of CO 2 sequestration). Here, we extend and present a non-intrusive reduced order model of natural convection in porous media employing deep convolutional autoencoders for the compression and reconstruction and either radial basis function (RBF) interpolation or artificial neural networks (ANNs) for mapping parameters of partial differential equations (PDEs) on the corresponding nonlinear manifolds. To benchmark our approach, we also describe linear compression and reconstruction processes relying on proper orthogonal decomposition (POD) and ANNs. Further, we present comprehensive comparisons among different models through three benchmark problems. The reduced order models, linear and nonlinear approaches, are much faster than the finite element model, obtaining a maximum speed-up of 7 × 10 6 because our framework is not bound by the Courant–Friedrichs–Lewy condition; hence, it could deliver quantities of interest at any given time contrary to the finite element model. Our model’s accuracy still lies within a relative error of 7% in the worst-case scenario. We illustrate that, in specific settings, the nonlinear approach outperforms its linear counterpart and vice versa. We hypothesize that a visual comparison between principal component analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE) could indicate which method will perform better prior to employing any specific compression strategy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Improved sampling technique to collect natural gas from hydrate-bearing pressure cores

High quality gas compositional data are an important factor in interpreting the genetic source of natural gas hosted in hydrate-bearing sediments and other subsurface systems. In order to accurately characterize the composition of gas samples degassed from hydrate-bearing pressure cores, one must use a reproducible sampling technique that minimizes artifacts of the sampling process. Herein, we review sediment core degassing techniques and compare data obtained from a commonly used degassing approach, which we term the standard quantitative degassing (SQD) technique, to our newly developed modified quantitative degassing (MQD) method designed to minimize atmospheric contamination and gas-water interactions. The SQD method allows sample gas to interact with water in a bubbling chamber, which we hypothesize could alter the gas composition following mixing with water or dissolved gases in the bubbling chamber. Whereas, the MQD method allows for the collection of sample gas prior to the bubbling chamber. To compare the SQD and MQD methods, we performed a side-by-side comparison of noble (He, Ne, Ar, Kr, and Xe), major (H 2 , N 2 , O 2 , and CO 2 ), and hydrocarbon (CH 4 , C 2 H 6 , C 3 H 8 , i-C 4 H 10 , C 4 H 10 , i-C 5 H 12 , C 5 H 12 ) gas concentrations and select isotopic compositions obtained using both sample collection techniques. Gas samples were collected from hydrate-bearing pressure cores recovered and maintained under hydrate stable conditions from the northern Gulf of Mexico during the UT-GOM 2 -1 Expedition. The MQD method displayed significantly lower concentrations of atmospheric gases, higher proportions of hydrocarbon gases, lower ratios of C 1 /C 2 + , and heavier stable carbon and hydrogen isotopes of methane than the SQD method. These results demonstrate that the MQD method reduced air contamination and minimized alteration of the hydrocarbon gases. Finally, we conclude this method may be important for future work that seeks to determine the composition of natural gas from pressure cores using quantitative degassing experiments, especially those seeking to measure major (e.g., N 2 ) and noble gases.

58 GEOSCIENCES↗
DOE OSTI2026

Measurement of gamma-induced reactions between 10 and 19 MeV on natural zinc with potential application to 67 Cu production

As part of a broader campaign to understand gamma-induced charged particle emission with multiple materials, the cross sections of the (γ, p), and (γ, α) reactions on a natural zinc target were measured. Here, these cross sections were measured experimentally using a kinematically-complete, event-by-event methodology, using monoenergetic gamma ray beams from the High Intensity Gamma Source (HIγS) facility, ranging from 10 to 19 MeV, to bombard a natural metallic zinc target in vacuum. The measured cross sections are compared with theoretical predictions using the statistical model approach, which is important for the use of such models in real-world applications such as the production of the 67 Cu theranostic via the 68 Zn(γ, p) reaction.

