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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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986 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Overexpression of a Sugarcane BAHD Acyltransferase Alters Hydroxycinnamate Content in Maize Cell Wall

The purification of hydroxycinnamic acids [ p -coumaric acid ( p CA) and ferulic acid (FA)] from grass cell walls requires high-cost processes. Feedstocks with increased levels of one hydroxycinnamate in preference to the other are therefore highly desirable. We identified and conducted expression analysis for nine BAHD acyltransferase ScAts genes from sugarcane. The high conservation of AT10 proteins, together with their similar gene expression patterns, supported a similar role in distinct grasses. Overexpression of ScAT10 in maize resulted in up to 75% increase in total p CA content. Mild hydrolysis and derivatization followed by reductive cleavage (DFRC) analysis showed that p CA increase was restricted to the hemicellulosic portion of the cell wall. Furthermore, total FA content was reduced up to 88%, resulting in a 10-fold increase in the p CA/FA ratio. Thus, we functionally characterized a sugarcane gene involved in p CA content on hemicelluloses and generated a C4 plant that is promising for valorizing p CA production in biorefineries.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Cell wall response of field grown Populus to Septoria infection

Due to its ability to spread quickly and result in tree mortality, Sphaerulina musiva (Septoria) is one of the most severe diseases impacting Populus . Previous studies have identified that Septoria infection induces differential expression of phenylpropanoid biosynthesis genes. However, more extensive characterization of changes to lignin in response to Septoria infection is lacking. To study the changes of lignin due to Septoria infection, four field grown, naturally variant Populus trichocarpa exhibiting visible signs of Septoria infection were sampled at health, infected, and reaction zone regions for cell wall characterization. Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR), and acid hydrolysis were applied to identify changes to the cell wall, and especially lignin. FTIR and subsequent principal component analysis revealed that infected and reaction zone regions were similar and could be distinguished from the non-infected (healthy) region. NMR results indicated the general trend that infected region had a higher syringyl:guaiacyl ratio and lower p -hydroxybenzoate content than the healthy regions from the same genotype. Finally, Klason lignin content in the infected and/or reaction zone regions was shown to be higher than healthy region, which is consistent with previous observations of periderm development and metabolite profiling. These results provide insights on the response of Populus wood characteristics to Septoria infection, especially between healthy and infected region within the same genotype.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Metabolite signatures in hydrophilic extracts of mouse lungs exposed to cigarette smoke revealed by 1 H NMR metabolomics investigation

Herein, 1 H-NMR metabolomics are carried out to evaluate the changes of metabolites in lungs of mice exposed to cigarette smoke. It is found that the concentrations of adenosine derivatives (i.e. ATP, ADP and AMP), inosine and uridine are significantly fluctuated in the lungs of mice exposed to cigarette smoke compared with those of controls regardless the mouse is obese or regular weight. The decreased ATP, ADP, AMP and elevated inosine predict that the deaminases in charge of adenosine derivatives to inosine derivatives conversion are altered in lungs of mice exposed to cigarette smoke. Transcriptional analysis reveals that the concentrations of adenosine monophosphate deaminase and adenosine deaminase are different in the lungs of mice exposed to cigarette smoke, confirming the prediction from metabolomics studies. We also found, for the first time, that the ratio of glycerophosphocholine (GPC) to phosphocholine (PC) is significantly increased in the lungs of obese mice compared with regular weight mice. The ratio of GPC/PC is further elevated in the lungs of obese group by cigarette smoke exposure. Since GPC/PC ratio is a known biomarker for cancer, these results may suggest that obese group is more susceptible to lung cancer when exposed to cigarette smoke.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Atmospheric condition identification in multivariate data through a metric for total variation

Identification of atmospheric conditions within a multivariable atmospheric data set is a necessary step in the validation of emerging and existing high-fidelity models used to simulate wind plant flows and operation.Atmospheric conditions relevant for wind energy research include stationary conditions, given the need for well-converged statistics for model validation, as well as conditions observed less frequently, such as extreme atmospheric events, which are used in wind turbine and wind plant design.Aggregation of observations without regard to covariance between time series discounts the dynamical nature of the atmosphere and is not sufficiently representative of atmospheric conditions.Identification and characterization of continuous time periods with atmospheric conditions that have a high value for analysis or simulation set the stage for more advanced model validation and the development of real-time control and operational strategies.The current work explores a single metric for variation in a multivariate data sample that quantifies variability within each channel as well as covariance between channels.The total variation is used to identify conditions of interest that conform to desired objective functions, such as stationary conditions, ramps or waves of wind speed, and changes in wind direction.Total variation is somewhat sensitive to the presence of outliers in the input data, and the method is best complemented by quality-control procedures to ensure reliable results.The direct detection and classification of events or conditions of interest within atmospheric data sets is vital to developing our understanding of wind plant response and to the formulation of forecasting and control models.

