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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Discovery and analysis of a blind geothermal system in southeastern Gabbs Valley, Western Nevada

This study assessed the potential for high-temperature (≥130°C) blind geothermal systems in southeastern Gabbs Valley by employing a geothermal play fairway analysis approach involving integration of geologic, geophysical, and geochemical datasets. Gabbs Valley is a complex, tectonically active basin within the Great Basin on the boundary between the transtensional central Walker Lane domain and extensional Basin and Range province. The termination of the Petrified Springs fault, a major dextral fault of the central Walker Lane, in an array of normal faults indicates that southeastern Gabbs Valley occupies a displacement transfer zone, which is a favorable structural setting for geothermal activity. The displacement transfer zone is a structurally complicated area with many faults of varying geometries, kinematics, and ages. A substantial northwest-trending gravity high within the south-central part of southeastern Gabbs Valley is produced from offsets along concealed northwest-striking dextral-normal faults that intersect strands of north-northeast-to east-northeast-striking normal faults. This area of tightly spaced faults and fault intersections is a particularly favorable structural setting within the broader-scale displacement transfer zone. Multiple lines of direct and indirect evidence suggest the presence of a relatively high-temperature (≥130°C) blind geothermal system in this area, including collocated intersecting gravity gradients, magnetic-low, low-resistivity, and 2-m temperature anomaly. Potentially related, water samples from agricultural wells ~7 km northwest of the 2-m anomaly yield geothermometers indicating subsurface fluid temperatures of 130-140°C. Six temperature-gradient holes were drilled to target the extent of the shallow-temperature and geophysical anomalies to define the geothermal system in southeastern Gabbs Valley. Two wells contained high temperatures exceeding boiling with bottom-hole temperatures ii of 114.5°C and 124.9°C, respectively, and the remaining wells displayed elevated to background temperatures ranging from 79.2°C to 28.7°C. The observed temperature gradients for the two hottest drill holes necessitate drill-hole intercepts of convecting hydrothermal fluids. The 2-m survey is spatially and thermally consistent with the temperature-gradient holes and constrains the core of upflow at a shallow depth interval (<250m) to an area <0.5-1 km west-southwest of the hottest drill hole. The zone of inferred upwelling occupies the area corresponding to the center of the magnetic-low. This project has several significant implications. The newly discovered blind geothermal system in southeastern Gabbs Valley may be capable of supporting a binary-type geothermal power plant. This detailed study provides an initial validation of the play fairway approach to geothermal exploration. It also demonstrates both the broad applicability of the play fairway exploration strategy and the large untapped potential for commercial-grade blind geothermal systems in many of the basins in the Great Basin region.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Proposal and application of ROM-Lasso method for sensitivity coefficient evaluation

We propose a novel method for evaluating sensitivity coefficients of neutronics parameters to cross sections, so-called the reduced-order modeling technique ROM-Lasso. In this method, cross sections of interest are randomly sampled, and corresponding perturbed core analyses are performed. Then, the sensitivity coefficient vector of the higher-level model is expanded via the active subspace bases obtained with the lower-level model whose dimensional complexity is smaller than that of the higher-level model, and the expansion coefficients are estimated by the Lasso regression. A unique feature of the ROM-Lasso method allows the use of different bases optimized for each neutronics parameter. We conducted a verification calculation for an accelerator-driven system and demonstrated that the ROM-Lasso method can reproduce the sensitivity coefficients with a much smaller number of forward calculations than the direct method. The proposed method can be used to practically evaluate sensitivity coefficients. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Artificial neural networks estimate evapotranspiration for Miscanthus × giganteus as effectively as empirical model but with fewer inputs

