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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Advective gas flow in bentonite: Development and comparison of enhanced multi-phase numerical approaches

Understanding the impact of repository gas, generated from degradation of waste and its interaction with the host rock, is essential when assessing the performance and safety function of long-term disposal systems for radioactive waste. Numerical models based on conventional multi-phase flow theory have historically been applied to predict the outcome and impact of gas flow on different repository components. However, they remain unable to describe the full complexity of the physical processes observed in water-saturated experiments (e.g., creation of dilatant pathways) and thus, the development of novel representations for their description is required when assessing fully saturated clay-based systems. This was the primary focus of Task A within the international cooperative project DECOVALEX-2019 (D-2019) and refinement of these approaches is the primary focus of this study (Task B in the current phase of DECOVALEX-2023). This paper summarises development of enhanced numerical representations of key processes and compares the performance of each model against high-quality laboratory test data. Experimental data reveals that gas percolation in water-saturated compacted bentonite is characterised by four key features: (i) a quiescence phase, followed by (ii) the gas breakthrough, which leads to a (iii) peak value, which is then followed by (iv) a negative decay. Three models based on the multiphase flow theory have been developed. These models can provide good initial values and reasonable responses for gas breakthrough (although some of them still predict a too-smooth response). Peak gas pressure values are in general reasonably well captured, although maximum radial stress differences are observed at 48 mm from the base of the sample. Here, numerical peak values of 12.8 MPa are predicted, whereas experimental values are about 11 MPa. These models are also capable of providing a reasonable representation of the negative pressure decay following peak pressure. However, other key specific features (such as the timing of gas breakthrough) still require a better representation. The model simulations and their comparison with experimental data show that these models need to be further improved with respect to model parameter calibration, the numerical representation of spatial heterogeneities in material properties and flow localisation, and the upscaling of the related physical processes and parameters. To further understand gas flow localisation, a new conceptual model has been developed, which shows that discrete channels can possibly be induced through the instability of gas-bentonite interface during gas injection, thus providing a new perspective for modeling gas percolation in low-permeability deformable media.

58 GEOSCIENCES↗
DOE OSTI2022

Capacitance of Carbon Nanotube/Graphene Composite Electrodes with [BMIM + ][BF$_4^–$]/Acetonitrile: Fixed Voltage Molecular Dynamics Simulations

The capacitance of nanoporous carbon electrode materials is dictated by the physical interactions with electrolyte ions and molecules at the accessible interior electrode surface. While significant progress has been made in designing and synthesizing carbon materials with well-defined and relatively homogeneous nanoporosity, the majority of materials remain heterogeneous, and the resulting properties reflect an average over this distribution. In this regard, computer simulations can be a valuable tool to predict or validate structure/property relationships by systematically investigating well-defined, model electrode morphologies. In this work, we utilize fixed-voltage molecular dynamics simulations to predict structure/capacitance relationships for five different model morphologies of carbon nanotube/graphene (CNT/G) composite electrodes with 1-butyl-3-methylimidazolium tetrafluoroborate/acetonitrile electrolyte. The CNT/G electrode models are inspired by experimental “layer-by-layer” syntheses and strike a balance between realism and computational tractability. Comparison between different model electrode architectures elucidates important structure/property relationships. We find that CNT/graphene contact points serve as “hot spots” with significantly enhanced charge separation relative to the rest of the electrode. Furthermore, we demonstrate a specific nanoconfinement motif that provides substantial 3–4$\times$ enhancement of local capacitance, resulting in a ~40% increase of the total electrode differential capacitance. Because the accessible surface area of the model CNT/G electrodes is precisely determined, a comparison of per-area capacitance across systems is unambiguous. Our results thus complement a prior computational demonstration of capacitance enhancement in nanoconfinement while elucidating additional interaction motifs at CNT/G electrochemical interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Immobilization of “Capping Arene” Cobalt(II) Complexes on Ordered Mesoporous Carbon for Electrocatalytic Water Oxidation

