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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Mechanisms and kinetics of citrate-promoted dissolution of a uranyl phosphate mineral

The formation of uranyl phosphate precipitates is a remediation strategy to limit the mobility of uranium in contaminated soils. However, exposure to organic ligands, like the plant exudate citrate, can remobilize the uranium. The purpose of this study is to provide a more thorough comprehension of citrate-promoted dissolution of a uranyl phosphate mineral, chernikovite [(H 3 O)(UO 2 )(PO 4 )·3H 2 O], by determining the extent of uranium release from chernikovite at a wide range of citrate concentrations. Here we have quantified the kinetics of dissolution and proposed potential mechanisms of chernikovite dissolution to gain a better understanding of the fate of uranyl phosphate precipitates in the environment. Batch dissolution and continuously stirred tank reactor (CSTR) experiments indicate that increasing citrate concentrations from 0.1 mM to 50 mM increases the concentration of dissolved uranium. However, at citrate concentrations of 10 mM and greater, the effectiveness of the ligand to enhance the dissolution decreases. Density functional theory modeling and Raman spectroscopy indicate a strong interaction between citrate and the uranyl ions at the surface of the uranyl phosphate. The interaction between citrate and uranyl suggests the formation of an alteration layer of uranyl-citrate surface complexes, which could impede uranium release at citrate concentrations of 10 mM or higher. Together, these results indicate that the citrate-promoted dissolution of chernikovite is a fast reaction that is hindered by a combination of surface saturation and a secondary-phase precipitation reaction at higher concentrations of citrate and reaction times greater than or equal to 72 min based on the hydraulic residence time of CSTR experiments. These findings improve our understanding of the stability of uranyl phosphate for use in sequestration of uranium groundwater plumes at contaminated sites.

58 GEOSCIENCES↗
DOE OSTI2023

Unraveling the 2021 Central Tennessee flood event using a hierarchical multi-model inundation modeling framework

Flood prediction systems need hierarchical atmospheric, hydrologic, and hydraulic models to predict rainfall, runoff, streamflow, and floodplain inundation. The accuracy of such systems depends on the error propagation through the modeling chain, sensitivity to input data, and choice of models. In this study, we used multiple precipitation forcings (hindcast and forecast) to drive hydrologic and hydrodynamic models to analyze the impacts of various drivers on the estimates of flood inundation depth and extent. We implement this framework to unravel the August 2021 extreme flooding event that occurred in Central Tennessee, USA. We used two radar-based quantitative precipitation estimates (STAGE4 and MRMS) as well as quantitative precipitation forecasts (QPF) from the National Weather Service Weather Prediction Center (WPC) to drive a series of models in the hierarchical framework, including the Variable Infiltration Capacity (VIC) land surface model, the Routing Application for Parallel Computation of Discharge (RAPID) river routing model, and the AutoRoute and TRITON inundation models. An evaluation with observed high-water marks demonstrates that the framework can reasonably simulate flood inundation. Despite the complex error propagation mechanism of the modeling chain, we show that inundation estimates are most sensitive to rainfall estimates. Most notably, QPF significantly underestimates flood magnitudes and inundations leading to unanticipated severe flooding for all stakeholders involved in the event. Finally, we discuss the implications of the hydrodynamic modeling framework for real-time flood forecasting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Observing the three-dimensional dynamics of supported metal complexes

Dynamics are intricately linked with activity and selectivity when it comes to catalysis, as noted for instance in the enzymatic principles of induced fit and allostery, and yet the range of motions heterogeneous catalytic sites are able to undergo is poorly understood. Solid-state nuclear magnetic resonance (NMR) spectroscopy is perhaps the only tool capable of probing the rapid conformational dynamics found in heterogeneous catalysts but has historically been restricted by its low sensitivity, limiting the detail with which structures can be resolved. In this work, we apply solid-state NMR and dynamic nuclear polarization, in combination with density functional theory modeling, to reveal the high-resolution structure and motional freedom of a scandium supported complex in three dimensions. The results are contrasted with the study of the analogous homoleptic complex in the crystalline state, highlighting the impacts that surface structure may have on the dynamics of supported complexes.

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

Ion emission from warm dense matter produced by irradiation with a soft x-ray free-electron laser

Here we report on an experiment performed at the FLASH2 free-electron laser (FEL) aimed at producing warm dense matter via soft x-ray isochoric heating. In the experiment, we focus on study of the ions emitted during the soft x-ray ablation process using time-of-flight electron multipliers and a shifted Maxwell–Boltzmann velocity distribution model. We find that most emitted ions are thermal, but that some impurities chemisorbed on the target surface, such as protons, are accelerated by the electrostatic field created in the plasma by escaped electrons. The morphology of the complex crater structure indicates the presence of several ion groups with varying temperatures. We find that the ion sound velocity is controlled by the ion temperature and show how the ion yield depends on the FEL radiation attenuation length in different materials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

First-principles design of a single-atom–alloy propane dehydrogenation catalyst

The complexity of heterogeneous catalysts means that a priori design of new catalytic materials is difficult, but the well-defined nature of single-atom–alloy catalysts has made it feasible to perform unambiguous theoretical modeling and precise surface science experiments. Herein we report the theory-led discovery of a rhodium-copper (RhCu) single-atom–alloy catalyst for propane dehydrogenation to propene. Although Rh is not generally considered for alkane dehydrogenation, first-principles calculations revealed that Rh atoms disperse in Cu and exhibit low carbon-hydrogen bond activation barriers. Surface science experiments confirmed these predictions, and together these results informed the design of a highly active, selective, and coke-resistant RhCu nanoparticle catalyst that enables low-temperature nonoxidative propane dehydrogenation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Scalable Hot-Water-Repellent Superhydrophobicity via Thermal Insulation