Estimating actual evapotranspiration (ET) is particularly crucial for addressing how vegetation affects the water balance of ecosystems. ET estimation can be complex with empirical models due to their many parameters and reliance on aridity. In contrast, artificial neural networks (ANNs) could potentially estimate ET with fewer and more common meteorological parameters. In this study, we trained two ANNs, one using a feed-forward approach (FFN) and the other a nonlinear auto-regressive network (NARX), to predict ET and compared them to the commonly used empirical model Granger and Gray (GG). We trained our models on a nine-year eddy covariance (EC) dataset for Miscanthu s × giganteus ( M . × giganteus ) from Illinois (UIEF), then tested them using out-of-sample data from both UIEF and a different location in Iowa (SABR) to compare the accuracy of FFN, NARX, and GG models in estimating daily ET. A combination of air temperature (T a ) and solar radiation (R s ) was chosen as inputs due to the highest R 2 for FFN (R 2 = 0.79, 0.81, and 0.79 for training, testing, and validation, respectively) and only T a for NARX (R 2 = 0.70 for out-of-sample validation). The predictive power of the FFN model was superior to the NARX and GG models at the UIEF site (R 2 = 0.84, 0.70, and 0.83 for out-of-sample validation, respectively). Our analysis showed that ANN approaches are as accurate as empirical approaches for estimating ET but use fewer inputs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

PHOTOMETRIC REDSHIFTS FOR QUASARS IN MULTI-BAND SURVEYS

The Multi Layer Perceptron with Quasi Newton Algorithm (MLPQNA) is a machine learning method that can be used to cope with regression and classification problems on complex and massive data sets. In this paper, we give a formal description of the method and present the results of its application to the evaluation of photometric redshifts for quasars. The data set used for the experiment was obtained by merging four different surveys (Sloan Digital Sky Survey, GALEX, UKIDSS, and WISE), thus covering a wide range of wavelengths from the UV to the mid-infrared. The method is able (1) to achieve a very high accuracy, (2) to drastically reduce the number of outliers and catastrophic objects, and (3) to discriminate among parameters (or features) on the basis of their significance, so that the number of features used for training and analysis can be optimized in order to reduce both the computational demands and the effects of degeneracy. The best experiment, which makes use of a selected combination of parameters drawn from the four surveys, leads, in terms of {Delta}z{sub norm} (i.e., (z{sub spec} - z{sub phot})/(1 + z{sub spec})), to an average of {Delta}z{sub norm} = 0.004, a standard deviation of {sigma} = 0.069, and a median absolute deviation, MAD = 0.02, over the whole redshift range (i.e., z{sub spec} {<=} 3.6), defined by the four-survey cross-matched spectroscopic sample. The fraction of catastrophic outliers, i.e., of objects with photo-z deviating more than 2{sigma} from the spectroscopic value, is <3%, leading to {sigma} = 0.035 after their removal, over the same redshift range. The method is made available to the community through the DAMEWARE Web application.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Cadmium retention and distribution in contaminated soil: effects and interactions of soil properties, contamination level, aging time and in situ immobilization agents

As soil cadmium (Cd) contamination becomes a serious concern and one of the significant environmental pollution issues all over the world, knowledge of the basic chemistry, origin, inputs, sources, quantity, chemical forms, reactions, as well as the fate and transport of Cd in different types of soil is crucial for better understanding Cd bioavailability, health risks and remedial options. This study aimed to increase the current knowledge on the complex interdependence between the factors affecting behavior, transport and fate of Cd in the soil and to test and compare the performance of the stabilization agents in different soil types. Soils demonstrated various sorption affinity and capacity for Cd accumulation, which proved to be positively correlated with soil pH and the cation exchange capacity (CEC). With increasing levels of contamination, sequential extraction analysis showed the highest increase of relative Cd amounts in the exchangeable fraction regardless of the soil properties, suggesting that added Cd is principally associated with the easily accessible and mobile fraction. For different initial Cd concentrations and soil types, Cd sorption reached the quasi-equilibrium within 24 h of contact. Prolonged aging (two months) influenced the natural stabilization of Cd in all types of soil, but only at low contamination level. The application of both, conventional (slaked lime Ca(OH) 2) and alternative phosphate-rich (annealed bovine bones B 400) amendments, resulted in Cd relocation and reduction of exchangeable Cd content. Although the effect was smaller when apatite amendment was utilized, observed re-distribution of Cd to more stable soil fractions is preferable for achieving long-term stabilization. Cd concentrations extracted in exchangeable and acid soluble fractions after the treatments of contaminated soil samples suggest that the practical applicability of in situ immobilization depends on the soil properties and the level of contamination, as well as that effect, should be monitored for the possible re-mobilization of Cd. © 2019 Elsevier Inc.