We report the synthesis, characterization, and electrocatalytic water oxidation activity of two cobalt complexes, (6-FP)Co(NO 3 ) 2 (1) (6-FP = 8,8'-(1,2-phenylene)diquinoline) and (5-FP)Co(NO 3 ) 2 (2) (5-FP = 1,2-bis(N-7-azaindolyl)benzene), containing "capping arene" bidentate ligands with nitrogen atom donors. The cobalt complexes 1 and 2 were supported on ordered mesoporous carbon (OMC) by π-π stacking, resulting in heterogenized cobalt materials 6-FP-Co-OMC-1 and 5-FP-Co-OMC-2, respectively, and studied for electrocatalytic water oxidation. We find that 6-FP-Co-OMC-1 exhibits an overpotential of 355 mV for a current density of 10 mA cm -2 and a turnover frequency (TOF) of ~0.53 s -1 at an overpotential of 400 mV at pH 14. 6-FP-Co-OMC-1 exhibits activity that is ~1.6 times that of 5-FP-Co-OMC-2, which gives a TOF of 0.32 s -1 at 400 mV overpotential. The structural stability of the single-atom Co site was demonstrated for 6-FP-Co-OMC-1 using X-ray absorption spectroscopy for the molecular complex supported on OMC, but slow degradation in catalyst activity can be attributed to eventual formation of Co oxide clusters. DFT computations of electrocatalytic water oxidation using the molecular complexes as models provide a description of the catalytic mechanism. These studies reveal that the mechanism for O-O bond formation involves an intermediate Co IV oxo complex that undergoes an intramolecular reductive O-O coupling to form a Co II -OOH species. Further, the calculations predict that the molecular 6-FP-Co structure is more active for electrocatalytic water oxidation than 5-FP-Co, which is consistent with experimental studies of 6-FP-Co-OMC-1 and 5-FP-Co-OMC-2, highlighting the possibility that the ligand structure influences the catalytic activity of the supported molecular catalysts.

25 ENERGY STORAGE↗
DOE OSTI2025

Long-Range Metal–Sorbent Interactions Determine CO 2 Capture and Conversion in Dual-Function Materials

Carbon capture and utilization involve multiple energy- and cost-intensive steps. Dual-function materials (DFMs) can reduce these demands by coupling CO 2 adsorption and conversion into a single material with two functionalities: a sorbent phase and a metal for catalytic CO 2 conversion. The role of metal catalysts in the conversion process seems salient from previous work, but the underlying mechanisms remain elusive and deserve deeper investigation to achieve maximum utilization of the two phases. Here, for this work, preformed colloidal Ru nanoparticles were deposited onto a “NaOx”/Al 2 O 3 sorbent to prepare prototypical DFMs with controlled phases for CO 2 capture and hydrogenation to CH 4 . Ru addition was found to double the high-temperature CO 2 adsorption capacity by activating the “NaOx”/Al 2 O 3 sorbent phase during a reductive pretreatment step. Most importantly, low Ru loadings were sufficient to ensure maximum CO 2 adsorption and conversion. This was attributed to the key role of the metal–sorbent interactions, wherein Ru was required to hydrogenate strongly bound CO 2 on the “NaO x ”/Al 2 O 3 sorbent to CH 4 via the H 2 activated on Ru. This interaction facilitated rate-determining carbonate migration and subsequent hydrogenation at the metal–sorbent interface. Overall, Ru controlled the CO 2 hydrogenation reaction rate, while the “NaO x ”/Al 2 O 3 sorbent dictated the CO 2 uptake capacity. By controlling metal–sorbent interactions at the molecular level, we demonstrate the critical role of the two phases and their synergy, facilitating the design of DFMs with maximum CO 2 capture and conversion efficiency.

carbon capture↗
DOE OSTI2020

Growth and auto-oxidation of Pd on single-layer AgO x /Ag(111)

Here, we investigated the growth and auto-oxidation of Pd deposited onto a AgO x single-layer on Ag(111) using scanning tunneling microscopy (STM) and X-ray photoelectron spectroscopy (XPS). Palladium initially grows as well-dispersed, single-layer clusters that adopt the same triangular shape and orientation of Ag n units in the underlying AgO x layer. Bi-layer clusters preferentially form upon increasing the Pd coverage to ~0.30 ML (monolayer) and continue to develop until aggregating and forming a nearly conformal Pd bi-layer at a coverage near 2 ML. Analysis of the STM images provides quantitative evidence of a transition from single to bi-layer Pd growth on the AgO x layer, and a continuation of bi-layer growth with increasing Pd coverage from ~0.3 to 2 ML. XPS further demonstrates that the AgO x layer efficiently transfers oxygen to Pd at 300 K, and that the fraction of Pd that oxidizes is approximately equal to the local oxygen coverage in the AgO x layer for Pd coverages up to at least ~0.7 ML. Our results show that oxygen in the initial AgO x layer mediates the growth and structural properties of Pd on the AgO x /Ag(111) surface, enabling the preparation of model PdAg surfaces with uniformly distributed single or bi-layer Pd clusters. Facile auto-oxidation of Pd by AgO x further suggests that oxygen transfer from Ag to Pd could play a role in promoting oxidation chemistry of adsorbed molecules on PdAg surfaces.

