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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Persistent compositions of non-stoichiometric compounds with low bulk diffusivity: A theory and application to Nb3Sn superconductors

Non-stoichiometric compounds may develop a composition gradient when they are formed by reactive diffusional processes. This paper reports an interesting phenomenon that in compounds with low bulk diffusivities, which rely mainly on grain boundary diffusion for their growth, the final bulk compositions may be far from equilibrium, with a very low bulk diffusivity leading to fixed (persistent) compositions – one such example is Nb 3 Sn, a superconductor. We investigated the microchemistry at the reactive interface using atom probe tomography to clarify the diffusion reaction mechanism for this low-bulk-diffusivity case and thus propose a theory for what determines the compound composition, using Nb 3 Sn as an example for concreteness. Using certain approximations, we derive an explicit analytical equation that illustrates what factors determine its composition profile. We compare our model with the known facts of Nb 3 Sn and see good agreement. In particular, this model predicts that internal oxidation may lead to higher Sn contents than conventional, non-oxidized Nb 3 Sn. Our measurements show that this is indeed true, and that the internally-oxidized Nb 3 Sn also has higher upper critical fields, achieving up to 28.2 T at 4.2 K. We discuss the general applicability of this model to non-stoichiometric compounds with low bulk diffusivity, and propose it as a tool to help in the design and processing of such materials for compositional control.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Efficient reactive Brownian dynamics

We develop a Split Reactive Brownian Dynamics (SRBD) algorithm for particle simulations of reaction-diffusion systems based on the Doi or volume reactivity model, in which pairs of particles react with a specified Poisson rate if they are closer than a chosen reactive distance. In our Doi model, we ensure that the microscopic reaction rules for various association and dissociation reactions are consistent with detailed balance (time reversibility) at thermodynamic equilibrium. The SRBD algorithm uses Strang splitting in time to separate reaction and diffusion and solves both the diffusion-only and reaction-only subproblems exactly, even at high packing densities. To efficiently process reactions without uncontrolled approximations, SRBD employs an event-driven algorithm that processes reactions in a time-ordered sequence over the duration of the time step. A grid of cells with size larger than all of the reactive distances is used to schedule and process the reactions, but unlike traditional grid-based methods such as reaction-diffusion master equation algorithms, the results of SRBD are statistically independent of the size of the grid used to accelerate the processing of reactions. We use the SRBD algorithm to compute the effective macroscopic reaction rate for both reaction-limited and diffusion-limited irreversible association in three dimensions and compare to existing theoretical predictions at low and moderate densities. We also study long-time tails in the time correlation functions for reversible association at thermodynamic equilibrium and compare to recent theoretical predictions. Finally, we compare different particle and continuum methods on a model exhibiting a Turing-like instability and pattern formation. Our studies reinforce the common finding that microscopic mechanisms and correlations matter for diffusion-limited systems, making continuum and even mesoscopic modeling of such systems difficult or impossible. We also find that for models in which particles diffuse off lattice, such as the Doi model, reactions lead to a spurious enhancement of the effective diffusion coefficients.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Synchrotron x-ray study of a low roughness and high efficiency K 2 CsSb photocathode during film growth

Reduction of roughness to the nm level is critical of achieving the ultimate performance from photocathodes used in high gradient fields. The thrust of this paper is to explore the evolution of roughness during sequential growth, and to show that deposition of multilayer structures consisting of very thin reacted layers results in an nm level smooth photocathode. Synchrotron x-ray methods were applied to study the multi-step growth process of a high efficiency K 2 CsSb photocathode. We observed a transition point of the Sb film grown on Si at the film thickness of similar to 40 angstrom with the substrate temperature at 100 degrees C and the growth rate at 0.1 Å s -1 . The final K 2 CsSb photocathode exhibits a thickness of around five times that of the total deposited Sb film regardless of how the Sb film was grown. The film surface roughening process occurs first at the step when K diffuses into the crystalline Sb. Furthermore, the photocathode we obtained from the multi-step growth exhibits roughness in an order of magnitude lower than the normal sequential process. X-ray diffraction measurements show that the material goes through two structural changes of the crystalline phase during formation, from crystalline Sb to K 3 Sb and finally to K 2 CsSb.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Selenium infiltrated hierarchical hollow carbon spheres display rapid kinetics and extended cycling as lithium metal battery (LMB) cathodes

