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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 73 records · Page 4

Extraction of Furfural and Furfural/5-Hydroxymethylfurfural from Mixed Lignocellulosic Biomass-Derived Feedstocks

We present a combined in silico and experimental study on the extraction of furfural and 5-hydroxymethylfurfural (HMF) in aqueous–organic biphasic systems. We predict the liquid–liquid equilibria and furfural/HMF partition coefficients of over 2200 water-organic biphasic systems using the multiscale COSMO-RS model and measure experimentally single-component (furfural) and mixture (furfural and HMF) partition coefficients at room and dehydration reaction-relevant temperatures in 28 solvents. We find the experimental data to be within a factor of 2 from the COSMO-RS predictions. Even though furfural and HMF have chemical similarity, the slight differences in molecular structure render the separation of furfural easier by the supply of more solvents of higher partition coefficient for extraction. We leverage this molecular difference and experimentally demonstrate that with an additional extraction step, using dichloromethane or toluene, we can selectively extract furfural from furfural-HMF mixtures, which can coexist in lignocellulosic biomass dehydration products, despite their partition coefficients being generally correlated. We complement solvent selection criteria for biphasic lignocellulosic biomass processes with a simple mass balance extraction model for determining volume ratios in multistage extraction. Lastly, the molecular nature of the preferential furfural extraction is rationalized using COSMO-RS σ-profile analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A highly efficient uranium grabber derived from acrylic fiber for extracting uranium from seawater

Acrylic fiber can be chemically converted to an am- idoxime and carboxylate containing chelating adsorbent for extraction of uranium from seawater. At an optimized ratio of amidoxime:carboxylate, the chelating fiber in real seawater shows a higher uranium, shorter saturation time and lower vanadium adsorption capacity relative to similar high-surface area chelating fibers developed recently using a radiation-induced grafting method. This simple and low-cost synthesis method can be scaled up to mass produce the chelating fiber for recovering metals from aquatic environments including production of uranium from seawater.

Pan, H B.↗

Evaluating the location capabilities of a regional infrasonic network in Utah, US, using both ray tracing-derived and empirical-derived celerity-range and backazimuth models

SUMMARY More realistic models for infrasound signal propagation across a region can be used to improve the precision and accuracy of spatial and temporal source localization estimates. Motivated by incomplete infrasound event bulletins in the Western US, the location capabilities of a regional infrasonic network of stations located between 84–458 km from the Utah Test and Training Range, Utah, USA, is assessed using a series of near-surface explosive events with complementary ground truth (GT) information. Signal arrival times and backazimuth estimates are determined with an automatic F-statistic based signal detector and manually refined by an analyst. This study represents the first application of three distinct celerity-range and backazimuth models to an extensive suite of realistic signal detections for event location purposes. A singular celerity and backazimuth deviation model was previously constructed using ray tracing analysis based on an extensive archive of historical atmospheric specifications and is applied within this study to test location capabilities. Similarly, a set of multivariate, season and location specific models for celerity and backazimuth are compared to an empirical model that depends on the observations across the infrasound network and the GT events, which accounts for atmospheric propagation variations from source to receiver. Discrepancies between observed and predicted signal celerities result in locations with poor accuracy. Application of the empirical model improves both spatial localization precision and accuracy; all but one location estimates retain the true GT location within the 90 per cent confidence bounds. Average mislocation of the events is 15.49 km and average 90 per cent error ellipse areas are 4141 km2. The empirical model additionally reduces origin time residuals; origin time residuals from the other location models are in excess of 160 s while residuals produced with the empirical model are within 30 s of the true origin time. We demonstrate that event location accuracy is driven by a combination of signal propagation model and the azimuthal gap of detecting stations. A direct relationship between mislocation, error ellipse area and increased station azimuthal gaps indicate that for sparse networks, detection backazimuths may drive location biases over traveltime estimates.

