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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Influence of contrasting redox conditions on iron (oxyhydr)oxide transformation and associated phosphate sorption

Iron (oxyhydr)oxides strongly adsorb phosphate and limit its bioavailability, but interactions between phosphate and various Fe (oxyhydr)oxides are poorly constrained in natural systems. An in-situ incubation experiment was conducted to explore Fe (oxyhydr)oxide transformation and effects on phosphate sorption in soils with contrasting saturation and redox conditions. Synthetic Fe (oxyhydr)oxides (ferrihydrite, goethite and hematite) were coated onto quartz sand and either pre-sorbed with phosphate or left phosphate-free. The oxide-coated sands were mixed with natural organic matter, enclosed in mesh bags, and buried in and around a vernal pond for up to 12 weeks. Redox conditions were stable and oxic in the upland soils surrounding the vernal pond but largely shifted from Fe reducing to Fe oxidizing in the lowland soils within the vernal pond as it dried during the summer. Iron (oxyhydr)oxides lost more Fe (- 41% ± 10%) and P (- 43 ± 11%) when incubated in the redox-dynamic lowlands compared to the uplands (- 18% ± 5% Fe and - 24 ± 8% P). Averaged across both uplands and lowlands, Fe losses from crystalline goethite and hematite (- 38% ± 6%) were unexpectedly higher than losses from short range ordered ferrihydrite (- 12% ± 10%). We attribute losses of Fe and associated P from goethite and hematite to colloid detachment and dispersion but losses from ferrihydrite to reductive dissolution. Iron losses were partially offset by retention of solubilized Fe as organic-bound Fe(III). Iron (oxyhydr)oxides that persisted during the incubation retained or even gained P, indicating low amounts of phosphate sorption from solution. In conclusion, these results demonstrate that hydrologic variability and Fe (oxyhydr)oxide mineralogy impact Fe mobilization pathways that may regulate phosphate bioavailability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A multi-material platform for imaging of single cell-cell junctions under tensile load fabricated with two-photon polymerization

We previously reported a single-cell adhesion micro tensile tester (SCAμTT) fabricated from IP-S photoresin with two-photon polymerization (TPP) for investigating the mechanics of a single cell-cell junction under defined tensile loading. A major limitation of the platform is the autofluorescence of IP-S, the photoresin for TPP fabrication, which significantly increases background signal and makes fluorescent imaging of stretched cells difficult. In this study, we report the design and fabrication of a new SCAμTT platform that mitigates autofluorescence and demonstrate its capability in imaging a single cell pair as its mutual junction is stretched. By employing a two-material design using IP-S and IP-Visio, a photoresin with reduced autofluorescence, we show a significant reduction in autofluorescence of the platform. Further, by integrating apertures onto the substrate with a gold coating, the influence of autofluorescence on imaging is almost completely mitigated. With this new platform, we demonstrate the ability to image a pair of epithelial cells as they are stretched up to 250% strain, allowing us to observe junction rupture and F-actin retraction while simultaneously recording the accumulation of over 800 kPa of stress in the junction. In conclusion, the platform and methodology presented here can potentially enable detailed investigation of the mechanics of and mechanotransduction in cell-cell junctions and improve the design of other TPP platforms in mechanobiology applications.

Autofluorescence↗
DOE OSTI2020

Calcium Phosphate Catalysts for Ethanol Coupling to Butanol and Butadiene

The catalytic conversion of ethanol to butanol and butadiene at 633 K and atmospheric pressure (7 vol% ethanol) was studied over calcium phosphate materials pretreated over a wide temperature range. For calcium phosphate pretreated at or below 923 K, the resulting solid had an apatite structure identified by X-ray diffraction and strong acid sites probed by triethylamine (TEA) adsorption microcalorimetry. The low temperature pretreated materials were not effective at ethanol coupling reactions but instead were highly selective to acid-catalyzed products ethene and diethyl ether. Pretreatment of calcium phosphate at 973 K transformed the apatite structure to β-tricalcium phosphate, which exposed both acid and base sites evaluated by TEA and CO 2 adsorption microcalorimetry. In conclusion, high temperature pretreated calcium phosphate catalysts formed the coupling products butanol and butadiene during ethanol reaction. The butadiene selectivity was improved by supporting calcium phosphate on zirconia.