Lithium metal–selenium (Li–Se) batteries offer high volumetric energy but are limited in their cycling life and fast charge characteristics. Here a facile approach is demonstrated to synthesize hierarchically porous hollow carbon spheres that host Se (Se@HHCS) and allow for state-of-the-art electrochemical performance in a standard carbonate electrolyte (1 M LiPF 6 in 1:1 EC:DEC). The Se@HHCS electrodes display among the most favorable fast charge and cycling behavior reported. For example, they deliver specific capacities of 442 and 357 mA h g -1 after 1500 and 2000 cycles at 5C and 10C, respectively. At 2C, Se@HHCS delivers 558 mA h g -1 after 500 cycles, with cycling coulombic efficiency of 99.9%. Post-mortem microstructural analysis indicates that the structures remain intact during extended cycling. Per GITT analysis, Se@HHCS possesses significantly higher diffusion coefficients in both lithiation and delithiation processes as compared to the baseline. Furthermore, the superior performance of Se@HHCS is directly linked to its macroscopic and nanoscale pore structure: the hollow carbon sphere morphology as well as the remnant open nanoporosity accommodates the 69% volume expansion of the Li to Li 2 Se transformation, with the nanopores also providing a complementary fast ion diffusion path.

25 ENERGY STORAGE↗
DOE OSTI2019

Influence of non-solvent chemistry on polybenzimidazole hollow fiber membrane preparation

Polybenzimidazole membrane materials have attractive H 2 /CO 2 separation characteristics and high thermo-chemical stability for elevated temperature synthesis (syn) gas separations. The development of PBI membranes with a thin defect-free selective layer and porous support morphology is vital to achieving industrially attractive separation performance. This work is focused on developing a fundamental understanding of the liquid-liquid demixing-based phase inversion process for asymmetric PBI hollow fiber membrane (HFM) formation. The development of industrially attractive HFMs is a challenging process due to the complex interplay between phase equilibria, phase inversion kinetics, and interfacial mass transfer that exist during the liquid-liquid demixing process. Numerous parameters including the dope, bore, and outer coagulant chemistries and compositions significantly influence the HFM morphologies produced. Here, a systematic study is conducted to investigate the phase inversion process parameters including the roles of the non-solvent solubility and diffusivity parameters with respect to the solvent and PBI on the phase inversion process. Furthermore, the influence of dope, bore and coagulant chemistries and compositions on PBI HFM morphology are investigated. As a result, the fabricated PBI HFMs are evaluated for their ideal H 2 and CO 2 permeance and H 2 /CO 2 selectivity at 250 °C to benchmark their separation performance.

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

Morphology–Diffusivity Relationships in Fluorine-Free Random Terpolymers for Proton-Exchange Membranes

Here, using atomistic molecular dynamics simulations, we investigate the morphology and transport properties of a new family of fluorine-free terpolymers designed as proton-exchange membranes. Simulated random terpolymers consist of three monomers with a 5-carbon backbone with a phenylsulfonate, phenyl, or no pendant group and have ion exchange capacities (IECs) ranging from 1.06–4.14 mmol/g. At a hydration level of 9, cluster analysis reveals macrophase separation between water and terpolymers with IEC < 2.1 mmol/g and continuous, percolated hydrophilic and hydrophobic nanoscale domains at higher IECs. Channel width distribution analysis of the percolated morphologies revealed that more hydrophobic units produce less uniform channels. Decreasing the surface area per sulfonate group and increasing the fractal dimension of the hydrophilic domains correlate with increased water diffusivity, due to a more acidic interface and more isotropic water channels. Relative to the previously studied phenylsulfonate homopolymer, these terpolymers with lower IECs have only modestly lower water diffusion, and we anticipate other advantages related to processability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Fabrication of high-performance gas-diffusion-electrode based membrane-electrode assemblies