58 GEOSCIENCES↗

Data for Greenhouse Gas Accounting Procedures in Low Carbon Fuel Policies Overlook the Spatial Variability of Miscanthus-Derived Sustainable Aviation Fuel

Low carbon fuel policies such as the U.S. Renewable Fuel Standard (RFS), Canada Clean Fuel Regulations (CFR), and California Low Carbon Fuel Standard (LCFS) as well as the 45Z tax credit are intended to reduce greenhouse gas (GHG) emissions from transportation. Cellulosic feedstocks, optimized biorefineries, and favorable farming locations can significantly reduce biofuel carbon intensity (CI). Despite advances in field-to-fuel GHG monitoring and flexibility in resource allocation within biorefineries (e.g., governing net electricity production), rigid CI accounting procedures in current policies may limit CI responsiveness across candidate sites and processing facilities. This work examines a hypothetical biomass-to-sustainable aviation fuel (SAF) pathway using miscanthus and alcohol-to-jet (i) to demonstrate how GHG accounting requirements drive estimates of biofuel CIs and (ii) to explore potential CI and financial implications of scenario-specific life cycle assessment (LCA). Results demonstrate that GHG accounting using the CFR/LCFS can reasonably account for distinct levels of net electricity production by a biorefinery, but only the CFR yields similar CI sensitivity to spatially explicit factors (feedstock CI, grid electricity CI) as scenario-specific LCA: most GHG accounting frameworks do not capture CI variation across candidate sites in the United States. Ultimately, this work demonstrates the importance of LCA methodological specifications in low carbon fuel policies and tax credits.

Miscanthus↗

Multi-resolution Arctic Shrub Cover Dataset Derived from UAS and Airborne SfM and LiDAR (2013-2025)

We synthesized 177 unoccupied aerial system flights and 77 airborne flights across the Arctic and created a multi-resolution benchmark data of low-to-tall shrub fractional cover leveraging Structure-from-Motion and Light Detection and Ranging. The resulting dataset covered a total of 1899 km2 across Alaska, Western Canada, Sweden, and Siberian Arctic, including key sites from the Oro Arctic to the High Arctic. The dataset is organized into 6 primary data collection directories (“Abisko,” “AWI,” “ERE,” “Fairbanks,” “NGEE,” “Toolik”), each containing site and flight subdirectories. Flight directories include shrub cover rasters (*.tifs) at 1 m, 5 m, and 30 m resolution, the canopy height model at 1 m resolution (*.tifs), and a bounding box *.kml file. For the AWI, Abisko, NGEE, and Fairbanks collections, we also include the GCC raster at 1 m resolution (*.tif). Files are organized by Collection > Site > Flight Name > Data Files. Flight rasters are in the local UTM zone and the .kml files are in the geographic coordinate system EPSG 4326. We also include a .csv file that details the source datasets for every flight. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

canopy height model↗

Modeled Results of Four Residential Energy Efficiency Measure Packages for Deriving Advanced Building Construction Research Targets

The Advanced Building Construction (ABC) Initiative from the U.S. Department of Energy Building Technologies Office is working to accelerate industrialized construction innovations for decarbonizing buildings. To inform performance and cost targets for research under the ABC Initiative, this analysis used the ResStock™ tool to evaluate the energy savings, utility bill impacts, and carbon emissions impacts of four simulated upgrade packages with specific target performance levels on a large sample of residential dwelling units (approximately 550,000) representative of the U.S. housing stock.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Biomass-Derived Carbon and Their Composites for Supercapacitor Applications: Sources, Functions, and Mechanisms

Biomass-derived carbons are eco-friendly and sustainable materials, making them ideal for supercapacitors due to their high surface area, excellent conductivity, cost-effectiveness, and environmental benefits. This review provides valuable insights into biomass-derived carbon and modified carbon for supercapacitors, integrating both experimental results and theoretical calculations. This review begins by discussing the origins of biomass-derived carbon in supercapacitors, including plant-based, food waste-derived, animal-origin, and microorganism-generated sources. Then, this review presents strategies to improve the performance of biomass-derived carbon in supercapacitors, including heteroatom doping, surface functionalization, and hybrid composite construction. Furthermore, this review analyzes the functions of biomass-derived carbon in supercapacitors both in its pure form and as modified materials. The review also explores composites derived from biomass-based carbon, including carbon/MXenes, carbon/MOFs, carbon/graphene, carbon/conductive polymers, carbon/transition metal oxides, and carbon/hydroxides, providing a thorough investigation. Most importantly, this review offers an innovative summary and analysis of the role of biomass-derived carbon in supercapacitors through theoretical calculations, concentrating on four key aspects: energy band structure, density of states, electron cloud density, and adsorption energy. Finally, the review concludes the future research directions for biomass carbon-based supercapacitors, including the discovery of novel biomass materials, tailoring surface functional groups, fabricating high-performance composite materials, exploring ion transfer mechanisms, and enhancing practical applications. In summary, this review offers a thorough exploration of the sources, functions, and mechanisms of biomass-derived carbon in supercapacitors, providing valuable insights for future research.

