Search NASA⌕ Search

SEARCH · Search NASA

Results for “Understanding”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

PNNL DataHub NIAID Program Project: Modeling Host Responses to Understand Severe Human Virus Infections, Multi-Omic Viral Dataset Catalog Collection

The National Institute of Allergy and Infectious Diseases (NIAID) "Modeling Host Responses to Understand Severe Human Virus Infections" program project was a highly integrated and comprehensive systems biology research core, funded by the National Institute of Health (U19AI106772) from 2013-06-01 to 2018-05-31, investigating the complex host response to category A, B, and C priority pathogen infections. Resulting project deliverables include an extensive comprehensive collections of linked primary and secondary transformation viral experimental infection data. Here we provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open access to viral Omics lifecycle datasets and project metadata. Using a highly integrated and multidisciplinary approach, linked primary data and metadata supporting secondary normalization datasets, provide critical information necessary for research reproducibility and long-term preservation. Enabling on-demand data access for research community consumption and developer reuse, serves to support new mechanistic insights and discoveries into host-pathogen interactions for aiding future biohazard data preparedness efforts in emergency response to global health crises involving viral infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Toward Process-Based Quality through a Fundamental Understanding of Weld Microstructural Evolution

Here, in this overview paper, the possibility of qualifying welded components by integrating software and hardware tools that are capable of describing physical processes that occur during welding is explored. The existing and emerging tools to define geometrical boundary conditions, process parameters, heat and mass transfer, solidification, solid-state transformation, plastic deformation, distortion, residual stress, and performance of welded components are reviewed. Existing challenges relevant to the fundamental understanding of complex alloying, processing environment, and transients in energy deposition are discussed with reference to microstructure evolution. Finally, approaches to address these challenges were articulated with published case studies relevant to welding and additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Current understanding of the correlation of lignin structure with biomass recalcitrance

Lignin, a complex aromatic polymer in terrestrial plants, contributes significantly to biomass recalcitrance to microbial and/or enzymatic deconstruction. To reduce biomass recalcitrance, substantial endeavors have been exerted on pretreatment and lignin engineering in the past few decades. Lignin removal and/or alteration of lignin structure have been shown to result in reduced biomass recalcitrance with improved cell wall digestibility. While high lignin content is usually a barrier to a cost-efficient application of bioresources to biofuels, the direct correlation of lignin structure and its concomitant properties with biomass remains unclear due to the complexity of cell wall and lignin structure. Advancement in application of biorefinery to production of biofuels, chemicals, and bio-derived materials necessitates a fundamental understanding of the relationship of lignin structure and biomass recalcitrance. In this mini-review, we focus on recent investigations on the influence of lignin chemical properties on bioprocessability—pretreatment and enzymatic hydrolysis of biomass. Furthermore, lignin-enzyme interactions and the effects of lignin compositional units, hydroxycinnamates, and lignin functional groups on biomass recalcitrance have been highlighted, which will be useful not only in addressing biomass recalcitrance but also in deploying renewable lignocelluloses efficiently.

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

Understanding the Impact of Hydrogen Activation by SrCe 0.8 Zr 0.2 O 3-δ Perovskite Membrane Material on Direct Non-Oxidative Methane Conversion

Direct non-oxidative methane conversion (DNMC) converts methane (CH 4 ) in one step to olefin and aromatic hydrocarbons and hydrogen (H 2 ) co-product. Membrane reactors comprising methane activation catalysts and H 2 -permeable membranes can enhance methane conversion by in situ H 2 removal via Le Chatelier's principle. Rigorous description of H 2 kinetic effects on both membrane and catalyst materials in the membrane reactor, however, has been rarely studied. In this work, we report the impact of hydrogen activation by hydrogen-permeable SrCe 0.8 Zr 0.2 O 3-δ (SCZO) perovskite oxide material on DNMC over an iron/silica catalyst. The SCZO oxide has mixed ionic and electronic conductivity and is capable of H 2 activation into protons and electrons for H 2 permeation. In the fixed-bed reactor packed with a mixture of SCZO oxide and iron/silica catalyst, stable and high methane conversion and low coke selectivity in DNMC was achieved by co-feeding of H 2 in methane stream. The characterizations show that SCZO activates H 2 to favor “soft coke” formation on the catalyst. The SCZO could absorb H 2 in situ to lower its local concentration to mitigate the reverse reaction of DNMC in the tested conditions. The co-existence of H 2 co-feed, SCZO oxide, and DNMC catalyst in the present study mimics the conditions of DNMC in the H 2 -permeable SCZO membrane reactor. The findings in this work offer the mechanistic understanding of and guidance for the design of H 2 -permeable membrane reactors for DNMC and other alkane dehydrogenation reactions.