02 PETROLEUM↗
DOE OSTI2015

Post-Growth Annealing of Bridgman-grown CdZnTe and CdMnTe Crystals for Room-temperature Nuclear Radiation Detectors

Bridgman-grown cadmium zinc telluride (CdZnTe or CZT) and cadmium manganese telluride (CdMnTe or CMT) crystals often have Te inclusions that limit their performances as X-ray- and gamma-ray-detectors. We present here the results of post-growth thermal annealing aimed at reducing and eliminating Te inclusions in them. In a 2D analysis, we observed that the sizes of the Te inclusions declined to 92% during a 60-h annealing of CZT at 510 °C under Cd vapor. Further, tellurium inclusions were eliminated completely in CMT samples annealed at 570 °C in Cd vapor for 26 h, whilst their electrical resistivity fell by an order of 10 2 . During the temperature-gradient annealing of CMT at 730 °C and an 18 °C/cm temperature gradient for 18 h in a vacuum of 10 -5 mbar, we observed the diffusion of Te from the sample, causing a reduction in size of the Te inclusions. For CZT samples annealed at 700 °C in a 10 °C/cm temperature gradient, we observed the migration of Te inclusions from a low-temperature region to a high one at 0.022 μm/s. During the temperature-gradient annealing of CZT in a vacuum of 10 -5 mbar at 570 °C and 30 °C/cm for 18 h, some Te inclusions moved toward the high-temperature side of the wafer, while other inclusions of the same size, i.e., 10 µm in diameter, remained in the same position. These results show that the migration, diffusion, and reaction of Te with Cd in the matrix of CZT- and CMT-wafers are complex phenomena that depend on certain conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Genome-resolved metaproteomic characterization of preterm infant gut microbiota development reveals species-specific metabolic shifts and variabilities during early life

Establishment of the human gut microbiota begins at birth. This early-life microbiota development can impact host physiology during infancy and even across an entire life span. But, the functional stability and population structure of the gut microbiota during initial colonization remain poorly understood. Metaproteomics is an emerging technology for the large-scale characterization of metabolic functions in complex microbial communities (gut microbiota). We applied a metagenome-informed metaproteomic approach to study the temporal and inter-individual differences of metabolic functions during microbial colonization of preterm human infants’ gut. By analyzing 30 individual fecal samples, we identified up to 12,568 protein groups for each of four infants, including both human and microbial proteins. With genome-resolved matched metagenomics, proteins were confidently identified at the species/strain level. The maximum percentage of the proteome detected for the abundant organisms was ~45%. A time-dependent increase in the relative abundance of microbial versus human proteins suggested increasing microbial colonization during the first few weeks of early life. We observed remarkable variations and temporal shifts in the relative protein abundances of each organism in these preterm gut communities. Given the dissimilarity of the communities, only 81 microbial EggNOG orthologous groups and 57 human proteins were observed across all samples. These conserved microbial proteins were involved in carbohydrate, energy, amino acid and nucleotide metabolism while conserved human proteins were related to immune response and mucosal maturation. We also identified seven proteome clusters for the communities and showed infant gut proteome profiles were unstable across time and not individual-specific. By applying a gut-specific metabolic module (GMM) analysis, we found that gut communities varied primarily in the contribution of nutrient (carbohydrates, lipids, and amino acids) utilization and short-chain fatty acid production. Overall, this study reports species-specific proteome profiles and metabolic functions of human gut microbiota during early colonization. In particular, our work contributes to reveal microbiota-associated shifts and variations in the metabolism of three major nutrient sources and short-chain fatty acid during colonization of preterm infant gut.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

STRIDES: a 3.9 per cent measurement of the Hubble constant from the strong lens system DES J0408−5354