biomass-derived carbon↗

Solar position confounds the relationship between ecosystem function and vegetation indices derived from solar and photosynthetically active radiation fluxes

Vegetation indices derived from solar and photosynthetically active radiation (PAR) sensors (i.e. radiation derived) have been under-utilized in inferring ecosystem function, despite measurement capability at hundreds of sites. This under-utilization may be attributed to reported mismatches among the seasonality of radiation- and satellite-derived vegetation indices and canopy photosynthesis; herein referred to as measurement biases. In this work, biases in radiation derived reflectance and vegetation indices were assessed using a decadal record of satellite and ground based spectroradiometer data, ecosystem phenology and CO 2 fluxes, and radiation derived vegetation indices (i.e. the Normalized Difference Vegetation Index [NDVI], the two band Enhanced Vegetation Index [EVI2]) from a high latitude tundra site (i.e. Imnaviat). At Imnaviat, we found poor correspondence between the three types of reflectance and vegetation indices, especially during the latter part of the growing season. Radiation derived vegetation indices resulted in incorrect estimates of phenological timing of up to a month and poor relationships with canopy photosynthesis (i.e. Gross Ecosystem Exchange (GEE)). These mismatches were attributed to solar position (i.e. solar zenith and azimuth angle) and a method, based on the diel visible and near-infrared albedo variation, was developed to improve the performance of the vegetation indices. The ability of radiation derived vegetation indices to infer GEE and phenological dates drastically improved once radiation derived vegetation indices were corrected for solar position associated biases at Imnaviat. Moreover, radiation derived vegetation indices became better aligned with MODerate resolution Imaging Spectroradiometer (MODIS) satellite estimates after solar position associated biases were corrected at Imnaviat and at 25 Fluxnet sites (~90 site years) across North America. Corrections developed here provide a way forward in understanding daily ecosystem function or filling large gaps in eddy covariance data at a significant number of Fluxnet sites.

54 ENVIRONMENTAL SCIENCES↗

Recommendations for developing, documenting, and distributing data products derived from NEON data

The National Ecological Observatory Network (NEON) provides over 180 distinct data products from 81 sites (47 terrestrial and 34 freshwater aquatic sites) within the United States and Puerto Rico. These data products include both field and remote sensing data collected using standardized protocols and sampling schema, with centralized quality assurance and quality control (QA/QC) provided by NEON staff. Such breadth of data creates opportunities for the research community to extend basic and applied research while also extending the impact and reach of NEON data through the creation of derived data products—higher level data products derived by the user community from NEON data. Derived data products are curated, documented, reproducibly-generated datasets created by applying various processing steps to one or more lower level data products—including interpolation, extrapolation, integration, statistical analysis, modeling, or transformations. Derived data products directly benefit the research community and increase the impact of NEON data by broadening the size and diversity of the user base, decreasing the time and effort needed for working with NEON data, providing primary research foci through the development via the derivation process, and helping users address multidisciplinary questions. Creating derived data products also promotes personal career advancement to those involved through publications, citations, and future grant proposals. However, the creation of derived data products is a nontrivial task. Here we provide an overview of the process of creating derived data products while outlining the advantages, challenges, and major considerations.

