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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Temperature-Dependent Solubility of Solid Electrolyte Interphase on Silicon Electrodes

The lithium-ion batteries powering mass market electric vehicles must be capable of operating in a wide temperature range. Temperature variation has the possibility to greatly affect the stability of the solid electrolyte interphase (SEI) responsible for mitigating capacity fade due to electrolyte decomposition in the lithium-ion battery. Here, we explore the solubility of the SEI on the silicon (Si) electrode, an alternative anode material to the conventional graphite electrode, at temperatures ranging from -10 to 50 °C. Through use of an electrochemical protocol with a high cathodic cutoff voltage, we measure the evolution of the SEI independently of competing Si mechanical stress. We correlate the electrochemical data with three-dimensional resistivity versus depth profiling as well as atomic force microscopy to show that SEI dissolution occurs at significantly faster rates at higher temperatures.

25 ENERGY STORAGE↗
DOE OSTI2026

Confined Room-Temperature Ferromagnetism in Kagome (Fe 3 Sn 2 /CoSn) Superlattices

We reveal the presence of robust ferromagnetism in topological kagome (Fe 3 Sn 2 /CoSn) ×n superlattices via polarized neutron reflectivity (PNR) and magnetization measurements. Using molecular beam epitaxy, we have synthesized superlattices of alternating ferromagnetic Fe 3 Sn 2 and paramagnetic CoSn layers, the interfacial integrity of which is confirmed using scanning transmission electron microscopy. Magnetization depth profiles, obtained by fitting the PNR data, confirm the presence of ferromagnetism in the confined Fe 3 Sn 2 layers at room temperature, with minimal thickness dependence down to 2 nm. A net magnetization is found in the near-surface region of CoSn, which we attribute to surface oxidation. Our results demonstrate that superlattice engineering is a means to confine ferromagnetism in kagome metals, enabling future studies of thickness-dependent anomalous Hall and Nernst effects as well as spin-dependent transport and tunneling in device structures.

kagome metals↗
DOE OSTI2024

Upscaling Soil Organic Carbon Measurements at the Continental Scale Using Multivariate Clustering Analysis and Machine Learning

Abstract Estimates of soil organic carbon (SOC) stocks are essential for many environmental applications. However, significant inconsistencies exist in SOC stock estimates for the U.S. across current SOC maps. We propose a framework that combines unsupervised multivariate geographic clustering (MGC) and supervised Random Forests regression, improving SOC maps by capturing heterogeneous relationships with SOC drivers. We first used MGC to divide the U.S. into 20 SOC regions based on the similarity of covariates (soil biogeochemical, bioclimatic, biological, and physiographic variables). Subsequently, separate Random Forests models were trained for each SOC region, utilizing environmental covariates and SOC observations. Our estimated SOC stocks for the U.S. (52.6 ± 3.2 Pg for 0–30 cm and 108.3 ± 8.2 Pg for 0–100 cm depth) were within the range estimated by existing products like Harmonized World Soil Database, HWSD (46.7 Pg for 0–30 cm and 90.7 Pg for 0–100 cm depth) and SoilGrids 2.0 (45.7 Pg for 0–30 cm and 133.0 Pg for 0–100 cm depth). However, independent validation with soil profile data from the National Ecological Observatory Network showed that our approach ( R 2 = 0.51) outperformed the estimates obtained from Harmonized World Soil Database ( R 2 = 0.23) and SoilGrids 2.0 ( R 2 = 0.39) for the topsoil (0–30 cm). Uncertainty analysis (e.g., low representativeness and high coefficients of variation) identified regions requiring more measurements, such as Alaska and the deserts of the U.S. Southwest. Our approach effectively captures the heterogeneous relationships between widely available predictors and the current SOC baseline across regions, offering reliable SOC estimates at 1 km resolution for benchmarking Earth system models.