This paper demonstrates the fabrication and processing steps required to produce high performance fuel cell membrane electrode assemblies (MEAs) based on spray-coated gas-diffusion electrodes (GDEs). It is demonstrated that coating the catalyst layer with a thin layer of ionomer and then hot pressing the GDEs to the membrane is required to achieve comparable catalyst activity and air performance to catalyst-coated-membrane MEAs. We show that there is a critical amount of ionomer required to achieve maximized performance. Using electron microscopy, we show that the combination of the ionomer overlayer and hot-pressing bonds the catalyst layer to the membrane, increasing the interfacial contact area and quality of this interface. We also find that the ionomer overlayer smooths the surface of the GDE and provides increased contact area between the GDE and the membrane. Additionally, we demonstrate that much less ionomer is required for high-performance than has been previously reported. Through model fitting of electrochemical impedance spectroscopy, we show that this improvement in the catalyst layer - membrane interface reduces the effective catalyst layer resistance, which reduces Ohmic losses and increases catalyst utilization.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Adaptive Sampling of Large Deviations

We introduce and test an algorithm that adaptively estimates large deviation functions characterizing the fluctuations of additive functionals of Markov processes in the long-time limit. These functions play an important role for predicting the probability and pathways of rare events in stochastic processes, as well as for understanding the physics of nonequilibrium systems driven in steady states by external forces and reservoirs. The algorithm uses methods from risk-sensitive and feedback control to estimate from a single trajectory a new process, called the driven process, known to be efficient for importance sampling. Its advantages compared to other simulation techniques, such as splitting or cloning, are discussed and illustrated with simple equilibrium and nonequilibrium diffusion models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Assessing the Sensitivity of the Tropical Cyclone Boundary Layer to the Parameterization of Momentum Flux in the Community Earth System Model

Recent studies have demonstrated that high-resolution (~25 km) Earth System Models (ESMs) have the potential to skillfully predict tropical cyclone (TC) occurrence and intensity. However, biases in ESM TCs still exist, largely due to the need to parameterize processes such as boundary layer (PBL) turbulence. Building on past studies, we hypothesize that the depiction of the TC PBL in ESMs is sensitive to the configuration of the PBL parameterization scheme, and that the targeted perturbation of tunable parameters can reduce biases. The Morris one-at-a-time (MOAT) method is implemented to assess the sensitivity of the TC PBL to tunable parameters in the PBL scheme in an idealized configuration of the Community Atmosphere Model, version 6 (CAM6). The MOAT method objectively identifies several parameters in an experimental version of the Cloud Layers Unified by Binormals (CLUBB) scheme that appreciably influence the structure of the TC PBL. We then perturb the parameters identified by the MOAT method within a suite of CAM6 ensemble simulations and find a reduction in model biases compared to observations and a high-resolution, cloud-resolving model. Importantly, we demonstrate that the high-sensitivity parameters are tied to PBL processes that reduce turbulent mixing and effective eddy diffusivity, and that in CAM6 these parameters alter the TC PBL in a manner consistent with past modeling studies. In this way, we provide an initial identification of process-based input parameters that, when altered, have the potential to improve TC predictions by ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Diagnosis and prognosis of Alzheimer's disease using brain morphometry and white matter connectomes