54 ENVIRONMENTAL SCIENCES↗

Rock-Sourced Nitrogen in Semi-Arid, Shale-Derived California Soils

Models suggest that rock-derived nitrogen (N) inputs are of global importance to ecosystem N budgets; however, field studies demonstrating the significance of rock N inputs are rare. We examined rock-derived N fluxes in soils derived from sedimentary rocks along a catena formed under a semi-arid climate. Our measurements demonstrate that there are distinct and traceable pools of N in the soil and bedrock and that the fraction of rock-derived N declines downslope along the catena. We used geochemical mass balance weathering flux measurements to estimate a rock-derived N flux of 0.145 to 0.896 kg ha -1 yr -1 at the ridgecrest. We also developed independent N flux estimates using a 15 N-based isotope mixing model. While geochemical mass-balance-based estimates fell within the 95% confidence range derived from the isotope mixing model (-1.1 to 44.3 kg ha -1 yr -1 ), this range was large due to uncertainty in values for atmospheric 15 N deposition. Along the catena, N isotopes suggest a diminishing effect of rock-derived N downslope. Overall, we found that despite relatively large N pools within the saprolite and bedrock, slow chemical weathering and landscape denudation limit the influence of rock-derived N, letting atmospheric N deposition (7.1 kg ha -1 yr -1 ) and N fixation (0.9-3.1 kg ha -1 yr -1 ) dominate N inputs to this grassland ecosystem.

54 ENVIRONMENTAL SCIENCES↗

Identification of the Tyrosine- and Phenylalanine-Derived Soluble Metabolomes of Sorghum

The synthesis of small organic molecules, known as specialized or secondary metabolites, is one mechanism by which plants resist and tolerate biotic and abiotic stress. Many specialized metabolites are derived from the aromatic amino acids phenylalanine (Phe) and tyrosine (Tyr). In addition, the improved characterization of compounds derived from these amino acids could inform strategies for developing crops with greater resilience and improved traits for the biorefinery. Sorghum and other grasses possess phenylalanine ammonia-lyase (PAL) enzymes that generate cinnamic acid from Phe and bifunctional phenylalanine/tyrosine ammonia-lyase (PTAL) enzymes that generate cinnamic acid and p -coumaric acid from Phe and Tyr, respectively. Cinnamic acid can, in turn, be converted into p -coumaric acid by cinnamate 4-hydroxylase. Thus, Phe and Tyr are both precursors of common downstream products. Not all derivatives of Phe and Tyr are shared, however, and each can act as a precursor for unique metabolites. In this study, 13 C isotopic-labeled precursors and the recently developed Precursor of Origin Determination in Untargeted Metabolomics (PODIUM) mass spectrometry (MS) analytical pipeline were used to identify over 600 MS features derived from Phe and Tyr in sorghum. These features comprised 20% of the MS signal collected by reverse-phase chromatography and detected through negative-ionization. Ninety percent of the labeled mass features were derived from both Phe and Tyr, although the proportional contribution of each precursor varied. In addition, the relative incorporation of Phe and Tyr varied between metabolites and tissues, suggesting the existence of multiple pools of p -coumaric acid that are fed by the two amino acids. Furthermore, Phe incorporation was greater for many known hydroxycinnamate esters and flavonoid glycosides. In contrast, mass features derived exclusively from Tyr were the most abundant in every tissue. The Phe- and Tyr-derived metabolite library was also utilized to retrospectively annotate soluble MS features in two brown midrib mutants ( bmr6 and bmr12 ) identifying several MS features that change significantly in each mutant.

09 BIOMASS FUELS↗

Optimization using pathwise algorithmic derivatives of electromagnetic shower simulations

Among the well-known methods to approximate derivatives of expectancies computed by Monte-Carlo simulations, averages of pathwise derivatives are often the easiest one to apply. Computing them via algorithmic differentiation typically does not require major manual analysis and rewriting of the code, even for very complex programs like simulations of particle-detector interactions in high-energy physics. However, the pathwise derivative estimator can be biased if there are discontinuities in the program, which may diminish its value for applications. This work integrates algorithmic differentiation into the electromagnetic shower simulation code HepEmShow based on G4HepEm, allowing us to study how well pathwise derivatives approximate derivatives of energy depositions in a sampling calorimeter with respect to parameters of the beam and geometry. We found that when multiple scattering is disabled in the simulation, means of pathwise derivatives converge quickly to their expected values, and these are close to the actual derivatives of the energy deposition. Additionally, we demonstrate the applicability of this novel gradient estimator for stochastic gradient-based optimization in a model example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Equation of state for He bubbles in W and model of He bubble growth and bursting near W{100} surfaces derived from molecular dynamics simulations

