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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Extraordinary phylogenetic diversity and metabolic versatility in aquifer sediment

Microorganisms in the subsurface represent a substantial but poorly understood component of the Earth’s biosphere. Subsurface environments are complex and difficult to characterize; thus, their microbiota have remained as a ‘dark matter’ of the carbon and other biogeochemical cycles. Here we deeply sequence two sediment-hosted microbial communities from an aquifer adjacent to the Colorado River, CO, USA. No single organism represents more than ~1% of either community. Remarkably, many bacteria and archaea in these communities are novel at the phylum level or belong to phyla lacking a sequenced representative. The dominant organism in deeper sediment, RBG-1, is a member of a new phylum. On the basis of its reconstructed complete genome, RBG-1 is metabolically versatile. Its wide respiration-based repertoire may enable it to respond to the fluctuating redox environment close to the water table. We document extraordinary microbial novelty and the importance of previously unknown lineages in sediment biogeochemical transformations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Cooking methods and kitchen ventilation availability, usage, perceived performance and potential in Canadian homes

Cooking is a substantial contributor to air pollutant exposures in many residences. Effective use of kitchen ventilation can mitigate exposure; however, information on its availability, usage, and potential to increase its use across the population has been limited. This study aimed to obtain nationally representative information on cooking methods, kitchen ventilation availability and usage, and the potential for education to increase effective usage. An online survey was sent to a representative sample of Canadian homes to collect data on cooking methods, the presence and use of mechanical kitchen ventilation devices, perceived device performance, and willingness to implement mitigation strategies. Responses were weighted to match key demographic factors and analyzed using non-parametric statistics. Among the 4500 respondents, 90% had mechanical ventilation devices over the cooktop (66% of which were vented to the outside), and 30% reported regularly using their devices. Devices were used most often for deep-frying, followed by stir-frying, sautéing or pan-frying, indoor grilling, boiling or steaming. Almost half reported rarely or never using their ventilation devices during baking or oven self-cleaning. Only 10% were fully satisfied with their devices. More frequent use was associated with the device being vented to the outdoors, having more than two speed settings, quiet operation if only one speed, covering over half of the cooktop, and higher perceived effectiveness. After being informed of the benefits of kitchen ventilation, 64% indicated they would consider using their devices more often, preferentially using back burners with ventilation, and/or using higher ventilation device settings when needed. This study provides population-representative data on the most used cooking methods, kitchen ventilation availability and usage, and influencing factors in Canadian homes. Such data are needed for exposure assessments and evaluating the potential to mitigate cooking-related pollutant exposures via more effective use of kitchen ventilation. The data can be reasonably extrapolated to the United States, given the similarities in residential construction practices and cultural norms between the two countries.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Climate and hydraulic traits interact to set thresholds for liana viability

Lianas, or woody vines, and trees dominate the canopy of tropical forests and comprise the majority of tropical aboveground carbon storage. These growth forms respond differently to contemporary variation in climate and resource availability, but their responses to future climate change are poorly understood because there are very few predictive ecosystem models representing lianas. We compile a database of liana functional traits (846 species) and use it to parameterize a mechanistic model of liana-tree competition. The substantial difference between liana and tree hydraulic conductivity represents a critical source of inter-growth form variation. Here, we show that lianas are many times more sensitive to drying atmospheric conditions than trees as a result of this trait difference. Further, we use our competition model and projections of tropical hydroclimate based on Representative Concentration Pathway 4.5 to show that lianas are more susceptible to reaching a hydraulic threshold for viability by 2100.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Super-resolving microscopy images of Li-ion electrodes for fine-feature quantification using generative adversarial networks

Abstract For a deeper understanding of the functional behavior of energy materials, it is necessary to investigate their microstructure, e.g., via imaging techniques like scanning electron microscopy (SEM). However, active materials are often heterogeneous, necessitating quantification of features over large volumes to achieve representativity which often requires reduced resolution for large fields of view. Cracks within Li-ion electrode particles are an example of fine features, representative quantification of which requires large volumes of tens of particles. To overcome the trade-off between the imaged volume of the material and the resolution achieved, we deploy generative adversarial networks (GAN), namely SRGANs, to super-resolve SEM images of cracked cathode materials. A quantitative analysis indicates that SRGANs outperform various other networks for crack detection within aged cathode particles. This makes GANs viable for performing super-resolution on microscopy images for mitigating the trade-off between resolution and field of view, thus enabling representative quantification of fine features.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Trajectory sampling and finite-size effects in first-principles stopping power calculations