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

Toward an Understanding of Synergies and Trade-Offs Between Water, Energy, and Food SDG Targets

Achieving the targets set out in the UN Sustainable Development Goals (SDG) will require committed efforts by nations and organizations over the coming decade. To determine which actions work most harmoniously within funding, infrastructure development, and implementation of three closely aligned goals, we conducted an assessment to identify where the greatest synergies may occur and where conflicting resource needs create trade-offs that may threaten SDG success. The SDGs each have several targets that need to be realized for the goal to be reached. In the present study, we developed a methodology where each target of the SDG 2 (food), 6 (water), and 7 (energy) was analyzed for its input requirements, infrastructure needs, and the risks and benefits for the provision of ecosystem services. Then the targets were compared pairwise and a total score of interaction was calculated to determine different levels of synergies and trade-offs for every pair. In some cases targets were mutually supportive, in other cases there were no interactions among the targets, and for some areas the targets were in conflict with each other. For example, targets 2.5 (maintain genetic diversity), 6.5 (implement integrated water resources management) and 7.a (enhance international cooperation to facilitate access to clean energy) have no conflicts with other targets and have different levels of synergies with most of the other targets. On the contrary, various targets of SDG 2, and especially the target 2.b (correct and prevent trade restrictions), are in slight conflict with other targets by potentially overusing resources needed by other targets or threatening ecosystem services. Our approach confirms the general belief that SDG 6 (water) has the highest number of potential synergies (a total of 124). Thus, achieving the water targets will make it continuously easier to achieve other targets. While the results may need to be adapted for a specific locality or country, overall they provide an improved understanding of the interactions between the targets. Furthermore, the value of the study lies in the quantitative methodology as it can be used as a replicable analysis for any level of work on SDG implementation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Pollution in the Press: Employing Text Analytics to Understand Regional Water Quality Narratives

Drinking water has and will continue to be at the foundation of our nation’s well-being and there is a growing interest in United States (US) drinking water quality. Nearly 30% of the United States population obtained their water from community water systems that did not meet federal regulations in 2019. Given the heavy interactions between society and drinking water quality, this study integrates social constructionism, environmental injustice, and sociohydrological systems to evaluate local awareness of drinking water quality issues. By employing text analytics, we explore potential drivers of regional water quality narratives within 25 local news sources across the United States. Specifically, we assess the relationship between printed local newspapers and water quality violations in communities as well as the influence of social, political, and economic factors on the coverage of drinking water quality issues. Results suggest that the volume and/or frequency of local drinking water violations is not directly reflected in local news coverage. Additionally, news coverage varied across sociodemographic features, with a negative relationship between Hispanic populations and news coverage of Lead and Copper Rule, and a positive relationship among non-Hispanic white populations. These findings extend current understanding of variations in local narratives to consider nuances of water quality issues and indicate opportunities for increasing equity in environmental risk communication.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Omics Approaches for Understanding Biogenesis, Composition and Functions of Fungal Extracellular Vesicles

Extracellular vesicles (EVs) are lipid bilayer structures released by organisms from all kingdoms of life. The diverse biogenesis pathways of EVs result in a wide variety of physical properties and functions across different organisms. Fungal EVs were first described in 2007 and different omics approaches have been fundamental to understand their composition, biogenesis, and function. In this review, we discuss the role of omics in elucidating fungal EVs biology. Transcriptomics, proteomics, metabolomics, and lipidomics have each enabled the molecular characterization of fungal EVs, providing evidence that these structures serve a wide array of functions, ranging from key carriers of cell wall biosynthetic machinery to virulence factors. Omics in combination with genetic approaches have been instrumental in determining both biogenesis and cargo loading into EVs. We also discuss how omics technologies are being employed to elucidate the role of EVs in antifungal resistance, disease biomarkers, and their potential use as vaccines. Finally, we review recent advances in analytical technology and multi-omic integration tools, which will help to address key knowledge gaps in EVs biology and translate basic research information into urgently needed clinical applications such as diagnostics, and immuno- and chemotherapies to fungal infections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation

Understanding gene function and regulation is essential for the interpretation, prediction, and ultimate design of cell responses to changes in the environment. A multitude of technologies, abstractions, and interpretive frameworks have emerged to answer the challenges presented by genome function and regulatory network inference. Here, we propose a new approach for producing biologically meaningful clusters of coexpressed genes, called Atomic Regulons (ARs), based on expression data, gene context, and functional relationships. We demonstrate this new approach by computing ARs for Escherichia coli , which we compare with the coexpressed gene clusters predicted by two prevalent existing methods: hierarchical clustering and k-means clustering. We test the consistency of ARs predicted by all methods against expected interactions predicted by the Context Likelihood of Relatedness (CLR) mutual information based method, finding that the ARs produced by our approach show better agreement with CLR interactions. We then apply our method to compute ARs for four other genomes: Shewanella oneidensis , Pseudomonas aeruginosa , Thermus thermophilus , and Staphylococcus aureus . We compare the AR clusters from all genomes to study the similarity of coexpression among a phylogenetically diverse set of species, identifying subsystems that show remarkable similarity over wide phylogenetic distances. We also study the sensitivity of our method for computing ARs to the expression data used in the computation, showing that our new approach requires less data than competing approaches to converge to a near final configuration of ARs. We go on to use our sensitivity analysis to identify the specific experiments that lead most rapidly to the final set of ARs for E. coli . As a result, this analysis produces insights into improving the design of gene expression experiments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Membrane-Inlet Mass Spectrometry Enables a Quantitative Understanding of Inorganic Carbon Uptake Flux and Carbon Concentrating Mechanisms in Metabolically Engineered Cyanobacteria

Photosynthesis uses solar energy to drive inorganic carbon (Ci) uptake, fixation, and biomass formation. In cyanobacteria, Ci uptake is assisted by carbon concentrating mechanisms (CCM), and CO 2 fixation is catalyzed by RubisCO in the Calvin-Benson-Bassham (CBB) cycle. Understanding the regulation that governs CCM and CBB cycle activities in natural and engineered strains requires methods and parameters that quantify these activities. Here, we used membrane-inlet mass spectrometry (MIMS) to simultaneously quantify Ci concentrating and fixation processes in the cyanobacterium Synechocystis 6803 . By comparing cultures acclimated to ambient air conditions to cultures transitioning to high Ci conditions, we show that acclimation to high Ci involves a concurrent decline of Ci uptake and fixation parameters. By varying light input, we show that both CCM and CBB reactions become energy limited under low light conditions. A strain over-expressing the gene for the CBB cycle enzyme fructose-bisphosphate aldolase showed higher CCM and carbon fixation capabilities, suggesting a regulatory link between CBB metabolites and CCM capacity. While the engineering of an ethanol production pathway had no effect on CCM or carbon fixation parameters, additional fructose-bisphosphate aldolase gene over-expression enhanced both activities while simultaneously increasing ethanol productivity. These observations show that MIMS can be a useful tool to study the extracellular Ci flux and how CBB metabolites regulate Ci uptake and fixation.

09 BIOMASS FUELS↗
DOE OSTI2024

Understanding piezocatalysis, pyrocatalysis and ferrocatalysis

The last decade has witnessed the emergence of the application of piezoelectric and ferroelectric materials for catalytic and photocatalytic applications that harness light, thermal and mechanical energy into chemical reactions. This article surveys the different concepts of pyro- and piezocatalysis and differences with respect to ferrocatalysis and switchable catalysis and delves into the current understanding of the mechanisms underlying piezocatalysis. The outlook for advancing in the surface science studies required for the design of new and better catalysts based on polar electromechanically active materials is discussed in the context of the state of the art experimental studies and potential future nanoscience developments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Understanding the Formation of Complex Phases: The Case of FeSi 2

One of the fundamental goals of materials science is to understand and predict the formation of complex phases. In this study, FeSi 2 is considered as an illustration of complex phase formation. Although Fe and Si both crystallize with a simple structure, namely, body-centered cubic (bcc A2) and diamond (A4) structures, respectively, it is rather intriguing to note the existence of two complex structures in the Si-rich part of the phase diagram around FeSi 2 : α-FeSi 2 at high temperatures (HT) with a slight iron-deficient structure and β-FeSi2 (also referred to as Fe 3 Si 7 ) at low temperatures (LT). We re-analyze the geometry of these two phases and rely on approximant phases that make the relationship between these two phases simple. To complete the analysis, we also introduce a surrogate of the C16 phase that is observed in FeGe 2 . We clearly identify the relationship that exists between these three approximant phases, corroborated by a ground-state analysis of the Ising model for describing ordering that takes place between the transition metal element and the “vacancies”. This work is further supported by ab initio electronic structure calculations based on density functional theory in order to investigate properties and transformation paths. Finally, extension to other alloys, including an entire class of alloys, is discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Atomic-Scale Understanding of Structure and Properties of Complex Pyrophosphate Crystals by First-Principles Calculations