09 BIOMASS FUELS↗
DOE OSTI2022

Chemical Grafting of Highly Dispersed VO x /CeO 2 for Increased Catalytic Activity in Methanol Oxidative Dehydrogenation

Vanadia supported on well-defned ceria nanocubes are synthesized at various loadings using a liquid-phase chemical grafting technique and are compared to those prepared using traditional incipient wetness impregnation. Raman and IR characterization reveal that, as vanadia loading is increased to near monolayer coverage, vanadia deposited using grafting shows greatly enhanced dispersion (i.e., improved VO x monomer/dimer distribution). Methanol is used as a probe molecule to explore the redox behavior of the catalysts. IR and temperature programmed desorption of methanol show increased CO 2 formation occurs on the bare ceria support and increasing the dispersion of vanadia promotes dehydrogenation to formaldehyde due to the inhibited oxygen vacancy formation on VO x /CeO 2 . Hydrogen temperature programmed reduction demonstrates that the catalyst reducibility and formation of surface oxygen vacancy are directly related to the degree of vanadia oligomerization. In conclusion, the samples prepared using grafting exhibit superior catalytic performance for methanol oxidative dehydrogenation to formaldehyde compared to the impregnated samples, due to the presence of highly dispersed VO x species (i.e., monomers and dimers).

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

Functional group effect of chemically modified microcrystalline methyl cellulose on thermoplastic polyurethane composites

Microcrystalline cellulose (MCC) is a promising bio-based filler for lightweight yet mechanically high-performance eco-polymer composites because of its low density and high biocompatibility. However, intermolecular hydrogen bonding among MCC is stronger than the polymer–filler interactions, which deteriorate the mechanical properties of the composites. Herein, we investigated the effects of functional groups on the mechanical properties of composites by scrutinizing chemically modified microcrystalline methyl cellulose (m-MMC) with three different substitution levels of hydroxyl group to hydroxypropyl (HP) group: no-, low-, and high-level substitution (HP-0, HP-low, and HP-high). The degree of HP substitution of m-MMC was quantitatively measured by CP/MAS NMR analysis. The relatively bulky HP groups interrupted the filler–filler intermolecular interactions and reduced the crystallinity and density of m-MMC, as evident from X-ray diffractometer and pycnometer data, respectively. For scalable production of the composites, the m-MMC were compounded with thermoplastic polyurethane (TPU) by a twin-screw extruder at concentrations between 0.5 and 10 wt%. Despite its low filler concentration, the toughness of m-MMC/TPU composites was remarkably enhanced, up to 28% (229.2 to 294.4 MJ/m 3 ) at 0.5 wt% loading of HP-low, owing to the enhanced polymer–filler interactions. In conclusion, the fundamental understanding on structure–property relationships will provide insights for designing of mechanically robust yet eco-friendly polymer composites.

composites↗
DOE OSTI2024

Mercury bioaccumulation and Hepatozoon spp. infections in two syntopic watersnakes in South Carolina

Mercury (Hg) is a ubiquitous environmental contaminant known to bioaccumulate in biota and biomagnify in food webs. Parasites occur in nearly every ecosystem and often interact in complex ways with other stressors that their hosts experience. Hepatozoon spp. are intraerythrocytic parasites common in snakes. The Florida green watersnake (Nerodia floridana) and the banded watersnake (Nerodia fasciata) occur syntopically in certain aquatic habitats in the Southeastern United States. The purpose of this study was to investigate relationships among total mercury (THg) concentrations, body size, species,habitat type and prevalence and parasitemia of Hepatozoon spp. infections in snakes. In the present study, we sampled N. floridana and N. fasciata from former nuclear cooling reservoirs and isolated wetlands of the Savannah River Site in South Carolina. We used snake tail clips to quantify THg and collected blood samples for hemoparasite counts. Our results indicate a significant, positive relationship between THg and snake body size in N. floridana and N. fasciata in both habitats. Average THg was significantly higher for N. fasciata compared to N. floridana in bays (0.22 ± 0.02 and 0.08 ± 0.006 mg/kg, respectively; p < 0.01), but not in reservoirs (0.17 ± 0.02 and 0.17 ± 0.03 mg/kg, respectively; p = 0.29). Sex did not appear to be related to THg concentration or Hepatozoon spp. infections in either species. In conclusion, we found no association between Hg and Hepatozoon spp. prevalence or parasitemia; however, our results suggest that species and habitat type play a role in susceptibility to Hepatozoon spp. infection.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