Gamma-induced reactions↗
DOE OSTI2025

Biphasic solvents for post-combustion CO 2 capture from natural gas flue Gas

Fossil fuel fired power plants are generally expected to remain one of the most significant global sources of electricity for decades to come. Consequently, carbon management technologies are needed to reduce or eliminate ongoing emissions from these sources. Amongst the many techniques for carbon capture, aqueous amine-based absorbents (monoethanolamine, MEA, in particular) are, presently, considered the leading technology for post-combustion CO 2 point-source capture. These technologies are nevertheless limited by their high capital and regeneration energy costs. Biphasic solvents have been identified as an attractive alternative to traditional MEA based absorbents due to their potential energy savings. Thus far, however, the research on biphasic solvents has largely focused on their performance in coal flue gas while more dilute natural gas flue gas applications have received relatively little attention. Here, this work examines the performances of two novel biphasic solvent blends, diethylenetriamine (DETA) and triethylenetetramine (TETA), in CO 2 capture from a natural gas flue gas simulant. Across several regeneration tests, both solvents achieved considerable energy savings over the benchmark MEA solution. Specifically, the energy consumption per mol CO 2 recovered for the DETA-based and TETA-based solvents was 46 % and 35 % less than that of the benchmark MEA solution, respectively. Molecular dynamics simulations were also performed to gain a deeper understanding of the phase separation phenomena that occur as a consequence of CO 2 absorption. These simulations indicated that phase change was driven by the strong interaction between the absorption products and water, while the degree of separation depended on the CO 2 loading.

Biphasic solvents↗
DOE OSTI2025

Efficient Synthetic Natural Gas Production from Direct Air Capture Using Titania-Based Dual Function Materials

Converting atmospheric CO2 into methane offers a compelling pathway to store intermittent renewable electricity and enhance energy security using existing natural gas infrastructure. However, current CO2 utilization approaches remain energy- and capital-intensive, largely due to the need for separate capture, purification, and conversion steps. Integrating CO2 capture with catalytic methanation represents a transformative strategy for process intensification on both the unit operation and molecular levels. We report a series of Ru-Na/TiO2 dual function materials (DFMs) for a reactive carbon capture (RCC) process consisting of simulated direct air capture and subsequent CO2 methanation (DACM). Superior methane desorption purity was observed on TiO2-based DFMs (>94 %) relative to state-of-the-art Al2O3-supported DFMs (77 %). Modifying the process to begin CO2 adsorption immediately following the methanation stage, rather than beginning adsorption near ambient temperature, resulted in >97 % methane desorption purity, suitable for injection into the natural gas pipeline without additional CO2 separation steps.

organic↗
DOE OSTI2026

Improving anaerobic digestion of sewage sludge to renewable natural gas by the Advanced Pretreatment & Anaerobic Digestion technology (APAD): Pilot testing

Conventional anaerobic digestion (AD) of sewage sludge in wastewater treatment facilities suffers from low carbon conversion efficiency (CCE = 40%) and requires costly CO2 removal for injection of the produced CH4 into the natural gas grid. To address these limitations, we developed the Advanced Pretreatment and Anaerobic Digestion (APAD) process. This integrates Advanced Wet Oxidation & Steam Explosion (AWOEx) pretreatment of residual sludge after conventional AD, followed by biogas upgradation using a novel methanogenic strain, Methanothermobacter wolfeii BSEL, converting CO2 with H2 into CH4 or RNG (renewable natural gas). Pilot-scale results demonstrated that AWOEx pretreatment achieved a CCE of 62% for the residual sludge, 68% higher than the conventional AD process. The CH4 production was further increased by 79%. Subsequent biogas upgrading in a trickling bed reactor with H2 further enhanced total methane output by 100% and resulted in a final CO2 concentration of =3%. The integrated APAD process achieved a remarkable overall CCE of 83%, resulting in a 200% increase in RNG output when compared to conventional AD. Techno-economic analysis revealed that AWOEx pretreatment alone reduced sludge treatment costs from $494 to $253 per ton of dry solids. The complete APAD process incurred a higher cost of treatment of $530 per ton, driven by prices for bottled H2. The process did, however, show gains in energy recovery and decarbonization. Renewable H2, which may reduce in price in the near future, can positively improve the economics of biogas upgrading for the APAD process.

Life Cycle Assessment (LCA)↗
DOE OSTI2021

Efficiency of natural pozzolans, ground glasses and coal bottom ashes in mitigating sulfate attack and alkali-silica reaction

The use of pozzolans to partially replace Portland cement in concrete has generally demonstrated beneficial impacts on the durability characteristics of concrete for decades. In this paper a diverse range of pozzolans including natural pozzolans, ground glasses and industrial by-products such as coal ash (fly ash and bottom ash) and silica fume were investigated for their synergistic potential in binary or ternary blends with Portland cement in improving resistance to chemical sulfate attack and alkali-silica reaction (ASR). It is generally considered that pozzolans improve most of the durability issues encountered in concrete, including reducing the risk of sulfate attack or ASR. But this is not always the case. For example, it was found that ground glasses were very efficient in improving sulfate resistance, but their ability to mitigate expansion due to ASR was dictated by the equivalent alkalis content (Na{sub 2}O{sub e}) of the glass and high-alkali soda glass was generally not effective in this role. On the other hand, metakaolin, a highly reactive pozzolan, was highly effective in reducing ASR expansion, but may actually increase the damage due to sulfate attack when used at moderate replacement levels. Most pozzolans, such as low-CaO coal fly ash and ground coal bottom ash, silica fume, and pumice, were effective in controlling expansion due to both ASR and sulfate attack. The results demonstrated that the extent of the positive impact of using natural pozzolans on both properties was variable. The pozzolanic reactivity of materials alone was an unreliable indicator to assess the ability of the pozzolan to suppress expansion due to sulfate attack or ASR.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Optimization under uncertainty of a hybrid waste tire and natural gas feedstock flexible polygeneration system using a decomposition algorithm