58 GEOSCIENCES↗
DOE OSTI2018

Tropical peatland carbon storage linked to global latitudinal trends in peat recalcitrance

Peatlands represent large terrestrial carbon banks. Given that most peat accumulates in boreal regions, where low temperatures and water saturation preserve organic matter, the existence of peat in (sub)tropical regions remains enigmatic. Here we examined peat and plant chemistry across a latitudinal transect from the Arctic to the tropics. Near-surface low-latitude peat has lower carbohydrate and greater aromatic content than near-surface high-latitude peat, creating a reduced oxidation state and resulting recalcitrance. This recalcitrance allows peat to persist in the (sub)tropics despite warm temperatures. Because we observed similar declines in carbohydrate content with depth in high-latitude peat, our data explain recent field-scale deep peat warming experiments in which catotelm (deeper) peat remained stable despite temperature increases up to 9 °C. We suggest that high-latitude deep peat reservoirs may be stabilized in the face of climate change by their ultimately lower carbohydrate and higher aromatic composition, similar to tropical peats.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Unified field studies of the algae testbed public-private partnership as the benchmark for algae agronomics

National scale agronomic projections are an important input for assessing potential benefits of algae cultivation on the future of innovative agriculture. The Algae Testbed Public-Private Partnership was established with the goal of investigating open pond algae cultivation across different geographic, climatic, seasonal, and operational conditions while setting the benchmark for quality data collection, analysis, and dissemination. Identical algae cultivation systems and data analysis methodologies were established at testbed sites across the continental United States and Hawaii. Within this framework, the Unified Field Studies were designed for algae cultivation during all 4 seasons across the testbed network. With increasingly diverse algae research and development, and field deployment strategies, the challenges associated with data collection, quality, and dissemination increase dramatically. The dataset presented here is the complete, curated, climatic, cultivation, harvest, and biomass composition data for each season at each site. Furthermore, these data enable others to do in-depth cultivation, harvest, techno-economic, life cycle, resource, and predictive growth modelling analysis, as well as development of crop protection strategies throughout the algae cultivation industry.

09 BIOMASS FUELS↗
DOE OSTI2015

Neutrino masses and cosmology with Lyman-alpha forest power spectrum

We present constraints on neutrino masses, the primordial fluctuation spectrum from inflation, and other parameters of the ΛCDM model, using the one-dimensional Lyα-forest power spectrum measured by [1] from the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey (SDSS-III), complemented by Planck 2015 cosmic microwave background (CMB) data and other cosmological probes. This paper improves on the previous analysis by [2] by using a more powerful set of calibrating hydrodynamical simulations that reduces uncertainties associated with resolution and box size, by adopting a more flexible set of nuisance parameters for describing the evolution of the intergalactic medium, by including additional freedom to account for systematic uncertainties, and by using Planck 2015 constraints in place of Planck 2013. Fitting Lyα data alone leads to cosmological parameters in excellent agreement with the values derived independently from CMB data, except for a weak tension on the scalar index n{sub s}. Combining BOSS Lyα with Planck CMB constrains the sum of neutrino masses to ∑ m{sub ν} < 0.12 eV (95% C.L.) including all identified systematic uncertainties, tighter than our previous limit (0.15 eV) and more robust. Adding Lyα data to CMB data reduces the uncertainties on the optical depth to reionization τ, through the correlation of τ with σ{sub 8}. Similarly, correlations between cosmological parameters help in constraining the tensor-to-scalar ratio of primordial fluctuations r. The tension on n{sub s} can be accommodated by allowing for a running dn{sub s}/d ln k. Allowing running as a free parameter in the fits does not change the limit on ∑ m{sub ν}. We discuss possible interpretations of these results in the context of slow-roll inflation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Estimating fluid-induced stress change from observed deformation

Observed deformation is sensitive to a changing stress field within the Earth. There are, however, several impediments to a direct inversion of geodetic measurements for changes in stress. Estimating six independent components of stress change from a smaller number of displacement or strain components is inherently non-unique. The reliance upon surface measurements leads to a loss of resolution, due to the attenuation of higher spatial frequencies in the displacement field with distance from a source. Here, we adopt a technique suited to the estimation of stress changes due to the injection and/or withdrawal of fluids at depth. In this approach the surface displacement data provides an estimate of the volume change responsible for the deformation, rather than stress changes themselves. The inversion for volume change is constrained by the fluid fluxes into and out of the reservoir. The distribution of volume change is used to calculate the displacements in the region above the reservoir. Estimates of stress change follow from differentiating the displacement field in conjunction with a geomechanical model of the o verburden. We also apply the technique to Interferometric Synthetic Aperture Radar (InSAR) observations gathered over a petroleum reservoir in the San Joaquin Valley of California. An analysis of the InSAR range changes reveals that the stress field in the overburden varies rapidly both in space and in time. The inferred stress variations are found to be compatible with the documented failure of a well in the field.