Mortality among individuals exposed to atomic bomb radiation in utero: 1950–2012

We examined the mortality risks among 2463 individuals who were exposed in utero to atomic bomb radiation in Hiroshima or Nagasaki in August 1945 and were followed from October 1950 through 2012. Individual estimates of mother’s weighted absorbed uterine dose (DS02R1) were used. Poisson regression method was used to estimate the radiation-associated excess relative risk per Gy (ERR/Gy) and 95% confidence intervals (CI) for cause-specific mortality. Head size, birth weight, and parents’ survival status were evaluated as potential mediators of radiation effect. There were 339 deaths (216 males and 123 females) including deaths from solid cancer (n = 137), lymphohematopoietic cancer (n = 8), noncancer disease (n = 134), external cause (n = 56), and unknown cause (n = 4). Among males, the unadjusted ERR/Gy (95% CI) was increased for noncancer disease mortality (1.22, 0.10–3.14), but not for solid cancer mortality (-0.18,< -0.77–0.95); the unadjusted ERR/Gy for external cause mortality was not statistically significant (0.28, < -0.60–2.36). Among females, the unadjusted ERRs/Gy were increased for solid cancer (2.24, 0.44–5.58), noncancer (2.86, 0.56–7.64), and external cause mortality (2.57, 0.20–9.19). The ERRs/Gy adjusted for potential mediators did not change appreciably for solid cancer mortality, but decreased notably for noncancer mortality (0.39, < -0.43–1.91 for males; 1.48, - 0.046–4.55 for females) and external cause mortality (0.10, < -0.57–1.96 for males; 1.38, < -0.46–5.95 for females). In conclusion, antenatal radiation exposure is a consistent risk factor for increased solid cancer mortality among females, but not among males. The effect of exposure to atomic bomb radiation on noncancer disease and external cause mortality among individuals exposed in utero was mediated through small head size, low birth weight, and parental loss.

Public, Environmental & Occupational Health↗
DOE OSTI2020

An Interaction-Free Quantum Measurement-Driven Engine

Recently highly-efficient quantum engines were devised by exploiting the stochastic energy changes induced by quantum measurement. Here we show that such an engine can be based on an interaction-free measurement, in which the meter seemingly does not interact with the measured object. We use a modified version of the Elitzur–Vaidman bomb tester, an interferometric setup able to detect the presence of a bomb triggered by a single photon without exploding it. In our case, a quantum bomb subject to a gravitational force is initially in a superposition of being inside and outside one of the interferometer arms. We show that the bomb can be lifted without blowing up. This occurs when a photon traversing the interferometer is detected at a port that is always dark when the bomb is located outside the arm. The required potential energy is provided by the photon (which plays the role of the meter) even though it was not absorbed by the bomb. A natural interpretation is that the photon traveled through the arm which does not contain the bomb—otherwise the bomb would have exploded—but it implies the surprising conclusion that the energy exchange occurred at a distance despite a local interaction Hamiltonian. We use the weak value formalism to support this interpretation and find evidence of contextuality. Regardless of interpretation, this interaction-free quantum measurement engine is able to lift the most sensitive bomb without setting it off.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

DyG-DPCD: A Distributed Parallel Community Detection Algorithm for Large-Scale Dynamic Graphs

Dynamic (Temporal) graphs capture the valuable evolution of real-world systems, from the continuously evolving patterns of social interactions and genetic pathways to the dynamic fluctuations of economic forces. Detecting communities for such evolving networks poses unique challenges. Detecting and analyzing the evolution of communities within dynamic graphs unlocks valuable insights into the underlying structural and temporal patterns of real-world systems. However, the sheer volume of modern graph data and the inherent complexity of the temporal dimension pose significant challenges to scalable community detection algorithms. Addressing this gap, our work explores the limited landscape of scalable distributed-memory parallel methods specifically designed for dynamic network community detection. We propose a novel parallel algorithm, DyG-DPCD (Dynamic Graph Distributed Parallel Community Detection), to detect communities in dynamic networks using the Message Passing Interface (MPI) framework. We present a vertex-centric approach, allowing us to detect communities through local optimization. Furthermore, we enhance our baseline algorithm by incorporating three heuristics, which improve the algorithm’s performance significantly while maintaining the quality of the solutions. We demonstrate the efficiency of our algorithm by experimenting on several real-world large-scale networks with hundreds of millions of edges spanning diverse domains. Notably, DyG-DPCD achieves speedups between 25× and 30× for large networks that we experimented on using NERSC compute nodes. In conclusion, our algorithm outperforms the STINGER parallel re-agglomeration algorithm by 30×.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Using GANs to predict milling stability from limited data

Milling is a key manufacturing process that requires the selection of operating parameters that provide efficient performance. However, the presence of chatter, a self-excited vibration causing poor surface finish and potential damage to the machine and cutting tool, makes it challenging to select the appropriate parameters. To predict chatter, stability maps are commonly used, but their generation requires expensive data, making it difficult to employ these maps in industry. Therefore, there is a pressing need for an approach that can accurately predict stability maps using limited experimental data. This study introduces the new Encoder GAN (EGAN) approach based on Generative Adversarial Networks (GANs) that predicts stability maps using limited experimental data. The approach consists of the encoder, generator, and discriminator subnetworks and uses the trained encoder and generator to predict the target stability map. This versatile method can be applied to various tool setups and can accurately predict stability maps with limited experimental data (five to 10 cutting tests) even when there is little information available for unknown parameters. In conclusion, the study evaluates the proposed approach using both numerical data and experiments and demonstrates its superior performance compared to state-of-the-art benchmarks.