Market uncertainties motivate the development of flexible polygeneration systems that are able to adjust operating conditions to favor production of the most profitable product portfolio. However, this operational flexibility comes at the cost of higher capital expenditure. A scenario-based two-stage stochastic nonconvex Mixed-Integer Nonlinear Programming (MINLP) approach lends itself naturally to optimizing these trade-offs. This work studies the optimal design and operation under uncertainty of a hybrid feedstock flexible polygeneration system producing electricity, methanol, dimethyl ether, olefins or liquefied (synthetic) natural gas. A recently developed C++ based software framework (named GOSSIP) is used for modeling the optimization problem as well as its efficient solution using the Nonconvex Generalized Benders Decomposition (NGBD) algorithm. Two different cases are studied: The first uses estimates of the means and variances of the uncertain parameters from historical data, whereas the second assesses the impact of increased uncertain parameter volatility. The value of implementing flexible designs characterized by the value of the stochastic solution (VSS) is in the range of 260–405 M$ for a scale of approximately 893 MW of thermal input. Increased price volatility around the same mean results in higher expected net present value and VSS as operational flexibility allows for asymmetric exploitation of price peaks.

42 ENGINEERING↗
DOE OSTI2022

Context matters: Natural tree mortality can lead to neighbor growth release or suppression

Where competition suppresses tree growth, mortality of adjacent trees can release the surviving individuals, leading to a growth increase. However, primary forests are complicated systems, where trees interact in both competitive and facilitative ways mediated by their size, species, and the broad ecological context in which they grow. Thus, the magnitude and even direction of growth responses to the mortality of nearby trees may vary, which has implications for our understanding of community- and ecosystem-level dynamics following mortality events. Unfortunately, although many studies focus on the impacts of light availability and general crowding on tree growth, we know relatively little about the effects of naturally occurring mortality events on the growth of neighboring trees. To address this issue, we used 40 years of data from 15 permanent forest-monitoring plots in Mt Rainier old-growth forests, comparing observed to expected radial growth of individual trees following the death of their nearest neighbor. Although we found evidence of a general growth-release response, this was not universal among all trees, with small trees in particular exhibiting growth suppression (rather than release) following neighboring tree mortality. In addition to small size, growth-suppression was more likely if the dead neighbor was the same species, consistent with facilitative effects as mediated through belowground networks. At the stand level, the average growth release after nearest neighbor mortality was greatest in low-density stands with large trees, with elevation and community composition also playing a role. Decades more monitoring could reveal how long growth release (or suppression) is sustained by individual trees following neighboring mortality events, as well as potential response lags and the role of species identity in determining whether interactions with neighbors are competitive or facilitative. Nonetheless, our results suggest that although mature trees have competitive effects on their larger neighbors, they also have an important role in supporting the ingrowth of small trees. More broadly, we demonstrate that the nature of interactions between individual neighboring trees is highly context dependent.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Clinical Natural Language Processing for Radiation Oncology: A Review and Practical Primer

Natural language processing (NLP), which aims to convert human language into expressions that can be analyzed by computers, is one of the most rapidly developing and widely used technologies in the field of artificial intelligence. Natural language processing algorithms convert unstructured free text data into structured data that can be extracted and analyzed at scale. In medicine, this unlocking of the rich, expressive data within clinical free text in electronic medical records will help untap the full potential of big data for research and clinical purposes. Recent major NLP algorithmic advances have significantly improved the performance of these algorithms, leading to a surge in academic and industry interest in developing tools to automate information extraction and phenotyping from clinical texts. Thus, these technologies are poised to transform medical research and alter clinical practices in the future. Radiation oncology stands to benefit from NLP algorithms if they are appropriately developed and deployed, as they may enable advances such as automated inclusion of radiation therapy details into cancer registries, discovery of novel insights about cancer care, and improved patient data curation and presentation at the point of care. However, challenges remain before the full value of NLP is realized, such as the plethora of jargon specific to radiation oncology, nonstandard nomenclature, a lack of publicly available labeled data for model development, and interoperability limitations between radiation oncology data silos. Successful development and implementation of high quality and high value NLP models for radiation oncology will require close collaboration between computer scientists and the radiation oncology community. Here, we present a primer on artificial intelligence algorithms in general and NLP algorithms in particular; provide guidance on how to assess the performance of such algorithms; review prior research on NLP algorithms for oncology; and describe future avenues for NLP in radiation oncology research and clinics.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