Abstract Molecular dynamics (MD) simulations are performed to derive an equation of state (EOS) for helium (He) bubbles in tungsten (W) and to study the growth of He bubbles under a W(100) surface until they burst. We study the growth as a function of the initial nucleation depth of the bubbles. During growth, successive loop-punching events are observed, accompanied by shifts in the depth of the bubble towards the surface. Subsequently, the MD data are used to derive models that describe the conditions that cause the loop punching and bursting events. Simulations have been performed at 500, 933, 1500, 2000, and 2500 K to fit the parameters in the models. To compute the pressure in the bubble at the loop punching and bursting events from the models, we derive an EOS for He bubbles in tungsten with an accompanying volume model to compute the bubble volume for a given number of vacancies ( $$N_\text {V}$$ N V ), He atoms ( $$N_\text {He}$$ N He ), and temperature ( T ). To derive the bubble EOS, we firstly derive the EOS for a free He gas. The derived free-gas EOS can accurately predict all MD data included in the analysis (which span up to 54 GPa at 2500 K). Subsequently, the bubble EOS is derived based on the free-gas EOS by correcting the gas density to account for the interaction between He and W atoms. The EOS for the bubbles is fitted to data from MD simulations of He bubbles in bulk W that span a wide range of gas density and sizes up to about 3 nm in diameter. The pressure of subsurface bubbles at the loop punching events as calculated using the bubble-EOS and the volume model agrees well with the pressure obtained directly from the MD simulations. In the loop punching model, for bubbles consisting of $$N_\text {V}$$ N V vacancies and $$N_\text {He}$$ N He helium atoms, the $$N_\text {He}/N_\text {V}$$ N He / N V ratio that causes the event, the resulting increase in $$N_\text {V}$$ N V , and the associated shift of the bubble depth are formulated as a function of $$N_\text {V}$$ N V and T . In the bursting model, a bubble must simultaneously reach a certain depth and $$N_\text {He}/N_\text {V}$$ N He / N V ratio in order to burst. The burst depth and $$N_\text {He}/N_\text {V}$$ N He / N V are also modeled as a function of $$N_\text {V}$$ N V and T . The majority of the loop punching events occur at bubble pressures between 20 and 60 GPa, depending on the bubble size and temperature. The larger the bubble and the higher the temperature, the lower the bubble pressure. Furthermore, our results indicate that at a higher temperature, a bubble can burst from a deeper region.

36 MATERIALS SCIENCE↗

On the Derivation of Quasi-Newton Formulas for Optimization in Function Spaces

Newton’s method is usually preferred when solving optimization problems due to its superior convergence properties compared to gradient-based or derivative-free optimization algorithms. However, deriving and computing second-order derivatives needed by Newton’s method often is not trivial and, in some cases, not possible. In such cases quasi-Newton algorithms are a great alternative. In this paper, we provide a new derivation of well-known quasi-Newton formulas in an infinite-dimensional Hilbert space setting. Furthermore, it is known that quasi-Newton update formulas are solutions to certain variational problems over the space of symmetric matrices. In this paper, we formulate similar variational problems over the space of bounded symmetric operators in Hilbert spaces. By changing the constraints of the variational problem we obtain updates (for the Hessian and Hessian inverse) not only for the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method but also for Davidon–Fletcher–Powell (DFP), Symmetric Rank One (SR1), and Powell-Symmetric-Broyden (PSB). In addition, for an inverse problem governed by a partial differential equation (PDE), we derive DFP and BFGS “structured” secant formulas that explicitly use the derivative of the regularization and only approximates the second derivative of the misfit term. We show numerical results that demonstrate the desired mesh-independence property and superior performance of the resulting quasi-Newton methods.

97 MATHEMATICS AND COMPUTING↗