The electronic structure and mechanical and optical properties of five pyrophosphate crystals with very complex structures are studied by first principles density functional theory calculations. The results show the complex interplay of the minor differences in specific local structures and compositions can result in large differences in reactivity and interaction that are rare in other classes of inorganic crystals. These are discussed by dividing the pyrophosphate crystals into three structural units. H 2 P 2 O 7 is the most important and dominating unit in pyrophosphates. The other two are the influential cationic group with metals and water molecules. The strongest P-O bond in P 2 O 5 is the strongest bond for crystal cohesion, but O-H and N-H bonds also play an important part. Different type of bonding between O and H atoms such as O-H, hydrogen bonding, and bridging bonds are present. Metallic cations such as Mg, Zn, and Cu form octahedral bonding with O. The water molecule provides the unique H∙∙∙O bonds, and metallic elements can influence the structure and bonding to a certain extent. The two Cu-containing phosphates show the presence of narrow metallic bands near the valence band edge. All this complex bonding affects their physical properties, indicating that fundamental understanding remains an open question.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Understanding Solid Electrolyte Interphase Nucleation and Growth on Lithium Metal Surfaces

Experiments and theory are needed to decode the exact structure and distribution of components of a passivation layer formed at the anode surface of Li metal batteries, known as the Solid Electrolyte Interphase (SEI). Due to the inherent dynamic behavior as well as the lithium reactivity, the SEI structure and its growth mechanisms are still unclear. This study uses molecular simulation and computational chemistry tools to investigate the initial nucleation and growth dynamics of LiOH and Li2O that provide us with thermodynamics and structural information about the nucleating clusters of each species. Following the most favorable pathways for the addition of each of the components to a given nascent SEI cluster reveals their preferential nucleation mechanisms and illustrates different degrees of crystallinity and electron density distribution that are useful to understand ionic transport through SEI blocks.

25 ENERGY STORAGE↗
DOE OSTI2018

Recent Progress in Atomic-Level Understanding of Cu/SSZ-13 Selective Catalytic Reduction Catalysts

Cu/SSZ-13 Selective Catalytic Reduction (SCR) catalysts have been extensively studied for the past five-plus years. New and exciting fundamental and applied science has appeared in the literature quite frequently over this time. In this short review, a few topics specifically focused on a molecular-level understanding of this catalyst are summarized: (1) The nature of the active sites and, in particular, their transformations under varying reaction conditions that include dehydration, the presence of the various SCR reactants and hydrothermal aging; (2) Discussions of standard and fast SCR reaction mechanisms. Considerable progress has been made, especially in the last couple of years, on standard SCR mechanisms. In contrast, mechanisms for fast SCR are much less understood. Possible reaction paths are hypothesized for this latter case to stimulate further investigations; (3) Discussions of rational catalyst design based on new knowledge obtained regarding catalyst stability, overall catalytic performance and mechanistic catalytic chemistry.

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

Applying Two-Dimensional Correlation Spectroscopy and Principal Component Analysis to Understand How Temperature Affects the Neptunium(V) Absorption Spectrum

The visible-near infrared (Vis-NIR) electronic absorption spectrum of neptunium(V) (NpO 2 + ) comprises numerous f-f electronic transitions with mostly undocumented temperature dependencies. The effect of temperature on the absorption spectrum of the pentavalent neptunyl dioxocation (NpO 2 + ) is an important factor to consider with spectrophotometric applications but has often been overlooked. Optical Vis-NIR absorption spectra (400–1700 nm) of Np(V) (0.017–0.89 M) in 1 M nitric acid were evaluated with varying temperatures (T = 10–80 °C). The intensity, position, and overall shape of the bands were sensitive to interactions with the solvent and coordination environment. Numerous temperature-induced isosbestic points were identified resulting from dynamic, overlapping peak shifts. Spectral variations were characterized using principal component analysis (PCA) and 2D correlation spectroscopy (COS). 2D-COS revealed that the absorption band near 1095 nm likely consists of two bands centered near 1087 and 1096 nm, which cannot be explained by current computational methods. 2D-COS analysis also provided an unambiguous assignment of unresolved peaks in the visible region for comparison with computational predictions. PCA was used to identify nonlinearity in the spectral response at elevated Np(V) concentrations ≥ 0.5 M. This unique experimental data and interpretation will foster a deeper understanding of the absorption spectra for complex actinyl ions.