58 GEOSCIENCES↗
DOE OSTI2015

Lattice stability and high-pressure melting mechanism of dense hydrogen up to 1.5 TPa

Lattice stability and metastability, as well as melting, are vital features of the physics and chemistry of dense hydrogen. Using ab initio molecular dynamics (AIMD), the classical superheating limit and melting line of metallic hydrogen are investigated up to 1.5 TPa. The computations show that the classical superheating degree is about 100 K, and the classical melting curve becomes flat at a level of 350 K when beyond 500 GPa. This data allows us to estimate the well depth and the potential barriers that must be overcome when the crystal melts. Inclusion of nuclear quantum effects (NQE) using path integral molecular dynamics (PIMD) predicts that both superheating limit and melting temperature are lowered to below room temperature, but the latter never reaches absolute zero. Detailed analysis indicates that the melting is thermally activated, rather than driven by pure zero-point motion (ZPM). This argument was further supported by extensive PIMD simulations, demonstrating the stability of Fddd structure against liquefaction at low temperatures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Field Test of Enhanced Remedial Amendment Delivery Using a Shear-Thinning Fluid

Heterogeneity of hydraulic properties in aquifers may lead to contaminants residing in lower-permeability zones where it is difficult to deliver remediation amendments using conventional injection processes. The focus of this effort is to examine use of a shear-thinning fluid (STF) to improve the uniformity of remedial amendment distribution within a heterogeneous aquifer. Previous studies have demonstrated the significant potential of STFs for improving remedial amendment delivery in heterogeneous aquifers, but quantitative evaluation of these improvements from field applications are lacking. A field-scale test was conducted that compares data from successive injection of a tracer in water followed by injection of a tracer in a STF to evaluate the impact of the STF on tracer distribution uniformity in the presence of permeability contrasts within the targeted injection zone. Data from tracer breakthrough at multiple depth-discrete monitoring intervals and electrical resistivity tomography showed that inclusion of STF in the injection solution slowed movement in high-permeability pathways, improved delivery of amendment to low-permeability materials, and resulted in better uniformity in injected fluid distribution within the targeted treatment zone.

bioremediation, groundwater↗
DOE OSTI2022

Photometric Redshifts for Next-Generation Surveys

Photometric redshifts are essential in studies of both galaxy evolution and cosmology, as they enable analyses of objects too numerous or faint for spectroscopy. The Rubin Observatory, Euclid, and Roman Space Telescope will soon provide a new generation of imaging surveys with unprecedented area coverage, wavelength range, and depth. To take full advantage of these data sets, further progress in photometric redshift methods is needed. In this review, we focus on the greatest common challenges and prospects for improvement in applications of photometric redshifts to the next generation of surveys: ∙ Gains in performance (i.e., the precision of redshift estimates for individual galaxies) could greatly enhance studies of galaxy evolution and some probes of cosmology. ∙ Improvements in characterization (i.e., the accurate recovery of redshift distributions of galaxies in the presence of uncertainty on individual redshifts) are urgently needed for cosmological measurements with next-generation surveys. To achieve both of these goals, improvements in the scope and treatment of the samples of spectroscopic redshifts that make high-fidelity photometric redshifts possible will also be needed. For the full potential of the next generation of surveys to be reached, the characterization of redshift distributions must improve by roughly an order of magnitude compared with the current state of the art, requiring progress on a wide variety of fronts. We conclude by presenting a speculative evaluation of how photometric redshift methods and the collection of the necessary spectroscopic samples may improve by the time near-future surveys are completed.