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

Characterizing electronic and atomic structures for amorphous and molecular metal oxide catalysts at functional interfaces by combining soft X-ray spectroscopy and high-energy X-ray scattering

Amorphous thin film materials and heterogenized molecular catalysts supported on electrode and other functional interfaces are widely investigated as promising catalyst formats for applications in solar and electrochemical fuels catalysis. However the amorphous character of these catalysts and the complexity of the interfacial architectures that merge charge transport properties of electrode and semiconductor supports with discrete sites for multi-step catalysis poses challenges for probing mechanisms that activate and tune sites for catalysis. This minireview discusses advances in soft X-ray spectroscopy and high-energy X-ray scattering that provide opportunities to resolve interfacial electronic and atomic structures, respectively, that are linked to catalysis. This review discusses how these techniques can be partnered with advances in nanostructured interface synthesis for combined soft X-ray spectroscopy and high-energy X-ray scattering analyses of thin film and heterogenized molecular catalysts. Further, these combined approaches enable opportunities for the characterization of both electronic and atomic structures underlying fundamental catalytic function, and that can be applied under conditions relevant to device applications.

14 SOLAR ENERGY↗
DOE OSTI2023

The influence of physical and algorithmic factors on simulated far-field waveforms and source–time functions of underground explosions using unsupervised machine learning

SUMMARY Characterizing explosion sources and differentiating between earthquake and underground explosions using distributed seismic networks becomes non-trivial when explosions are detonated in cavities or heterogeneous ground material. Moreover, there is little understanding of how changes in subsurface physical properties affect the far-field waveforms we record and use to infer information about the source. Simulations of underground explosions and the resultant ground motions can be a powerful tool to systematically explore how different subsurface properties affect far-field waveform features, but there are added variables that arise from how we choose to model the explosions that can confound interpretation. To assess how both subsurface properties and algorithmic choices affect the seismic wavefield and the estimated source functions, we ran a series of 2-D axisymmetric non-linear numerical explosion experiments and wave propagation simulations that explore a wide array of parameters. We then inverted the synthetic far-field waveform data using a linear inversion scheme to estimate source–time functions (STFs) for each simulation case. We applied principal component analysis (PCA), an unsupervised machine learning method, to both the far-field waveforms and STFs to identify the most important factors that control variance in the waveform data and differences between cases. For the far-field waveforms, the largest variance occurs in the shallower radial receiver channels in the 0–50 Hz frequency band. For the STFs, both peak amplitude and rise times across different frequencies contribute to the variance. We find that the ground equation of state (i.e. lithology and rheology) and the explosion emplacement conditions (i.e. tamped versus cavity) have the greatest effect on the variance of the far-field waveforms and STFs, with the ground yield strength and fracture pressure being secondary factors. Differences in the PCA results between the far-field waveforms and STFs could possibly be due to near-field non-linearities of the source that are not accounted for in the estimation of STFs and could be associated with yield strength, fracture pressure, cavity radius and cavity shape parameters. Other algorithmic parameters are found to be less important and cause less variance in both the far-field waveforms and STFs, meaning algorithmic choices in how we model explosions are less important, which is encouraging for the further use of explosion simulations to study how physical Earth properties affect seismic waveform features and estimated STFs.