Abstract Real-time time-dependent density functional theory (TDDFT) is presently the most accurate available method for computing electronic stopping powers from first principles. However, obtaining application-relevant results often involves either costly averages over multiple calculations or ad hoc selection of a representative ion trajectory. We consider a broadly applicable, quantitative metric for evaluating and optimizing trajectories in this context. This methodology enables rigorous analysis of the failure modes of various common trajectory choices in crystalline materials. Although randomly selecting trajectories is common practice in stopping power calculations in solids, we show that nearly 30% of random trajectories in an FCC aluminum crystal will not representatively sample the material over the time and length scales feasibly simulated with TDDFT, and unrepresentative choices incur errors of up to 60%. We also show that finite-size effects depend on ion trajectory via “ouroboros” effects beyond the prevailing plasmon-based interpretation, and we propose a cost-reducing scheme to obtain converged results even when expensive core-electron contributions preclude large supercells. This work helps to mitigate poorly controlled approximations in first-principles stopping power calculations, allowing 1–2 order of magnitude cost reductions for obtaining representatively averaged and converged results.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Large loss of CO 2 in winter observed across the northern permafrost region

Recent warming in the Arctic, which has been amplified during the winter, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO 2 ) 4 . However, the amount of CO 2 released in winter is not known and has not been well represented by ecosystem models or empirically based estimates. In this paper, we synthesize regional in situ observations of CO 2 flux from Arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1,662 TgC per year from the permafrost region during the winter season (October–April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (-1,032 TgC per year). Extending model predictions to warmer conditions up to 2100 indicates that winter CO 2 emissions will increase 17% under a moderate mitigation scenario—Representative Concentration Pathway 4.5—and 41% under business-as-usual emissions scenario—Representative Concentration Pathway 8.5. Finally, our results provide a baseline for winter CO 2 emissions from northern terrestrial regions and indicate that enhanced soil CO 2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Perovskite- and Dye-Sensitized Solar-Cell Device Databases Auto-generated Using ChemDataExtractor

The number of scientific publications reporting cutting-edge third-generation photovoltaic devices is increasing rapidly, owing to the pressing need to develop renewable-energy technologies that address the climate-change crisis. Consequently, the field could benefit from a central repository where photovoltaic-performance metrics, such as the power-conversion efficiency (η) are recorded. We present two automatically generated databases that contain photovoltaic properties and device material data for dye-sensitized solar cells (DSCs) and perovskite solar cells (PSCs), totalling 660,881 data entries representing 57,678 photovoltaic devices. The databases were generated by applying the text-mining toolkit ChemDataExtractor on a corpus of 25,720 articles. A multi-faceted evaluation, incorporating manual and automatic methods, was applied to ensure that the data contained therein were of the highest quality, with precision metrics ranging from 73.1% to 95.8%. The DSC database contains 475,045 entries representing 41,680 devices, and the PSC database contains 185,836 entries representing 15,818 devices. The databases are available in MongoDB and JSON formats, which can be queried in Python, R, Java and MATLAB for data-driven photovoltaic materials discovery.

14 SOLAR ENERGY↗
DOE OSTI2021

A data-driven approach to modeling cancer cell mechanics during microcirculatory transport

In order to understand the effect of cellular level features on the transport of circulating cancer cells in the microcirculation, there has been an increasing reliance on high-resolution in silico models. Accurate simulation of cancer cells flowing with blood cells requires resolving cellular-scale interactions in 3D, which is a significant computational undertaking warranting a cancer cell model that is both computationally efficient yet sufficiently complex to capture relevant behavior. Given that the characteristics of metastatic spread are known to depend on cancer type, it is crucial to account for mechanistic behavior representative of a specific cancer’s cells. To address this gap, in the present work we develop and validate a means by which an efficient and popular membrane model-based approach can be used to simulate deformable cancer cells and reproduce experimental data from specific cell lines. Here, cells are modeled using the immersed boundary method (IBM) within a lattice Boltzmann method (LBM) fluid solver, and the finite element method (FEM) is used to model cell membrane resistance to deformation. Through detailed comparisons with experiments, we (i) validate this model to represent cancer cells undergoing large deformation, (ii) outline a systematic approach to parameterize different cell lines to optimally fit experimental data over a range of deformations, and (iii) provide new insight into nucleated vs. non-nucleated cell models and their ability to match experiments. While many works have used the membrane-model based method employed here to model generic cancer cells, no quantitative comparisons with experiments exist in the literature for specific cell lines undergoing large deformation. Here, we describe a phenomenological, data-driven approach that can not only yield good agreement for large deformations, but explicitly detail how it can be used to represent different cancer cell lines. This model is readily incorporated into cell-resolved hemodynamic transport simulations, and thus offers significant potential to complement experiments towards providing new insights into various aspects of cancer progression.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