Accurate, reliable prediction of risk for Alzheimer's disease (AD) is essential for early, disease-modifying therapeutics. Multimodal MRI, such as structural and diffusion MRI, is likely to contain complementary information of neurodegenerative processes in AD. Here we tested the utility of the multimodal MRI (T1-weighted structure and diffusion MRI), combined with high-throughput brain phenotyping—morphometry and structural connectomics—and machine learning, as a diagnostic tool for AD. We used, firstly, a clinical cohort at a dementia clinic (National Health Insurance Service-Ilsan Hospital [NHIS-IH]; N = 211; 110 AD, 64 mild cognitive impairment [MCI], and 37 cognitively normal with subjective memory complaints [SMC]) to test the diagnostic models; and, secondly, Alzheimer's Disease Neuroimaging Initiative (ADNI)-2 to test the generalizability. Our machine learning models trained on the morphometric and connectome estimates (number of features = 34,646) showed optimal classification accuracy (AD/SMC: 97% accuracy, MCI/SMC: 83% accuracy; AD/MCI: 97% accuracy) in NHIS-IH cohort, outperforming a benchmark model (FLAIR-based white matter hyperintensity volumes). In ADNI-2 data, the combined connectome and morphometry model showed similar or superior accuracies (AD/HC: 96%; MCI/HC: 70%; AD/MCI: 75% accuracy) compared with the CSF biomarker model (t-tau, p-tau, and Amyloid β, and ratios). In predicting MCI to AD progression in a smaller cohort of ADNI-2 (n = 60), the morphometry model showed similar performance with 69% accuracy compared with CSF biomarker model with 70% accuracy. Our comparisons of the classifiers trained on structural MRI, diffusion MRI, FLAIR, and CSF biomarkers showed the promising utility of the white matter structural connectomes in classifying AD and MCI in addition to the widely used structural MRI-based morphometry, when combined with machine learning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

A Codesign Framework for Online Data Analysis and Reduction

In this paper we discuss our design of a toolset for automating performance studies of composed HPC applications that perform online data reduction and analysis. We describe Cheetah, a new framework for performing parametric studies on coupled applications. Cheetah facilitates understanding the impact of various factors such as process placement, synchronicity of algorithms, and storage vs. compute requirements for online analysis of large data. Ultimately, we aim to create a catalog of performance results that can help scientists understand tradeoffs when designing next-generation simulations that make use of online processing techniques. We illustrate the design choices of Cheetah by using a reaction-diffusion simulation (Gray-Scott) paired with an analysis application to demonstrate initial results of fine-grained process placement on Summit, a pre-exascale supercomputer at Oak Ridge National Laboratory.

Mehta, Kshitij↗
DOE OSTI2018

Broadening of Modeled Cloud Droplet Spectra Using Bin Microphysics in an Eulerian Spatial Domain

This study investigates droplet size distribution (DSD) characteristics from condensational growth and transport in Eulerian dynamical models with bin microphysics. A hierarchy of modeling frameworks is utilized, including parcel, one-dimensional (1D), and three-dimensional large-eddy simulation (LES). The bin DSDs from the 1D model, which includes only vertical advection and condensational growth, are nearly as broad as those from the LES and in line with observed DSD widths for stratocumulus clouds. These DSDs are much broader than those from Lagrangian microphysical calculations within a parcel framework that serve as a numerical benchmark for the 1D tests. In contrast, the bin-modeled DSDs are similar to the Lagrangian microphysical benchmark for a rising parcel in which Eulerian transport is not considered. These results indicate that numerical diffusion associated with vertical advection is a key contributor to broadening DSDs in the 1D model and LES. This DSD broadening from vertical numerical diffusion is unphysical, in contrast to the physical mixing processes that previous studies have indicated broaden DSDs in real clouds. It is proposed that artificial DSD broadening from vertical numerical diffusion compensates for underrepresented horizontal variability and mixing of different droplet populations in typical LES configurations with bin microphysics, or the neglect of other mechanisms that broaden DSDs such as growth of giant cloud condensation nuclei. These results call into question the ability of Eulerian dynamical models with bin microphysics to investigate the physical mechanisms for DSD broadening, even though they may reasonably simulate overall DSD characteristics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Development of Cost-Competitive Advanced Thermoelectric Generators for Direct Conversion of Vehicle Waste Heat into Useful Electrical Power