We present a blind time-delay cosmographic analysis for the lens system DES J0408−5354. This system is extraordinary for the presence of two sets of multiple images at different redshifts, which provide the opportunity to obtain more information at the cost of increased modelling complexity with respect to previously analysed systems. We perform detailed modelling of the mass distribution for this lens system using three band Hubble Space Telescope imaging. We combine the measured time delays, line-of-sight central velocity dispersion of the deflector, and statistically constrained external convergence with our lens models to estimate two cosmological distances. We measure the ‘effective’ time-delay distance corresponding to the redshifts of the deflector and the lensed quasar |$D_{\Delta t}^{\rm eff}=$||$3382_{-115}^{+146}$| Mpc and the angular diameter distance to the deflector D_d = |$1711_{-280}^{+376}$| Mpc, with covariance between the two distances. From these constraints on the cosmological distances, we infer the Hubble constant H_0= |$74.2_{-3.0}^{+2.7}$| km s^−1 Mpc^−^1 assuming a flat ΛCDM cosmology and a uniform prior for Ω_m as |$\Omega _{\rm m} \sim \mathcal {U}(0.05, 0.5)$|⁠. This measurement gives the most precise constraint on H_0 to date from a single lens. Our measurement is consistent with that obtained from the previous sample of six lenses analysed by the H_0 Lenses in COSMOGRAIL’s Wellspring (H0LiCOW) collaboration. It is also consistent with measurements of H_0 based on the local distance ladder, reinforcing the tension with the inference from early Universe probes, for example, with 2.2σ discrepancy from the cosmic microwave background measurement.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Evaluating the Benefits of Bayesian Hierarchical Methods for Analyzing Heterogeneous Environmental Datasets: A Case Study of Marine Organic Carbon Fluxes

Large compilations of heterogeneous environmental observations are increasingly available as public databases, allowing researchers to test hypotheses across datasets. Statistical complexities arise when analyzing compiled data due to unbalanced spatial sampling, variable environmental context, mixed measurement techniques, and other reasons. Hierarchical Bayesian modeling is increasingly used in environmental science to describe these complexities, however few studies explicitly compare the utility of hierarchical Bayesian models to simpler and more commonly applied methods. Here we demonstrate the utility of the hierarchical Bayesian approach with application to a large compiled environmental dataset consisting of 5,741 marine vertical organic carbon flux observations from 407 sampling locations spanning eight biomes across the global ocean. We fit a global scale Bayesian hierarchical model that describes the vertical profile of organic carbon flux with depth. Profile parameters within a particular biome are assumed to share a common deviation from the global mean profile. Individual station-level parameters are then modeled as deviations from the common biome-level profile. The hierarchical approach is shown to have several benefits over simpler and more common data aggregation methods. First, the hierarchical approach avoids statistical complexities introduced due to unbalanced sampling and allows for flexible incorporation of spatial heterogeneitites in model parameters. Second, the hierarchical approach uses the whole dataset simultaneously to fit the model parameters which shares information across datasets and reduces the uncertainty up to 95% in individual profiles. Third, the Bayesian approach incorporates prior scientific information about model parameters; for example, the non-negativity of chemical concentrations or mass-balance, which we apply here. We explicitly quantify each of these properties in turn. We emphasize the generality of the hierarchical Bayesian approach for diverse environmental applications and its increasing feasibility for large datasets due to recent developments in Markov Chain Monte Carlo algorithms and easy-to-use high-level software implementations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

SU-E-J-163: A Biomechanical Lung Model for Respiratory Motion Study

Purpose: This work presents a biomechanical model to investigate the complex respiratory motion for the lung tumor tracking in radiosurgery by computer simulation. Methods: The models include networked massspring-dampers to describe the tumor motion, different types of surrogate signals, and the force generated by the diaphragm. Each mass-springdamper has the same mechanical structure and each model can have different numbers of mass-spring-dampers. Both linear and nonlinear stiffness parameters were considered, and the damping ratio was tuned in a range so that the tumor motion was over-damped (no natural tumor oscillation occurs without force from the diaphragm). The simulation was run by using ODE45 (ordinary differential equations by Runge-Kutta method) in MATLAB, and all time courses of motions and inputs (force) were generated and compared. Results: The curvature of the motion time courses around their peaks was sensitive to the damping ratio. Therefore, the damping ratio can be determined based on the clinical data of a high sampling rate. The peak values of different signals and the time the peaks occurred were compared, and it was found that the diaphragm force had a time lead over the tumor motion, and the lead time (0.1–0.4 seconds) depended on the distance between the tumor and the diaphragm. Conclusion: We reported a model based analysis approach for the spatial and temporal relation between the motion of the lung tumor and the surrogate signals. Due to the phase lead of the diaphragm in comparing with the lung tumor motion, the measurement of diaphragm motion (or its electromyography signal) can be used as a beam gating signal in radiosurgery, and it can also be an additional surrogate signal for better tumor motion tracking. The research is funded by the American Cancer Society (ACS) grant. The grant name is: Frameless SRS Based on Robotic Head Motion Cancellation. The grant number is: RSG-13-313-01-CCE.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Transition of Iodine Analysis to Accelerator Mass Spectrometry