A Model of Cyclic Transcriptomic Behavior in Cyanobacterium Cyanothece sp. ATCC 51142

Systems biology attempts to reconcile large amounts of disparate data with existing knowledge to provide models of functioning biological systems. Useful and predictive models aim to summarize complex and dynamic processes and represent the relationships between these processes. The cyanobacterial Cyanothece species Strain sp. ATCC 51142 is an excellent candidate for such systems studies because: (i) it displays tight functional regulation as it must separate the opposing processes of oxygen-generating photosynthesis and oxygen-sensitive nitrogen fixation temporally in the same cell, ; (ii) it has robust cyclic patterns at the genetic, protein and metabolomic levels, ; and (iii) and it has potential applications for bioenergy and carbon sequestration, and thus a predictive model of its function is of practical use. We have represented the transcriptomic data from Cyanothece 51142 under diurnal light/dark cycles as a high-level functional abstraction and describe development of a predictive in silico model of diurnal and circadian behavior in terms of regulatory and metabolic processes in Cyanothece 51142. Our model provides a way to integrate disparate data types into a framework that can be used to explain behavior, generate high-quality predictions for validation, and to suggest future experiments. We show that incorporating network topology into the model improves performance in terms of our ability to explain the behavior of the system under new conditions. The model presented robustly describes transcriptomic behavior of Cyanothece 51142 under different cyclic and non-cyclic growth conditions robustly, and represents a significant advance in the understanding of gene regulation in this important organism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Magnetic iron oxide nanoparticles for the collection and direct measurement of adsorbed alpha-emitting radionuclides from environmental waters by liquid scintillation analysis

Radioactive contamination in the environment, be it from accidental or intentional release, can create an urgent need to assess water and food supplies, the environment, and monitor human health. Alpha-emitting radionuclides represent the most ionizing, and therefore the most damaging, form of radiation when internalized. Additionally, because of its ease of energy attenuation in solids or liquids, alpha emissions cannot be reliably monitored using non-destructive means. In the event of such an emergency, rapid and efficient methods will be needed to screen scores of samples (food, water, and human excreta) within a short time window. Unfortunately, the assay of alpha-emitting radionuclides using traditional radioanalytical methods is typically labor intensive and time consuming. The creation of analytical counting sources typically requires a series of chemical treatment steps to achieve well performing counting sources. In an effort to devise radioanalytical methods that are fast, require little labor, and minimize the use of toxic or corrosive agents, researchers at PNNL have evaluated magnetite (Fe3O4) nanoparticles as extracting agents for alpha-emitting radionuclides from chemically unmodified aqueous systems. It is demonstrated that bare magnetic nanoparticles exhibit high affinity for representative α-emitting radionuclides (241Am and 210Po) from representative aqueous matrices: river and ground water. Furthermore, use of the magnetic properties of these materials to concentrate the sorbed analyte from the bulk aqueous solution has been demonstrated. The nanoparticle concentrate can be either directly dispensed into scintillation cocktail, or first dissolved and then added to scintillation cocktail as a solution for alpha emission assay by liquid scintillation analysis. Despite the extreme quench caused by the metal oxide suspensions, the authors have demonstrated that quench correction features available on modern liquid scintillation analyzers can be employed to assure that quench-induced analytical biases can be avoided.