General Motors LLC (GM) proposed a project to develop a cost-effective thermoelectric generator (TEG) that is fully integrated into a GM production light-duty vehicle. The project goal was to reduce automotive energy consumption and CO 2 emissions by generating usable electricity from exhaust gas waste heat. The project objectives were to overcome the major obstacles to TEG commercialization and demonstrate 5% fuel economy improvement over the US06 drive cycle. We investigated electrical and thermal management strategies that included: (1) reducing electrical accessory load on the alternator using thermoelectric (TE) generated power; (2) shifting engine-driven accessories to electrical drive to raise the electrical accessory load consumption; (3) attempting to use the excess electrical power for something other than the vehicle electrical load e.g., propulsion (optimal for hybrids); and (4) implementing fast engine/transmission warm-up during cold-start. We developed a TEG system and all vehicle controls and electrical systems for full vehicle integration. The TEG system was modeled and analyzed for performance and cost. Heat exchangers and thermal interfaces between heat exchangers and TE modules were optimized for TE performance. Other objectives of the project were to (1) further optimize compositions and processing parameters for TE materials, (2) develop suitable diffusion barriers, interfaces electrical interconnections, and thermal contacts within TE modules, (3) implement adequate protection of TE materials and modules from degradation during operation, and (4) develop manufacturing and assembly processes for large scale production of TE materials and components that include scale-up plans for the production of 100,000 TEG units per year.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Application of Linear Additive Conditions for Near-Infrared Diffuse Reflectance Absorption Spectroscopy

Determining the homogeneity of material mixing in real time during product processing is critical for quality control. According to the Kubelka–Munk (K-M) function of diffuse reflectance absorption spectrum, absorbance (A) is approximately linear with the content of the components when the sample scattering coefficient (S) is in a certain range. The S is determined by the particle size of powder samples. Therefore, this study determined particle size ranges that satisfy linear additivity in near-infrared diffuse reflectance spectroscopy (NIRDRS). Thus, the proposed NIRDRS analysis technique can be used to determine the homogeneity of material mixes or analyze the percentages of the components in the mixture. In this study, vitamin B3 and vitamin C were used for preparing mixed samples with varying percentages. The experimental results revealed that linear additivity is satisfied when the powder particle size is in the range of less than 280, 280–450, and 450–900 μm. When the confidence level is 0.01, the actual mixed spectra are not significantly different from the “simulated mixed spectra” constructed by linear addition, with their relative deviations less than 1.08%. The absolute errors of the actual and analytic percentages were within 2.98% for each component in the mixtures. The above conclusions also hold for sorghum, which has a complex material composition. Statistical models cannot analyze the percentages of components in the mixture. In contrast, linear addition and direct calibration approach avoids the use of a large number of samples for statistical modeling and analyze the percentages of mixed samples. Meanwhile, it can be used to discriminate and analyze the material mixing uniformity by building a mechanistic model.

Feng, Zhiyue↗
DOE OSTI2025

Observation of a Knotted Electron Diffusion Region in Earth's Magnetotail Reconnection

Magnetic reconnection is a fundamental plasma process that alters the magnetic field topology and releases magnetic energy. Most numerical simulations and spacecraft observations assume a two‐dimensional diffusion region, with the electron diffusion region (EDR) embedded in the same plane as the ion diffusion region (IDR) and a uniform guide field throughout. Using observations from Magnetospheric Multiscale mission, we report a non‐coplanar, knotted EDR in Earth's magnetotail current sheet. The reconnection plane of the knotted EDR deviates by approximately 38° from that of the IDR, with the guide field exhibiting both a 38° directional shift and a twofold increase in amplitude. Moreover, the Hall magnetic field is bipolar in the EDR but quadrupolar in the IDR, indicating different Hall current structures at electron and ion scales. These observations highlight the importance of three‐dimensional effects and illustrate the complexity of multiscale coupling between the EDR and IDR during reconnection studies.

diffusion region↗
DOE OSTI2017

Biphase Cobalt-Manganese Oxide with High Capacity and Rate Performance for Aqueous Sodium-Ion Electrochemical Energy Storage