The goal of the project, New Paradigms for Isotope Ratio Mass Spectrometry: Raising the Scientific Profile and Improved Performance for Accelerator Mass Spectrometry (AMS) and Thermal Ionization Mass Spectrometry (TIMS), is to ensure that the ongoing isotope ratio determination capability within the U.S. Department of Energy complex is the world’s best for application to nonproliferation. This report spells out the progress of Task 4, Transition of TIMS to AMS for Iodine Analysis, of the larger project. The subtasks under Task 4 and the accomplishments throughout the three year project life cycle are presented in this report. Progress was made in optimization of chemical extraction, determination of a detection limit for 127Iodine, production of standard materials for AMS analysis quality assurance, facilitation of knowledge exchange with respect to analyzing iodine on an AMS, cross comparison with a world-leading AMS laboratory, supercritical fluid extraction of iodine for AMS analysis and electrodeposition of seawater as a direct method of preparation for iodine analysis by AMS--all with the goal of minimizing the time required to stand up an AMS capability for iodine analysis of exposed air filters at INL. An effective extraction method has been developed and demonstrated for iodine analysis of exposed air filters. Innovative techniques to accomplish the cathode preparation for AMS analysis were developed and demonstrated and published. The known gap of a lack of available materials for reference standards in the analysis of iodine by AMS was filled by the preparation of homogenous materials that were calibrated against NIST materials. A minimum limit on the amount of abundant isotope in a sample was determined for AMS analysis. The knowledge exchange occurred with fantastic success. Scientists engaged the international AMS community at conferences, as well as in their laboratories for collaborative work. The supercritical fluid extraction work has positive data, but is not a replacement for leaching yet. The added seawater work has led to a good method and a possible publication. The focus of this project was to minimize the time to stand up the AMS capability, by having all the preparation and supporting functions worked out ahead of the instrument arrival. Due to all the preparatory work and its success, the instrument was delivered and turned over to the INL in February 2015. Since then, INL scientists have been successfully vetting the capabilities and accomplishing their own measurements that agree well with the leading laboratories of the world for iodine analysis by AMS. Initially, all AMS data was gathered on other laboratories instruments, but during the last six months data for this project has come from INL’s AMS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Thermal Conductivity Degradation in High Burnup U-Pu-Zr Fuel