Astronomy & Astrophysics↗
DOE OSTI2018

Nevada Play Fairway - Steptoe Valley Geodatabase and Modeling Data

This package contains data and metadata for the 3d thermal model, well lithology logs, gravity grids and depth to basement inversions, play fairway modelling, and ArcGIS geodatabase resources. This project focused on defining geothermal play fairways and development of a detailed geothermal potential map of a large transect across the Great Basin region (96,000 km2), with the primary objective of facilitating discovery of commercial-grade, blind geothermal fields (i.e. systems with no surface hot springs or fumaroles) and thereby accelerating geothermal development in this promising region.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Emrgy 2022 Hydrokinetic Turbine Data - TEAMER Post Access Submission

The data herein contains all data collected and used for the Performance Characterization Testing and Model Calibration of a Vertical Axis Hydrokinetic Turbine. The data includes performance data and durability data for the Hydrokinetic Turbine. The device performance data contains shaft RPM, turbine RPM, power output, flow velocity, pressure, and pressure drop across the turbine. The mechanical durability data includes stress and strain at varied depths and velocities. There is also an FEA analysis included. This TEAMER project was awarded to Emrgy, Inc.in collaboration with Alden Research Laboratory LLC.

16 TIDAL AND WAVE POWER↗
DOE OSTI2017

Validation of Material Models For Automotive Carbon Fiber Composite Structures Via Physical And Crash Testing (VMM Composites Project)

As automotive fuel economy requirements increase, the push for reducing overall vehicle weight will likely include the consideration of materials that have not previously been part of mainstream vehicle design and manufacturing, including carbon fiber composites. Vehicle manufacturers currently rely on computer-aided engineering (CAE) methods as part of the design and development process, so going forward, the ability to accurately and predictably model carbon fiber composites will be necessary. If composites are to be used for structural components, this need applies to both, crash and quasi-static modeling. This final report covers the results of a five-year, $6.89M, 50% cost-shared research project between Department of Energy (DOE) and the US Advanced Materials Partnership (USAMP) under Cooperative Agreement DE-EE-0005661 known as “Validation of Material Models for Automotive Carbon Fiber Composite Structures Via Physical and Crash Testing (VMM).” The objective of the VMM Composites Project was to validate and assess the ability of physics-based material models to predict crash performance of automotive primary load-carrying carbon fiber composite structures. Simulation material models that were evaluated included micro-mechanics based meso-scale models developed by the University of Michigan (UM) and micro-plane models by Northwestern University (NWU) under previous collaborations with the DOE and Automotive Composites Consortium/USAMP, as well as five commercial crash codes: LS-DYNA, RADIOSS, VPS/PAM-CRASH, Abaqus, and GENOA-MCQ. CAE predictions obtained from seven organizations were compared with experimental results from quasi-static testing and dynamic crash testing of a thermoset carbon fiber composite front-bumper and crush-can (FBCC) system gathered under multiple loading conditions. This FBCC design was developed to demonstrate progressive crush, virtual simulation, tooling, fabrication, assembly, non-destructive evaluation and crash testing advances in order to assess the correlation of the predicted results to the physical tests. The FBCC was developed to meet a goal of 30-35% mass reduction while aiming for equivalent energy absorption as a steel component for which baseline experimental results were obtained from testing in the same crash modes. The project also evaluated crash performance of thermoplastic composite structures fabricated from commercial prepreg materials and low cost carbon fiber sourced from Oak Ridge National Laboratory. The VMM Project determined that no set of predictions from a CAE supplier were found to be universally accurate among all the six crash modes evaluated. In general, crash modes that were most dependent on the properties of the prepreg were more accurate than those that were dependent on the behavior of the joints. The project found that current CAE modeling methods or best practices for carbon fiber composites have not achieved standardization, and accuracy of CAE is highly reliant on the experience of its users. Coupon tests alone are not sufficient to develop an accurate material model, but it is necessary to bridge the gap between the coupon data and performance of the actual structure with a series of subcomponent level tests. Much of the unreliability of the predictions can be attributed to shortcomings in our ability to mathematically link the effects of manufacturing and material variability into the material models. This is a subject of ongoing research in the industry. The final report is organized by key technical tasks to describe how the validation project developed, modeled and compared crash data obtained on the composite FBCC to the multiple sets of CAE predictions. Highlights of the report include a discussion of the quantitative comparison between predictions and experimental data, as well as an in-depth discussion of remaining technological gaps that exist in the industry, which are intended to spur innovations and improvements in CAE technology.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Modeling Nondestructive Defect Detection in Additively Manufactured Metallic Structures for Nuclear Applications