Manganese-based metal oxide electrode materials are of great importance in electrochemical energy storage for their favorable redox behavior, low cost and environmental-friendliness. However, their storage capacity and cycle life in aqueous Na-ion electrolytes is not satisfactory. In this paper, we report the development of a bi-phase cobalt-manganese oxide (Co-Mn-O) nanostructured electrode material, comprised of a layered MnO 2 .H 2 O birnessite phase and a (Co 0.83 Mn 0.13 Va 0.04 )tetra(Co 0.38 Mn 1.62 ) octa O 3.72 (Va: vacancy; tetra: tetrahedral sites; octa: octahedral sites) spinel phase, verified by neutron total scattering and pair distribution function analyses. The bi-phase Co-Mn-O material demonstrates an excellent storage capacity towards Na-ions in an aqueous electrolyte (121 mA h g -1 at a scan rate of 1 mV s -1 in the half-cell and 81 mA h g -1 at a current density of 2 A g -1 after 5000 cycles in full-cells), as well as high rate performance (57 mA h g -1 a rate of 360 C). Electro-kinetic analysis and in situ X-ray diffraction measurements further confirm that the synergistic interaction between the spinel and layered phases, as well as the vacancy of the tetrahedral sites of spinel phase, contribute to the improved capacity and rate performance of the Co-Mn-O material by facilitating both diffusion-limited redox and capacitive charge storage processes.

25 ENERGY STORAGE↗
DOE OSTI2018

Assembly of Rabbit Capsules for Irradiation of Pyrolytic Carbon / Silicon Carbide Diffusion Couples in the High Flux Isotope Reactor

Tristructural isotropic (TRISO)–coated particle fuel is a promising advanced fuel concept being considered for several advanced reactor applications and for accident-tolerant fuel for light water reactors. One of the aspects studied in the development of this advanced fuel concept is the release of specific fission products (Ag, Eu, and Sr). The silicon carbide (SiC) layer of TRISO fuel serves as the primary barrier to metallic fission products and actinides not retained in the fuel kernel. The goal of this project is to evaluate the effect of irradiation on the diffusion of these fission products in the SiC layer of the fuel. For this purpose, rabbit capsules containing small slab diffusion couple specimens have been assembled to be irradiated in the High Flux Isotope Reactor (HFIR). The diffusion couple specimens have been fabricated using similar processes and equipment as those used to make TRISO particles; the desired fission products have been implanted in the specimens using an ion accelerator. Moreover, the effect of temperature on the fission products diffusion will be studied separately by performing thermal experiments in the absence of irradiation. This report describes the irradiation experiment design concept, summarizes the irradiation test matrix, and reports on the successful assembly of two rabbit capsules that will be irradiated in the HFIR.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Linking Soil Moisture Variation and Abundance of Plants to Geomorphic Processes: A Generalized Model for Erosion-Uplifting Landscapes

American Geophysical Union. All Rights Reserved. The diffusive and advective erosion-created landscapes have similar structure (hillslopes and channels) across different scales regardless of variations in drivers and controls. The relative magnitude of diffusive erosion to advective erosion ( D/K ratio) in a landscape development model controls hillslope length, shape, and drainage density, which regulate soil moisture variation, one of the critical resources of plants, through the contributing area ( A ) and local slope ( S ) represented by a topographic index (TI). Here we explore the theoretical relation between geomorphic processes, TI, and the abundance and distribution of plants. We derived an analytical model that expresses the TI with D, K , and A . This gives us the relation between soil moisture variation and geomorphic processes. Plant tolerance curves are used to link plant performance to soil moisture. Using the hypothetical tolerance curves of three plants, we show that the abundance and distribution of xeric, mesic, and hydric plants on the landscape are regulated by the D/K ratio. Where diffusive erosion is the major erosion process (large D/K ratio), mesic plants have higher abundance relative to xeric and hydric plants and the landscape has longer and convex-upward hillslope and low channel density. Finally, increasing the dominance of advective erosion increases relative abundance of xeric and hydric plants dominance, and the landscape has short and concave hillslope and high channel density.

59 BASIC BIOLOGICAL SCIENCES↗