Recent advancements in the characterization of irradiated U-Pu-Zr fuels have revealed complexities that challenge existing understanding of constituent redistribution. Traditionally, models have proposed three concentric regions within the fuel, each characterized by distinctive phases and porosity. However, through detailed analysis of high burnup U-Pu-Zr, we discovered the presence of four distinct constituent redistribution regions. Particularly novel is the observation of significant Pu redistribution, a previously unreported phenomenon that necessitates a reevaluation of current models. This work aims to delve deeper into these findings, seeking to correlate mesoscale measurements of thermal diffusivity and respective thermal conductivity with the phases present in each redistribution region. To achieve this objective, we employed mesoscale thermoreflectance methods using the unique, Idaho National Laboratory (INL) developed, Thermal Conductivity Microscope (TCM) at INL’s Irradiated Materials Characterization Laboratory. The TCM employs two tightly focused lasers: one for heating to generate periodic thermal waves in the substrate, and another spatially separated probe laser to detect changes in the optical reflectivity of the gold-coated substrate resulting from thermal wave diffusion. We conducted several thermal diffusivity measurements within each region of constituent redistribution of a U-19Pu-10Zr fuel pin cross section irradiated to 11 at. % burnup. The TCM measurement positions strategically aligned with transmission electron microscopy (TEM) lift-out locations previously collected from the fuel sample. Complementary microstructural analysis techniques such as optical and scanning electron microscopy (OM/SEM), electron probe microanalysis for chemical compositions, and TEM-based selective area electron diffraction (SAED) analysis for crystallographic insights into each phase were also utilized. This comprehensive approach allowed us to correlate local thermal diffusivity data with microstructural characteristics, enabling the computation of local thermal conductivity at each position. The significance of this contribution lies in its pioneering use of the TCM for ternary fuel mesoscale examination, shedding light on the previously overlooked effects of Pu redistribution on local thermal conductivity. By informing current models capturing constituent redistribution and heat transfer, our findings pave the way for more accurate predictions of metallic fuel performance. Moreover, this work sets the stage for future comparisons with similar TCM examinations on U-19Pu-10Zr fuels at ultra-low burnup, facilitating a comprehensive understanding of thermal property changes across different burnup levels. Ultimately, our study not only enriches our understanding of the thermophysical properties of individual redistribution regions within U-Pu-Zr fuel but also offers valuable insights for the design and operational parameters of proposed next-generation fast reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Establishing performance metrics for quantitative non-targeted analysis: a demonstration using per- and polyfluoroalkyl substances

Abstract Non-targeted analysis (NTA) is an increasingly popular technique for characterizing undefined chemical analytes. Generating quantitative NTA (qNTA) concentration estimates requires the use of training data from calibration “surrogates,” which can yield diminished predictive performance relative to targeted analysis. To evaluate performance differences between targeted and qNTA approaches, we defined new metrics that convey predictive accuracy, uncertainty (using 95% inverse confidence intervals), and reliability (the extent to which confidence intervals contain true values). We calculated and examined these newly defined metrics across five quantitative approaches applied to a mixture of 29 per- and polyfluoroalkyl substances (PFAS). The quantitative approaches spanned a traditional targeted design using chemical-specific calibration curves to a generalizable qNTA design using bootstrap-sampled calibration values from “global” chemical surrogates. As expected, the targeted approaches performed best, with major benefits realized from matched calibration curves and internal standard correction. In comparison to the benchmark targeted approach, the most generalizable qNTA approach (using “global” surrogates) showed a decrease in accuracy by a factor of ~4, an increase in uncertainty by a factor of ~1000, and a decrease in reliability by ~5%, on average. Using “expert-selected” surrogates ( n = 3) instead of “global” surrogates ( n = 25) for qNTA yielded improvements in predictive accuracy (by ~1.5×) and uncertainty (by ~70×) but at the cost of further-reduced reliability (by ~5%). Overall, our results illustrate the utility of qNTA approaches for a subclass of emerging contaminants and present a framework on which to develop new approaches for more complex use cases. Graphical Abstract

Pu, Shirley (ORCID:0000000201223797)↗
DOE OSTI2025

Rapid spatial analysis of surrogate TRISO fuel particles using laser-induced breakdown spectroscopy image analysis

Laser-induced breakdown spectroscopy (LIBS) mapping enables rapid elemental and spatial analysis of solid samples. In this work, surrogate TRi-structural ISOtropic (TRISO) particles with various layers consisting of Zr, W, C, and Si were used to demonstrate the use of a new thickness measurement tool developed to analyze elemental images generated from LIBS maps. Zr particles with varying outer-layer thicknesses ranging from 16 to 32 μm were measured with scanning electron microscopy with energy dispersive spectroscopy (SEM-EDS) and LIBS with both a complementary metal-oxide-semiconductor (CMOS) detector and an intensified charged coupled device (ICCD) detector. LIBS maps of particles were completed using CMOS and ICCD spectrometers with effective spatial resolutions of 4 and 2 μm, respectively. The novel thickness measurement tool identified layer regions within a LIBS map and then identified the locations of the boundaries between these layers. The tool then generated up to 1000 random profiles stemming radially from the center region, which were used to measure the layer thickness/radius. This image analysis tool demonstrated LIBS's ability to provide values comparable with SEM-EDS (3.7% relative difference) along with a 95% reduction in measurement time. Furthermore, the precision of these measurements was on par with the SEM-EDS measurements at <15% relative standard deviation. Following the analysis of the Zr particles, W particles with increased complexity (e.g., five versus three layers) were analyzed using both the CMOS and ICCD spectrometers simultaneously. The spatial dimensions were extracted with an average relative difference of 2.7% and an average relative standard deviation of 9%.