The future of quickly, economically produced metallic nuclear reactor parts with minimal supply-chain dependence lies in Laser Powder Bed Fusion (LPBF) Additive Manufacturing (AM): a 3D printing method involving laser melting and net shaping stainless steel and Inconel metallic powder into a solid structure. However, intrinsic features in LPBF frequently leads to the formation of materials defects, such as pores, within 3D printed structures. As safe long-term use in energy applications requires knowledge of all relevant defects before deployment in a reactor, we must develop methods for nondestructive detection of these defects. We are investigating Pulsed Thermal Tomography (PTT), which is a non-contact nondestructive imaging method scalable to arbitrary structure size. Thermal tomography (TT) is a computational method for 3D spatial reconstruction of material thermal effusivity from flash or pulsed thermography temperature data cube. Thermography data cube consists of 2D surface temperature measurements at different times. The objective of the present work is to investigate limits on defect detection in AM metallic structures with PTT. To this effect, we modeled PTT with COMSOL heat transfer computer simulations. We developed a layered media COMSOL simulation consisting of a Stainless Steel 316 (SS316) plate with an internal layer of un-sintered SS316 powder. Thermophysical properties of the powder layer were modeled with equivalent volume mixing model. To account for partial sintering at the boundary of the defect, the transition between solid and powder layers was modeled as a Gaussian. Using data from COMSOL simulations, we reconstructed depth-dependent thermal effusivity, which allowed defect visibility estimation. A series of parametric studies determined that at 1mm depth, 50µm is the smallest detectable defect. In addition, classification of the defects which can lead to early fatigue of the metallic structure in a reactor is briefly discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Integration of Soft Data Into Geostatistical Simulation of Categorical Variables

Uncertain or indirect “soft” data, such as geologic interpretation, driller’s logs, geophysical logs or imaging, offer potential constraints or “soft conditioning” to stochastic models of discrete categorical subsurface variables in hydrogeology such as hydrofacies. Previous bivariate geostatistical simulation algorithms have not fully addressed the impact of data uncertainty in formulation of the (co) kriging equations and the objective function in simulated annealing (or quenching). This paper introduces the geostatistical simulation code tsim-s, which accounts for categorical data uncertainty through a data “hardness” parameter. In generating geostatistical realizations with tsim-s, the uncertainty inherent to soft conditioning is factored into both 1) the data declustering and spatial correlation functions in cokriging and 2) the acceptance probability for change of category in simulated quenching. The degree or sensitivity to which soft data conditions a realization as a function of hardness can be quantified by mapping category probabilities derived from multiple realizations. In addition to point or borehole data, arrays of data (e.g., as derived from a depth-dependency function, probability map, or “prior realization”) can be used as soft conditioning. The tsim-s algorithm provides a theoretically sound and general framework for integrating datasets of variable location, resolution, and uncertainty into geostatistical simulation of categorical variables. A practical example shows how tsim-s is capable of generating a large-scale three-dimensional simulation including curvilinear features.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

NifH -Harboring Bacterial Community Composition across an Alaskan Permafrost Thaw Gradient