actinide↗
DOE OSTI2018

Thermochemical wastewater valorization via enhanced microbial toxicity tolerance

Thermochemical (TC) biomass conversion processes such as pyrolysis and liquefaction generate considerable amounts of wastewater, which often contains highly toxic compounds that are incredibly challenging to convert via standard wastewater treatment approaches such as anaerobic digestion. These streams represent a cost for TC biorefineries, and a potential valorization opportunity, if effective conversion methods are developed. The primary challenge hindering microbial conversion of TC wastewater is toxicity. In this study, we employ a robust bacterium, Pseudomonas putida , with TC wastewater streams to demonstrate that aldehydes are the most inhibitory compounds in these streams. Proteomics, transcriptomics, and fluorescence-based immunoassays of P. putida grown in a representative wastewater stream indicate that stress results from protein damage, which we hypothesize is a primary toxicity mechanism. Constitutive overexpression of the chaperone genes, groEL, groES, and clpB, in a genome-reduced P. putida strain improves the tolerance towards multiple TC wastewater samples up to 200-fold. Moreover, the concentration ranges of TC wastewater are industrially relevant for further bioprocess development for all wastewater streams examined here, representing different TC process configurations. Furthermore, we demonstrate proof-of-concept polyhydroxyalkanoate production from the usable carbon in an exemplary TC wastewater stream. Altogether, this study demonstrates that protein quality control machinery and repair mechanisms can enable substantial gains in microbial tolerance to highly toxic substrates, including heterogeneous waste streams. When coupled to other metabolic engineering advances such as expanded substrate utilization and enhanced product accumulation, this study generally enables new strategies for biological conversion of highly-toxic, organic-rich wastewater via engineered aerobic monocultures or designer consortia.

09 BIOMASS FUELS↗
DOE OSTI2022

Influence of intermolecular interactions on the infrared complex indices of refraction for binary liquid mixtures

This paper investigates the accuracy of deriving the composite optical constants of binary mixtures from only the complex indices of refraction of the neat materials. These optical constants enable the reflectance spectra of the binary mixtures to be modeled for multiple scenarios (e.g., different substrates, thicknesses, volume ratios), which is important for contact and standoff chemical detection. Using volume fractions, each mixture's complex index of refraction was approximated via three different mixing rules. To explore the impact of intermolecular interactions, these predictions are tested by experimental measurements for two representative sets of binary mixtures: (1) tributyl phosphate combined with n-dodecane, a non-polar medium, to represent mixtures which primarily interact via dispersion forces and (2) tributyl phosphate and 1-butanol to represent mixtures with polar functional groups that can also interact via dipole–dipole interactions, including hydrogen bonding. The residuals and the root-mean-square error between the experimental and calculated index values are computed and demonstrate that for miscible liquids in which the average geometry of the cross-interactions can be considered isotropic (e.g., dispersion), the refractive indices of the mixtures can be modeled using composite n and k values derived from volume fractions of the neat liquids. Conversely, in spectral regions where the geometry of the cross-interactions is more restricted and anisotropic (e.g., hydrogen bonding), the calculated n and k values vary from the measured values. The impact of these interactions on the reflectance spectra are then compared by modeling a thin film of the binary mixtures on an aluminum substrate using both the measured and the mathematically computed indices of refraction.

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

Generation and Study of Am(IV) by Temperature-Controlled Electron Pulse Radiolysis

Used nuclear fuel (UNF) separation techniques that strive to separate radiotoxic americium (Am) from trivalent lanthanide fission products through oxidation state control have increased research efforts surrounding Am(V) and Am(VI). However, equivalent knowledge of the tetravalent state, Am(IV), has remained elusive, particularly in conditions more representative of UNF reprocessing, i.e., in concentrated nitric acid (HNO3). With this in mind, we have used electron pulse radiolysis to study the radiation-induced redox reaction of Am(III) with the oxidizing nitrate radical (NO3?) in 6 M HNO3: Am(III) + NO3? ? Am(IV) + NO3? . These experiments enabled us to observe the growth and decay of Am(IV) in a concentrated acidic solution for the first time. The transient Am(IV) species was found to have a lifetime of ~16 µs?sufficiently long-lived to play a critical mechanistic role in UNF reprocessing systems. Additionally, we performed the first-ever temperature-dependent kinetics study of an actinide element, elucidating unprecedented Arrhenius and Eyring activation parameters for the reaction of Am(III) with NO3?. This new knowledge provides much-needed molecular-level insights into the radiation-induced behavior of Am.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