58 GEOSCIENCES↗
DOE OSTI2022

Graphene-Based Interconnect Exploration for Large SRAM Caches for Ultrascaled Technology Nodes

Graphene-based interconnects are considered promising replacements for traditional copper (Cu) interconnect due to their great electric properties. In this article, an interconnect-memory co- design framework is developed to efficiently optimize various graphene-based interconnect technologies. Four interconnect materials and heterogeneous design schemes are benchmarked against their traditional Cu counterparts to optimize large cache-level SRAM performance in terms of delay and energy per access, energy-delay product (EDP), and energy-delay-area product (EDAP). Here, a large design space exploration is performed based on realistic subarray design and device technology. Various interconnect- and array-level design parameters are studied to quantify the true potential of graphene-based wires for optimal memory performance.

42 ENGINEERING↗
DOE OSTI2022

Review of metal-containing resists in electron beam lithography: perspectives for extreme ultraviolet patterning

Background: Metal-containing resists entered the mainstream semiconductor industry process flow to mitigate the low absorbance of extreme ultraviolet (EUV) radiation by thin films of organic resists that lead to poor sensitivity and their inability to handle rigors of development and etching conditions. Aim: The long and rich history of using metal-containing resists in electron beam lithography can offer interesting lessons, pointers, and insights to the relatively newcomer EUV lithography, which is slightly over a decade old. Approach: Electron beam lithography has been enjoying a considerable amount of freedom in the choice of resist materials for close to 50 years; especially the use of metal-containing resists to attain not only single digit nanometer resolution, higher sensitivity, and etch resistance but also lower line-edge roughness. Here, we make a comprehensive historical review of the progress made in the patterning of metal-containing resists in electron beam lithography and derive insights that can be potentially useful in EUV patterning. Perspectives: Small molecular weight resists are proven to be crucial for achieving higher resolution with low line-edge roughness. Simplifying process flow by reducing etch-stack-layers is conceivable with metal-containing resists, along with direct-patterning of functional materials for heterogeneous integration. Efficient contact hole patterning at tighter pitches may be incumbent on progress in positive-tone resist research.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

High-sensitivity nanoscale chemical imaging with hard x-ray nano-XANES

Resolving chemical species at the nanoscale is of paramount importance to many scientific and technological developments across a broad spectrum of disciplines. Hard x-rays with excellent penetration power and high chemical sensitivity are suitable for speciation of heterogeneous (thick) materials. Here, we report nanoscale chemical speciation by combining scanning nanoprobe and fluorescence-yield x-ray absorption near-edge structure (nano-XANES). First, the resolving power of nano-XANES was demonstrated by mapping Fe(0) and Fe(III) states of a reference sample composed of stainless steel and hematite nanoparticles with 50-nm scanning steps. Nano-XANES was then used to study the trace secondary phases in lithium iron phosphate (LFP) particles. We observed individual Fe-phosphide nanoparticles in pristine LFP, whereas partially (de)lithiated particles showed Fe-phosphide nanonetworks. These findings shed light on the contradictory reports on Fe-phosphide morphology in the literature. Nano-XANES bridges the capability gap of spectromicroscopy methods and provides exciting research opportunities across multiple disciplines.

25 ENERGY STORAGE↗
DOE OSTI2022

A two-phase model that unifies and extends the classical models of membrane transport

Two models describe solvent transport through swollen, nonporous membranes. The pore-flow model, based on fluid mechanics, works for porous membranes, whereas the solution-diffusion model invokes molecular diffusion to treat nonporous membranes. Both approaches make valid arguments for swollen polymer membranes, but they disagree in their predictions of intramembrane pressure and concentration profiles. Using a fluid-solid model that treats the solvent and membrane matrix as separate phases, we show both classical models to be valid, to represent complementary approaches to the same phenomenon, and to make identical predictions. The fluid-solid model clarifies recent reverse osmosis measurements; provides a predictive and mechanistic basis for empirical high-pressure limiting flux phenomena, in quantitative agreement with classic measurements; and gives a framework to treat nonporous but mechanically heterogeneous membrane materials.

Science & Technology - Other Topics↗
DOE OSTI2020

An energy-based coupling approach to nonlocal interface problems.