Andrews, Hunter B. [Oak Ridge National Laboratory ↗
DOE OSTI2024

Measuring thermomechanical response of large-format printed polymer composite structures via digital image correlation

Large-format additive manufacturing (LFAM) is a branch of additive manufacturing (AM) research with the ability to create large structures typically measuring several meters in scale. LFAM is advantageous for tooling applications, not only because it offers the ability to create complex geometries not easily made using subtractive manufacturing processes, but the cost savings of pelletized feedstock used by these systems result in larger parts printed at faster speeds than traditional AM systems. Fiber reinforced polymer (FRP) is a commonly used feedstock material in LFAM structures because it reduces the distortion experienced during printing. However, FRP introduces highly anisotropic thermomechanical properties and contributes to a nonhomogeneous microstructure that can result in critical distortion of dimensions during tooling. Measuring the global thermomechanical response of LFAM structures requires a more representative method that accounts for not only anisotropic properties but also the nonhomogeneous nature of the final part. This is where traditional techniques to measure thermomechanical response, such as thermomechanical analysis (TMA), fall short as they assume homogeneity. This study evaluated the coefficient of thermal expansion (CTE) of LFAM structures as measured by TMA as compared to a novel digital image correlation oven (DIC Oven) system. The LFAM structures were made from 20 % by weight carbon fiber reinforced acrylonitrile butadiene styrene (CF-ABS). TMA measurements showed significant variations in CTE across a single LFAM bead, confirming the need for a global technique that captures overall thermomechanical response. The CTE values measured using the DIC Oven compared well to average TMA values obtained from localized measurements across the sample. The DIC Oven was also used to quantify the effects of different layer orientations on thermomechanical properties, which cannot be easily captured using TMA. A predictive model was also developed by using localized TMA values across an LFAM bead to predict the overall thermomechanical response of an LFAM structure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Potassium isotopic fractionation in a humid and an arid soil–plant system in Hawai‘i

Plants play a critical role in the cycling of potassium (K) and the fractionation of its isotopes. However, little is known about K stable isotopic compositions in natural soil–plant systems and possible fractionation during intra-plant transport and root-soil uptake of K. Herein this study focuses on K isotopic fractionation within a humid and an arid soil–plant system sampled on the windward and leeward sides of Kohala Mountain, Hawai‘i. We determined the K isotopic compositions of < 2-mm bulk soil, soil saturation extraction, and selected plant tissues by multi-collector inductively coupled plasma mass spectrometry and X-ray absorption spectroscopy. We studied soils and individual tissue samples such as roots, stems, barks, shoots (a sum of stems and fresh leaves), leaves (fresh and dead), seeds, and flowers of trees and grasses. The results demonstrated that: (i) tissue δ 41 K values ranged from –1.06 ± 0.06 to 1.15 ± 0.09‰; (ii) within the same plant, stems (barks), dead leaves, and reproductive tissues (flowers and seeds) were isotopically lighter compared to fresh leaves, and to a lesser extent, roots; (iii) δ 41 K values of the humid soil (-0.54 ± 0.07 to –0.49 ± 0.06‰) were lower than those of the arid soil (-0.24 ± 0.07 to –0.14 ± 0.06‰); and (iv) soil bioavailable pool δ 41 K (saturation extracts) ranged from –0.63 ± 0.08 to 0.34 ± 0.08‰ and 0.48 ± 0.08 to 0.54 ± 0.10‰ in the humid and arid soils, respectively. From synchrotron-based analysis of K atoms, we identified two major K-bearing phases co-existing as ionic K + and K-pectate association of different fractions. Based on K isotopic and synchrotron data, we conclude that two dominant processes are responsible for plant-mediated K isotopic fractionation, including (1) K redistribution during intra-plant circulation and (2) uptake at the root-soil interface. For intra-plant circulation of K, there is a high affinity of isotopically lighter K to organic complexes as K-pectate, and K-pectate is particularly enriched in roots and fresh leaves. For K uptake at root-soil interface, isotopically lighter K is preferentially taken by roots from soil bioavailable pools following a low-affinity (passive) transport path. Soil K budget in two sites reflects strong source mixing effects with limited plant imprints. This work provides exploratory data on the biogeochemical fractionation of K isotopes in the soil–plant system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Surface-Functionalized Cellulose Nanocrystals as Nanofillers for Crosslinking Processes: Implications for Thermosetting Resins