17 WIND ENERGY↗
NASA NTRS2024

Baltimore Energy & Infrastructure: Assessing Urban Heat Vulnerability in Baltimore Neighborhoods to Inform Transportation Resiliency Planning Efforts

Across the world, climate change is altering cities and their local climate systems. Following global trends of rising mean temperatures, Baltimore, Maryland is projected to experience more frequent extreme heat events. Exacerbated by Urban Heat Island (UHI) effects, residents of the city face high temperatures from limited tree canopy, highly paved and impervious surfaces, limited air flow, and high concentrations of localized emissions. Urban heat is dispersed asymmetrically, with historically marginalized populations experiencing disproportionately severe heat. Recognizing the impacts of extreme urban heat, the Maryland Transit Administration (MTA) collaborated with us, the Spring 2024 Goddard Energy and Infrastructure NASA DEVELOP team to assess urban impacts of MTA users and assets and explore opportunities to enhance resiliency planning. We evaluated the feasibility of NASA Earth observations (EOs) in visualizing heat vulnerability in Baltimore City and County. We mapped UHI and extreme heat using remote sensing observations, tailored a Heat Priority Score (HPS) to analyze heat data in tandem with socioeconomic data from American Community Survey (ACS), and utilized SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG) model to estimate MTA riders’ thermal comfort. NASA EOs served to quantify the distribution and severity of extreme heat at the block group level, which was found to correlate with a lack of vegetation and presence of densely built-up surroundings. The HPS revealed that extreme heat events most negatively impact communities that exhibit social vulnerability through indicators such as age, race, and income. These findings will inform neighborhood resiliency plans for the MTA that can be incorporated into their Adaptation Resiliency Toolbox (ART).

Baltimore,↗
DOE OSTI2012

Pre-Processing of Cross-Sections Using Dimensionality Reduction Techniques

Reactor physics codes rely on cross-section data to determine, for example, flux profiles or burn-up calculations. This data contains cross section values for different neutron-atom interactions (e.g., absorption, fission and scattering) for a large number of isotopes as function of energy and it is tabulated for a specific set of parameters (e.g., moderator temperature, fuel temperature, moderator density). In order to perform such neutronic calculations, the amount of this data that needs to be stored is very large due to the high number of isotopes and many tabulation points are needed. This data needs to be retrieved at each time iteration of the code from the machine memory which negatively affects the computational time of the code itself.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Pumped Storage Hydropower Potential and Opportunities

Pumped storage hydropower (PSH) is a flexible energy storage technology with the potential to improve grid reliability, resiliency, and stability in the electric grid of the future. NREL has developed a range of data and tools to help understand opportunities for new PSH deployment, including nationwide resource assessment data, a bottom-up component-level cost model, and a lifecycle greenhouse gas emissions calculator. These datasets can then be used to inform grid planning models, analysis, and decision making to understand the role PSH can play in the power sector.

cost↗
DOE OSTI2025

Exploring Geothermal Potential of Great Basin Sub-Regions

The INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems (INGENIOUS) project aims to discover new, economically viable hidden geothermal systems in the Great Basin region by building on previous work in play fairway analysis and machine learning. A key objective of this project is to develop an exploration workflow to reduce geothermal exploration risks for hidden geothermal systems. A single preliminary play fairway workflow was developed from the assessment of the regional INGENIOUS geological, geophysical, and geochemical datasets. This workflow provided new preliminary predictive geothermal fairway maps for the INGENIOUS study area, which encompasses most of Nevada, western Utah, southern Idaho, southeastern Oregon, and easternmost California. However, a recent study (incorporating machine learning techniques) of a portion of Nevada identified four geologic domains and determined that the relative importance of individual datasets or features as indicators of geothermal potential may differ across these domains. The INGENIOUS study area includes a much larger and more geologically diverse region; therefore, additional geologic domains or sub-regions are expected. To assess the sub-regions in the INGENIOUS study area, principal component analysis and k-means clustering were applied. Preliminary results indicate that the INGENIOUS regional data cluster into groups that relate to different geologic domains in the Great Basin region. These include domains such as the Walker Lane, extensional western Great Basin region, broad lower strain region in the eastern Great Basin of western Utah and eastern Nevada, Quaternary volcanic fields, and the area adjacent to the Snake River Plain. These clusters are assessed to determine the key geologic drivers of the identified clusters. Understanding this variability can provide key insights for the exploration and characterization of hidden geothermal systems in the Great Basin region and could indicate the need to develop multiple geothermal conceptual models and play fairway workflows for the INGENIOUS study area.

exploration↗