Ambient mechanosynthesis of flexible two-dimensional covalent organic frameworks

We present the first ambient mechanosynthesis of 16 flexible covalent organic frameworks (COFs) within an hour. Notably, one representative COF exhibited a high iodine uptake capacity of ∼4.3 g g −1 from aqueous solutions and 5.97 g g −1 from vapor. Flexible two-dimensional covalent organic frameworks (2D COFs) constructed from nonplanar building blocks represent an emerging paradigm in COF design. Nevertheless, the prevailing solvothermal synthesis suffers from low time efficiency, environmental unfriendliness, and cumbersome protocols. Here, we address these challenges by developing the first ambient mechanosynthesis of a diverse library of flexible 2D COFs. Sixteen distinct triazine-cored Schiff-base COFs, including five as-yet-unreported ones, were rapidly synthesized via ball milling using 2,4,6-tris(4-aminophenoxy)-1,3,5-triazine (TPT-NH 2 ) and 2,4,6-tris(4-formylphenoxy)-1,3,5-triazine (TPT-CHO) as building blocks. Notably, the representative COF, MC-flexible-COF-1, was synthesized in as little as one hour under mechanosynthesis conditions, whereas it remained unattainable via the traditional solvothermal method, despite prolonged heating and extensive solvent screening. The highly dynamic nature of the imine linkage was unequivocally demonstrated through mechanochemical “scrambling” experiments using molecular model compounds. Furthermore, MC-flexible-COF-1 exhibited a high iodine uptake capacity of ∼4.30 g g −1 from aqueous solutions and 5.97 g g −1 from the vapor phase. This work underscores the immense potential of mechanochemistry as a powerful and sustainable tool for the rapid synthesis of advanced 2D COFs, including those inaccessible via conventional solution-based methods.

Nailwal, Yogendra↗
DOE OSTI2020

ML Track Fitting in Nuclear Physics

Charged particle tracking represents the largest consumer of CPU resources in high data volume Nuclear Physics (NP) experiments. An effort is underway to develop machine learning (ML) networks that will reduce the resources required for charged particle tracking. Tracking in NP experiments represent some unique challenges compared to high energy physics (HEP). In particular, track finding typically represents only a small fraction of the overall tracking problem in NP. This presentation will outline the differences and similarities between NP and HEP charged particle tracking and areas where ML learning may provide a benefit. The status of the specific effort taking place at Jefferson Lab will also be shown.

Britton, Thomas↗
DOE OSTI2011

Development of an alpha/beta/gamma detector for radiation monitoring

For radiation monitoring at the site of nuclear power plant accidents such as Fukushima Daiichi, radiation detectors not only for gamma photons but also for alpha and beta particles are needed because some nuclear fission products emit beta particles and gamma photons and some nuclear fuels contain plutonium that emits alpha particles. We developed a radiation detector that can simultaneously monitor alpha and beta particles and gamma photons for radiation monitoring. The detector consists of three-layered scintillators optically coupled to each other and coupled to a photomultiplier tube. The first layer, which is made of a thin plastic scintillator (decay time: 2.4 ns), detects alpha particles. The second layer, which is made of a thin Gd{sub 2}SiO{sub 5} (GSO) scintillator with 1.5 mol.% Ce (decay time: 35 ns), detects beta particles. The third layer made of a thin GSO scintillator with 0.4 mol.% Ce (decay time: 70 ns) detects gamma photons. By using pulse shape discrimination, the count rates of these layers can be separated. With individual irradiation of alpha and beta particles and gamma photons, the count rate of the first layer represented the alpha particles, the second layer represented the beta particles, and the third layer represented the gamma photons. Even with simultaneous irradiation of the alpha and beta particles and the gamma photons, these three types of radiation can be individually monitored using correction for the gamma detection efficiency of the second and third layers. Our developed alpha, beta, and gamma detector is simple and will be useful for radiation monitoring, especially at nuclear power plant accident sites or other applications where the simultaneous measurements of alpha and beta particles and gamma photons are required.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

High-energy radiation damage in zirconia: Modeling results

Zirconia is viewed as a material of exceptional resistance to amorphization by radiation damage, and consequently proposed as a candidate to immobilize nuclear waste and serve as an inert nuclear fuel matrix. Here, we perform molecular dynamics simulations of radiation damage in zirconia in the range of 0.1–0.5 MeV energies with account of electronic energy losses. We find that the lack of amorphizability co-exists with a large number of point defects and their clusters. These, importantly, are largely isolated from each other and therefore represent a dilute damage that does not result in the loss of long-range structural coherence and amorphization. We document the nature of these defects in detail, including their sizes, distribution, and morphology, and discuss practical implications of using zirconia in intense radiation environments.

36 MATERIALS SCIENCE↗