Understanding the response of fillers in the epoxy resin crosslinking process and characterizing polymer–filler dynamics are the key features that guide the engineering of new thermosetting resin composites. Here, in this work, X-ray photon correlation spectroscopy (XPCS) is used as a thermal analysis tool to track the microscopic changes occurring during the cure of a functionalized cellulose nanocrystal (mCNC)–epoxy composite. In contrast, traditional methods such as differential scanning calorimetry (DSC) and curing rheology are used to understand the kinetics and properties on macroscopic length scales. Of interest is the influence of the mCNC on the curing kinetics and properties of the thermosetting resin. Two levels of modification (increasing hydrophobicity) were chosen to observe the effect of functionalization. Before cure, the highly functionalized CNC (mCNC3) shows a 44% increase in complex viscosity (η*), while the less functionalized CNC (mCNC2) shows a η* value similar to that of the neat resin. As the cure cycle progresses, results from DSC, rheology, and XPCS further show the enhancement in dispersion for mCNC3. The results show a clear difference in the maximum drift velocity, maximum heat flow, and complex viscosity during the ramp to the isothermal cure temperature (T cure ). Such results suggest that mCNC3 contains a well-dispersed network of particles due to the higher level of functionalization. During T cure , a transition in elastic modulus (G') occurs only for the highly functionalized CNC particle system. We believe that heat-induced aggregation occurs, and the crosslinked resin ultimately dominates the macroscopic properties of the final cured system for all samples. The results from the three techniques are in good agreement and showcase XPCS as a beneficial experimental tool for characterizing the microscopic dynamics of particulate-filled thermosetting resins. Hence, we envision this to be a fundamental curing study for the design of thermosetting resin composites.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Does the leaf economic spectrum hold within plant functional types? A Bayesian multivariate trait meta-analysis

The leaf economic spectrum is a widely-studied axis of plant trait variability that defines a trade-off between leaf longevity and productivity. While this has been investigated at the global scale, where it is robust, and at local scales, where deviations from it are common, it has received less attention at the intermediate scale of PFTs. We investigated whether global leaf economic relationships are also present within the scale of plant functional types (PFTs) commonly used by Earth System models, and the extent to which this global-PFT hierarchy can be used to constrain trait estimates. We developed a hierarchical multivariate Bayesian model that assumes separate means and covariance structures within and across PFTs and fit this model to seven leaf traits from the TRY database related to leaf longevity, morphology, biochemistry, and photosynthetic metabolism. Although patterns of trait covariation were generally consistent with the leaf economic spectrum, we found three approximate tiers to this consistency. Relationships among morphological and biochemical traits (SLA, N, P) were the most robust within and across PFTs, suggesting that covariation in these traits is driven by universal leaf construction trade-offs and stoichiometry. Relationships among metabolic traits (R_d, V_{c,max}, J_max) were slightly less consistent, reflecting in part their much sparser sampling (especially for high-latitude PFTs), but also pointing to more flexible plasticity in plant metabolistm. Finally, relationships involving leaf lifespan were the least consistent, indicating that leaf economic relationships related to leaf lifespan are dominated by across-PFT differences and that within-PFT variation in leaf lifespan is more complex and idiosyncratic. Across all traits, these covariance were an important source of information, as evidenced by the improved imputation accuracy and reduced predictive uncertainty in multivariate models compared to univariate models. Ultimately, our study reaffirms the value of studying not just individual traits but the multivariate trait space and the utility of hierarchical modeling for studying the scale dependence of trait relationships.

biodiversity, ecological modeling, ecology, leaf b↗