Since nitrogen (N) is often limiting in permafrost soils, we investigated the N 2 -fixing genetic potential and the inferred taxa harboring those genes by sequencing nifH gene fragments in samples taken along a permafrost thaw gradient in an Alaskan boreal soil. Samples from minimally, moderately and extensively thawed sites were taken to a depth of 79 cm to encompass zones above and below the depth of the water table. NifH reads were translated with frameshift correction and 112,476 sequences were clustered at 5% amino acid dissimilarity resulting in 1,631 OTUs. Sample depth in relation to water table depth was correlated to differences in the NifH sequence classes with those most closely related to group I nifH -harboring Alpha- and Beta-Proteobacteria in higher abundance above water table depth while those related to group III nifH -harboring Delta Proteobacteria more abundant below. The most dominant below water table depth NifH sequences, comprising 1/3 of the total, were distantly related to Verrucomicrobia-Opitutaceae . Overall, these results suggest that permafrost thaw alters the class-level composition of N 2 -fixing communities in the thawed soil layers and that this distinction corresponds to the depth of the water table. These nifH data were also compared to nifH sequences obtained from a study at an Alaskan taiga site, and to those of other geographically distant, non-permafrost sites. The two Alaska sites were differentiated largely by changes in relative abundances of the same OTUs, whereas the non-Alaska sites were differentiated by the lack of many Alaskan OTUs, and the presence of unique halophilic, sulfate- and iron-reducing taxa in the Alaska sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

AN ADJOINT-BASED METHOD FOR THE INVERSION OF THE JUNO AND CASSINI GRAVITY MEASUREMENTS INTO WIND FIELDS

During 2016–17, the Juno and Cassini spacecraft will both perform close eccentric orbits of Jupiter and Saturn, respectively, obtaining high-precision gravity measurements for these planets. These data will be used to estimate the depth of the observed surface flows on these planets. All models to date, relating the winds to the gravity field, have been in the forward direction, thus only allowing the calculation of the gravity field from given wind models. However, there is a need to do the inverse problem since the new observations will be of the gravity field. Here, an inverse dynamical model is developed to relate the expected measurable gravity field, to perturbations of the density and wind fields, and therefore to the observed cloud-level winds. In order to invert the gravity field into the 3D circulation, an adjoint model is constructed for the dynamical model, thus allowing backward integration. This tool is used for the examination of various scenarios, simulating cases in which the depth of the wind depends on latitude. We show that it is possible to use the gravity measurements to derive the depth of the winds, both on Jupiter and Saturn, also taking into account measurement errors. Calculating the solution uncertainties, we show that the wind depth can be determined more precisely in the low-to-mid-latitudes. In addition, the gravitational moments are found to be particularly sensitive to flows at the equatorial intermediate depths. Therefore, we expect that if deep winds exist on these planets they will have a measurable signature by Juno and Cassini.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Recovering Interstellar Gas Properties with Hi Spectral Lines: A Comparison between Synthetic Spectra and 21-SPONGE

We analyze synthetic neutral hydrogen (H i) absorption and emission spectral lines from a high-resolution, three-dimensional hydrodynamical simulation to quantify how well observational methods recover the physical properties of interstellar gas. We present a new method for uniformly decomposing H i spectral lines and estimating the properties of associated gas using the Autonomous Gaussian Decomposition (AGD) algorithm. We find that H i spectral lines recover physical structures in the simulation with excellent completeness at high Galactic latitude, and this completeness declines with decreasing latitude due to strong velocity-blending of spectral lines. The temperature and column density inferred from our decomposition and radiative transfer method agree with the simulated values within a factor of <2 for the majority of gas structures. We next compare synthetic spectra with observations from the 21-SPONGE survey at the Karl G. Jansky Very Large Array using AGD. We find more components per line of sight in 21-SPONGE than in synthetic spectra, which reflects insufficient simulated gas scale heights and the limitations of local box simulations. In addition, we find a significant population of low-optical depth, broad absorption components in the synthetic data which are not seen in 21-SPONGE. This population is not obvious in integrated or per-channel diagnostics, and reflects the benefit of studying velocity-resolved components. The discrepant components correspond to the highest spin temperatures (1000<T{sub s}<4000 K), which are not seen in 21-SPONGE despite sufficient observational sensitivity. We demonstrate that our analysis method is a powerful tool for diagnosing neutral interstellar medium conditions, and future work is needed to improve observational statistics and implementation of simulated physics.

79 ASTRONOMY AND ASTROPHYSICS↗