Nonlocal models provide accurate representations of physical phenomena ranging from fracture mechanics to complex subsurface flows, settings in which traditional partial differential equation models fail to capture effects caused by long-range forces at the microscale and mesoscale. However, the application of nonlocal models to problems involving interfaces, such as multimaterial simulations and fluid-structure interaction, is hampered by the lack of a physically consistent interface theory which is needed to support numerical developments and, among other features, reduces to classical models in the limit as the extent of nonlocal interactions vanish. In this paper, we use an energy-based approach to develop a formulation of a nonlocal interface problem which provides a physically consistent extension of the classical perfect interface formulation for partial differential equations. Numerical examples in one and two dimensions validate the proposed framework and demonstrate the scope of our theory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Discovering new governing equations using ML

A hallmark of the scientific process since the time of Newton has been the derivation of mathematical equations meant to capture relationships between observables. As the field of mathematical modeling evolved, practitioners specifically emphasized mathematical formulations that were predictive, generalizable, and interpretable. Machine learning’s ability to interrogate complex processes is particularly useful for the analysis of highly heterogeneous, anisotropic materials where idealized descriptions often fail. As we move into this new era, we anticipate the need to leverage machine learning to aid scientists in extracting meaningful, but yet sometimes elusive, relationships between observed quantities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Machine Learning Inference of Random Medium Properties

Earth materials are heterogeneous across a range of spatial scales, but the resolvability of small structures is limited by sparse data coverage, noise, bandlimitedness, and other difficulties. In practice, heterogeneities below a certain size cannot be recovered from seismic data except through statistical medium descriptions, which even then can be difficult to uniquely determine. To improve the characterization of such heterogeneities, we develop a novel supervised machine learning (ML) model that provides insight about the recoverability of statistical medium properties from elastic waveform data and succeeds despite cycle-skipping and other challenges well known from elastic waveform inversion. We demonstrate the approach using random media generated by superimposing self-affine random variations on homogeneous and layered background structures. After training on sparsely-recorded, high-frequency waveforms from hundreds of different random medium realizations, we show the ability of our ML model to recover correlation lengths and other statistical properties of interest to near-surface and crustal seismology, among other fields. For frequency passbands and spatial offsets encountered in seismology, Gaussian correlation lengths and the amplitude of the random variations relative to the background model are recovered even in challenging scenarios involving unknown medium parameters, complex crustal structures, and low signal-to-noise ratio. In comparison, von Kármán correlation lengths, which are related to larger-wavelength variations of the medium than Gaussian correlation lengths, are not as well recovered. These results provide one of the first and most systematic investigations of the recoverability of statistical properties of heterogeneities below the resolution limit of deterministic seismic tomography, and suggest practical ML strategies for high-frequency waveform seismology.

58 GEOSCIENCES↗
DOE OSTI2024

The ORNL Moderator Test Station Science Case

Oak Ridge National Laboratory (ORNL) hosts two world-leading slow neutron sources, the Spallation Neutron Source (SNS) and the High Flux Isotope Reactor (HFIR), and is currently developing the technical design for a Second Target Station (STS) for the SNS. Upon completion of the STS project, ORNL will be uniquely positioned to optimize each of its three neutron sources, the SNS First Target Station (FTS), the STS, and HFIR, in a complementary way. Among the essential aspects of a re-imagined FTS and the current STS design are high-brightness parahydrogen moderators—moderators which are optimized for high per-unit-area neutron brightness rather than integrated-across-large-area neutron intensity. The high-brightness moderators proposed for the STS will, for the brightness metric, significantly outperform the coupled moderators currently on the FTS for appropriately optimized neutron beamlines, provided the moderating hydrogen is converted to near-equilibrium levels of parahydrogen (approximately 99.8% at 20 K). The original FTS moderators, by contrast, were conservatively designed to be relatively insensitive to the exact ortho:para ratio, with a consequent loss in performance. As a result, a redesign of the FTS moderators assuming fully converted parahydrogen could result in significant performance improvements on the FTS coupled moderators, and more consistent performance over time for all hydrogen moderators. This “parahydrogen problem” is a long-standing challenge for the effective implementation of hydrogen cold moderators at high-power neutron sources. In addition, the development of new moderator concepts, whether based on previously unused materials, structured heterogeneous arrays, or even simply on changes in overall shape and size is significantly restricted at a large-scale production facility intended to use the resulting neutron beams. Accordingly, moderators for production neutron sources are often designed in a very conservative, low-risk fashion, even though this compromises the absolute neutronic performance. Advanced moderator concepts worthy of study include features that could not be tested without redesigning and redeploying the entire existing reflector, shielding, and neutron beamline installation, making such development efforts far more expensive than building a stand-alone test facility.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