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

The Role of Dimensionality in Understanding Granuloma Formation

Within the first 2–3 months of a Mycobacterium tuberculosis (Mtb) infection, 2–4 mm spherical structures called granulomas develop in the lungs of the infected hosts. These are the hallmark of tuberculosis (TB) infection in humans and non-human primates. A cascade of immunological events occurs in the first 3 months of granuloma formation that likely shapes the outcome of the infection. Understanding the main mechanisms driving granuloma development and function is key to generating treatments and vaccines. In vitro, in vivo, and in silico studies have been performed in the past decades to address the complexity of granuloma dynamics. This study builds on our previous 2D spatio-temporal hybrid computational model of granuloma formation in TB (GranSim) and presents for the first time a more realistic 3D implementation. We use uncertainty and sensitivity analysis techniques to calibrate the new 3D resolution to non-human primate (NHP) experimental data on bacterial levels per granuloma during the first 100 days post infection. Due to the large computational cost associated with running a 3D agent-based model, our major goal is to assess to what extent 2D and 3D simulations differ in predictions for TB granulomas and what can be learned in the context of 3D that is missed in 2D. Our findings suggest that in terms of major mechanisms driving bacterial burden, 2D and 3D models return very similar results. For example, Mtb growth rates and molecular regulation mechanisms are very important both in 2D and 3D, as are cellular movement and modulation of cell recruitment. The main difference we found was that the 3D model is less affected by crowding when cellular recruitment and movement of cells are increased. Overall, we conclude that the use of a 2D resolution in GranSim is warranted when large scale pilot runs are to be performed and if the goal is to determine major mechanisms driving infection outcome (e.g., bacterial load). To comprehensively compare the roles of model dimensionality, further tests and experimental data will be needed to expand our conclusions to molecular scale dynamics and multi-scale resolutions.

2D vs. 3D↗
DOE OSTI2022

Understanding the Accuracy Limitations of Quantifying Methane Emissions Using Other Test Method 33A

Researchers have utilized Other Test Method (OTM) 33A to quantify methane emissions from natural gas infrastructure. Historically, errors have been reported based on a population of measurements compared to known controlled releases of methane. These errors have been reported as 2σ errors of ±70%. However, little research has been performed on the minimum attainable uncertainty of any one measurement. We present two methods of uncertainty estimation. The first was the measurement uncertainty of the state-of-the-art equipment, which was determined to be ±3.8% of the estimate. This was determined from bootstrapped measurements compared to controlled releases. The second approach of uncertainty estimation was a modified Hollinger and Richardson (H&R) method which was developed for quantifying the uncertainty of eddy covariance measurements. Using a modified version of this method applied to OTM 33A measurements, it was determined that uncertainty of any given measurement was ±17%. Combining measurement uncertainty with that of stochasticity produced a total minimum uncertainty of 17.4%. Due to the current nature of stationary single-sensor measurements and the stochasticity of atmospheric data, such uncertainties will always be present. This is critical in understanding the transport of methane emissions and indirect measurements obtained from the natural gas industry.

Heltzel, Robert↗
DOE OSTI2022

A Review of Modeling Approaches for Understanding and Monitoring the Environmental Effects of Marine Renewable Energy

Understanding the environmental effects of marine energy (ME) devices is fundamental for their sustainable development and efficient regulation. However, measuring effects is difficult given the limited number of operational devices currently deployed. Numerical modeling is a powerful tool for estimating environmental effects and quantifying risks. It is most effective when informed by empirical data and coordinated with the development and implementation of monitoring protocols. We reviewed modeling techniques and information needs for six environmental stressor–receptor interactions related to ME: changes in oceanographic systems, underwater noise, electromagnetic fields (EMFs), changes in habitat, collision risk, and displacement of marine animals. This review considers the effects of tidal, wave, and ocean current energy converters. We summarized the availability and maturity of models for each stressor–receptor interaction and provide examples involving ME devices when available and analogous examples otherwise. Models for oceanographic systems and underwater noise were widely available and sometimes applied to ME, but need validation in real-world settings. Many methods are available for modeling habitat change and displacement of marine animals, but few examples related to ME exist. Models of collision risk and species response to EMFs are still in stages of theory development and need more observational data, particularly about species behavior near devices, to be effective. We conclude by synthesizing model status, commonalities between models, and overlapping monitoring needs that can be exploited to develop a coordinated and efficient set of protocols for predicting and monitoring the environmental effects of ME.

16 TIDAL AND WAVE POWER↗