42 ENGINEERING↗
DOE OSTI2024

Data-driven search for promising intercalating ions and layered materials for metal-ion batteries

The rise in demand for lithium-ion batteries has led to a large-scale search for electrode materials and intercalating ion species to meet the demands of next-generation energy technologies. Recent efforts largely focus on searching for cathodes that can accommodate large amounts of intercalating ions, but similar work on anodes is relatively limited. This study utilizes machine learning methods to find alternative two-dimensional (2D) materials and intercalating ions beyond Li for metal-ion batteries with high-power efficiencies. The approach first uses density functional theory (DFT) calculations to estimate the theoretical capacities and voltages of various metal ions on 2D materials. The DFT-generated data also provide insights into the local structural accommodation upon ion intercalation on various 2D materials. Significant changes to the lattice can result in irreversible changes to the bonding environments in the anode material, resulting in poor cycling stability. Next, this study develops a binding energy and structural accommodation-based classification model to screen anode materials for next-generation batteries. The classification model selects intercalating ions and 2D material pairs suitable for batteries based on the calculated voltage and volumetric changes in the 2D material upon intercalation. Finally, this study builds a regression model to accurately predict the binding energies of the various intercalating ions on 2D materials. The approach highlights the importance of different elemental and structural features for classification and regression tasks. In conclusion, the insights gained from this study on the role of involved features, such as electronegativities of the constituent ions and the presence of unfilled electronic levels, will help to streamline further studies towards the search for future layered battery materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Micro–macro finite element modeling method for rub response in abradable coating materials

Gas turbine engines experience “rub” when the rotating blades come in contact with a static abradable coating. This results in extreme strain rates and dynamics inside a high-temperature/high-pressure environment. Current rub models are phenomenological and do not reflect the underlying microstructures, thus limiting their prediction accuracy. In this work, a microstructure-informed, reduced order modeling framework is introduced for simulating abradable coating “rub" behavior. This framework comprises a microscale model constructed based on digitized abradable microstructure and explicitly simulates the mechanical behavior of each constituent phases and their interactions. After calibration and validation with experiment data, the calibrated microscale model is used to generate data across a vast range of applied strain rates and temperature with various load paths. Then, the virtually generated data are used to fit the macroscopic-reduced order model, which enables fast component scale rub simulation without compromising the integrity of the complex material behavior. In conclusion, the proposed effort will address the technical challenge of predicting abradable material behavior during rub through the application of multiscale modeling from microstructure to engines behavior, effectively reducing the development costs and time of new abradable material for better “rub” properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Gaussian process autoregressive model capturing microstructure evolution paths in a Ni–Mo–Nb alloy

Additive manufacturing is increasingly being employed to produce components of complex geometries in structural alloys because of the expected energy savings associated with the near-net-shape capability and the ability to build in novel internal features that are not possible with many conventional manufacturing approaches. However, because of the extreme thermal conditions encountered, the non-equilibrium microstructures produced during powder bed-based additive manufacturing processes must be subjected to custom post-heat treatment processes to recover the target mechanical properties. Phase-field models and simulation techniques have matured to a state where the microstructure evolution paths, and the morphologies of the resulting precipitate phases can be predicted reasonably accurately, considering alloy-specific thermodynamic and kinetic aspects of the nucleation and growth processes. However, phase-field simulations are computationally intensive, which precludes the ability to apply the simulations directly to the length scale of the entire component. Therefore, it is highly desirable to develop low-computational-cost surrogate models that effectively capture the physics at the microstructural length scale, while facilitating the design of optimized processing conditions resulting in location-specific targeted microstructures at the component scale. The work presented here demonstrates the application of the materials knowledge system framework to develop a surrogate model that effectively captures the microstructural path during annealing of a Ni–Mo–Nb alloy containing different Mo and Nb compositions known to segregate during solidification under additive manufacturing conditions. Specifically, the surrogate model built in this work is based on a Gaussian process autoregressive model informed by statistical representation of simulated microstructures using two-point correlations and dimensionality reduction through principal component analysis. In conclusion, this surrogate model is shown to capture the bifurcation of the microstructural path during precipitation, which yields a microstructure dominated by the $\gamma^{\prime\prime}$ phase at high Nb concentrations and the $\delta$ phase at low Nb concentrations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Active Divertor Heat Flux Control using Impurity Powder Dropper