How does urbanization affect CO 2 emissions of central heating systems in China? An assessment of natural gas transition policy based on nighttime light data

Understanding the different impacts of urbanization on sectorial carbon dioxide (CO 2 ) emissions at different spatial scales is of great importance for the evaluation of energy transition policies and reduction of environmental inequality. However, how urbanization affects the CO 2 emissions of central heating systems at high spatial resolution in China has not been fully studied before. Based on satellite-observed NPP-VIIRS nighttime light (NTL) data, we develop a 5 km x 5 km annual CO 2 emission inventory for coal boilers, thermal power plants (TPPs), and natural gas boilers in China's central heating systems for the period 2012-2017 by using the geographical and temporally weighted regression (GTWR) model. It is observed that nonurban areas generated 2-4 times the CO 2 emissions of coal boilers in urban areas. The largest increments of CO 2 emissions of gas boilers are observed in urban areas of the eastern (6.80 times) and central regions (2.86 times) in 2013-2014, due to the clean heating policy in the "2 + 26" cities in China. The effects of urbanization on CO 2 emissions from natural gas boilers are approximately 2-3 times those of coal boilers, and the differences are largest in western cities with only minor differences in northeastern cities. Overall, our results will aid in designing low-carbon development goals and provide micro-level information on central heating facilities in urbanized and less developed regions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Investigation of oxygen evolution reaction with 316 and 304 stainless-steel mesh electrodes in natural seawater electrolysis

Here, two commercially available stainless steel mesh substrates (316 SS and 304 SS) were evaluated as electrodes for oxygen evolution reaction (OER) in natural seawater electrolysis. The results show the 304 SS is less stable against corrosion under neutral (pH of 8.5) and low alkaline (0.1 M NaOH, pH of 12.8) seawater electrolytes because of the direct metal dissolution and chlorine evolution reaction (CER), and the 316 SS is superior to 304 SS in terms of electrocatalytic activity and resistance to corrosion under the same media. The performance of 304 SS is comparable to 316 SS under the high alkaline (1 M NaOH, pH of 13.7) seawater electrolyte, where the CER and metal dissolution are suppressed by OER. The overpotential for 304 and 316 SS is around 430 mV at 10 mA cm -2 , and the Tafel slopes are below 50 mV dec -1 under the high alkaline (1 M NaOH) seawater electrolyte, showing promising performance. The poor resistance to corrosion of 304 SS is attributed to the low Mo content, and it is supposed that the stability of both 304 and 316 SS can be improved further with the addition of Mo content. This work expands on promising substrates for natural seawater electrolysis, with cost and performance advantages.

Stainless-steel mesh↗
DOE OSTI2025

Quantifying fission gas adsorption onto natural clinoptilolite in the presence of environmental air and water

Adsorption of noble gas fission products onto naturally occurring minerals is of interest for its potential to retain or retard emissions from nuclear fuel reprocessing operations or underground nuclear explosions. However, experimental studies of trace noble gas adsorption in the presence of air and water have largely focused on synthetic materials, such as activated carbon or metal-organic frameworks. Here, in this study, adsorption of Kr and Xe onto the naturally occurring zeolitic mineral clinoptilolite is studied in the presence of nitrogen and water. By varying the composition of the gas phase and monitoring the change in the combined adsorbate mass, the adsorbed concentration of noble gas is calculated gravimetrically. For dry clinoptilolite, the concentration of adsorbed Kr and Xe is linearly correlated with noble gas pressure and Henry's Law appears satisfactory, despite the presence of nitrogen at atmospheric pressures. However, the presence of water significantly reduces the adsorbed concentration of both Kr and Xe, which is typical in nanoporous sorbents. Here, an empirical bivariate model is presented, combining the Henry's Law adsorption model for a dry adsorbent with the exponential reduction in the presence of water, as reported by Lungu and Underhill in 1999. This model provides a means to estimate the adsorbate concentration at the trace partial pressures and higher water contents relevant to field-scale modeling of fission gas transport through the vadose zone.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