Divertor plasma-facing components (PFCs) in a tokamak are typically designed to withstand average steady-state heat loads of about 5–10 MW/m 2 , a limit that applies to both solid and liquid lithium (LL) PFCs. Exceeding these design values can result in surface damage to tungsten PFCs or excessive lithium (Li) evaporation in liquid lithium divertor (LLD) PFCs. Since exceeding the divertor heat load limits has serious consequences, it is therefore prudent to develop a tool to reduce the divertor heat load and bring the heat load to within the design limit without affecting the plasma performance. Active low Z impurity injection such as Li has been suggested as a potential solution to mitigate excess heat flux as suggested previously, given that non-coronal radiation can be quite large ~ 20–30 MJ per mole of injected Li. Li is considered desirable for reducing the edge neutral recycling helping to improve plasma energy confinement. In this paper, we model the Impurity Power Dropper (IPD) to investigate its potential of divertor heat flux control. The IPD is typically located at the top of the tokamak device and uses a vertical drift tube of a few meters. In the 2 m drift tube case, the IPD powder is accelerated to ~ 6 m/sec before reaching the plasma with the upper divertor configuration, matching the condition for the in-board side pellet injection case. By modeling the IPD geometry we determined the IPD powder deposition profile, and thus the non-coronal radiation and ionization profiles in time as well. From the enhanced radiation power loss, it is therefore possible to reduce the divertor heat load using the divertor simulation code. In conclusion, the IPD divertor heat flux control can be tested in the facilities with IPD including ST-40, DIII-D, EAST, WEST and NSTX-U.

Active lithium injection↗
DOE OSTI2024

Electron–Phonon Coupling in Copper-Substituted Lead Phosphate Apatite

Recent reports of room-temperature, ambient pressure superconductivity in copper-substituted lead phosphate apatite, commonly referred to as LK99, have prompted numerous theoretical and experimental studies into its properties. As the electron–phonon interaction is a common mechanism for superconductivity, the electron–phonon coupling strength is an important quantity to compute for LK99. In this work, we compare the electron–phonon coupling strength among the proposed compositions of LK99. The results of our study are in alignment with the conclusion that LK99 is a candidate for low-temperature, not room-temperature, superconductivity if electron–phonon interaction is to serve as the mechanism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Nonlinear Impact-Echo Test for Quantitative Evaluation of ASR Damage in Concrete

Nonlinear acoustic methods demonstrate high sensitivity for concrete damage evaluation. Among these methods, nonlinear resonance acoustic methods have been widely used in laboratory tests on small scale test samples. In this study, a nonlinear impact-echo (IE) method for concrete damage evaluation was introduced, in which the IE frequency shift was measured at different impact force levels. The nonlinear IE test and the nonlinear impact resonance acoustic spectroscopy (NIRAS) test share similarities in the experimental setup and analysis method. However, the nonlinear IE test excites a local thickness resonance mode of a member instead of the global resonance vibration. Therefore, the analyzed mode is unaffected by member boundary conditions and is applicable to large concrete structural members. To identify the fundamental IE frequencies, multiple impacts were applied along the members. Once the fundamental IE frequencies were determined, the effectiveness of the nonlinear IE method was evaluated by testing seven concrete beam specimens with varying levels of alkali-silica reaction (ASR) damage. In conclusion, the nonlinear IE test demonstrates high sensitivity to concrete damage and allows for quantitative assessment of the damage state of concrete without a baseline measurement.

36 MATERIALS SCIENCE↗
DOE OSTI2021

High-T c Superconducting Memory Cell

In this paper, operational principles of a cryogenic memory cell that utilizes high-temperature superconductors (high-T c ) are presented. Such a cell consists of three inductively coupled Josephson junctions coupled via inductors. Design and operational logic of this type of cell were recently introduced and demonstrated for low temperature 4 K environment. The basic memory cell operations (read, write, reset) can be implemented on the same simple circuit and both destructive and non-destructive memory cell operations can be realized. Here, we present the design principles and computational validation of basic memory cell operations (write, read, and reset) for the high-T c memory cell. In conclusion, our results for the high-T c memory cell operations show very good resemblance with the previously presented low-temperature 4 K memory cell operations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