Superhydrophobic surfaces, which rely on a combination of surface texture and chemistry, often lose their repellent behavior when contacted by hot water (≳40 °C) because the impinging hot water replaces the requisite air layer within the surface texture via evaporation and recondensation. In contrast to previous approaches targeting this condensation-induced failure mode that rely on intricately tailored surface structures or complex chemical treatments, we present a scalable approach based on thermal design: the multilayered insulated superhydrophobic (MISH) coating mitigates condensation-induced failure by preventing heat transfer. Superhydrophobicity is retained at impinging water temperatures up to 90 °C, with durability demonstrated via long-term (>1 million impacts) droplet impingement experiments. We explain the mechanism for this approach with a detailed thermal model; the model reveals that the underlying physical behavior is self-similar across coating parameters and impinging fluid temperatures. Finally, the MISH coating accommodates curved geometries and large surfaces, and it is over 4 orders of magnitude less expensive than cleanroomnanofabricated alternatives, indicating promise for practical use in the energy sector, chemical processing, and the food and medical industries.

coating materials↗
DOE OSTI2021

Interface creation on a mixed-terminated perovskite surface

In the field of complex oxide heterostructures, understanding of the initial substrate surface can be critical to fundamental studies regarding the development of emergent properties at the film–substrate interface. For this reason, a considerable amount of effort has gone into the development of techniques to achieve surfaces with single termination for a variety of perovskite single crystals. However, a decisive understanding of how an interface is created when epitaxial growth occurs on a mixed terminated surface remains lacking. Employing in situ synchrotron X-ray scattering during thin film growth by molecular beam epitaxy, we investigate the initial stages of growth on (LaAlO 3 )(Sr 2 AlTaO 6 ) (001) substrates with mixed termination. Using LaNiO 3 as a model system, we find that the surface layers of the substrate restructure during deposition such that while a NiO 2 monolayer is weakly bound, a LaO monolayer bonds strongly, effectively incorporating with (Al, Ta)O 2 from the surface and forming a La(Al, Ta)O 3 ultrathin film. <!--/abstract content--><!--fulltext content--> With regard to the synthesis of high-quality complex oxide heterostructures, it is important that the substrate meet an array of criteria related to the crystal structure, lattice parameter, thermodynamic properties, electrical and optical properties, and so on. In particular, the surface of the substrate should be atomically smooth and exhibit the step-terrace structure ideal for epitaxial thin film growth. Perovskite oxides with the formula ABO 3 have two possible (001) surfaces: AO (A-site termination) and BO 2 (B-site termination). The ability to consistently achieve one of these surface terminations on SrTiO 3 , i.e., TiO 2 , has helped SrTiO 3 become the predominant oxide in the field.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Plasmon coupling in topological insulator multilayers

Topological insulators (TIs) house two-dimensional Dirac plasmons on their surfaces. In TI thin films, plasmons on the top and bottom surfaces couple electrostatically, giving rise to an acoustic and an optical plasmon mode. By extension, a superlattice comprising TI layers and trivially-insulating layers could house multiple complex plasmon modes which could be used to create a new type of Dirac metamaterial. In this paper, we synthesize TI superlattices, fabricate them into stripe arrays, characterize their optical and plasmonic properties, and model the samples using transfer matrices. Furthermore, we excite plasmon modes that couple to the phonons in the superlattice, resulting in hybrid plasmon phonon polaritons. These modes are modeled using an analytical Fano resonance model and the extracted resonant positions are reproduced by transfer matrix modeling. We also excite an epsilon-near-zero mode in the top dielectric material (Bi 0.5 In 0.5 ) 2 Se 3 . Understanding the behavior of the polariton modes in this complex system will lend insight into the many-body interaction in low-dimensional systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Calculation of the Heat Transfer Coefficient in the Outer Body for a Rotational Detonation

Unsteady heat transfer characterization on the combustion surfaces of Rotational Detonation Engines (RDE) is not well understood. It is generally thought that the complex nature of the unsteady, reacting, compressible fluid flow inside the combustion anulus of the RDE causes the convective heat transfer coefficient to be significantly higher than it is in other applications. Empirical models that have been used to analyze this strictly apply to steady flows where dimensionless groups can be employed. The reacting flow fields that are characteristic of RDEs are inherently compressible, three dimensional, unsteady, and turbulent, having properties that change by orders of magnitude throughout the flow field. They will therefore contain multiple length scales and time scales operating everywhere in the flow during all times. Because of this it is not likely that the RDE flow fields will lend themselves to explanation using simple dimensionless parameters. The dimensionless groups have meaning only in situations where length scales and time scales are singular and well defined. In spite of this it may be possible to get a relatively good idea of what the convection heat transfer coefficient is. In this work a numerical study is performed where the inside wall surface temperature distribution in the RDE outer body is systematically changed over a given range that would be characteristic of the start-up flows inside an RDE. For each case, temperature distributions inside the outer containment wall of the RDE was calculated and compared with experimental data. The closet match can then be used to directly calculate the convection heat transfer coefficient on the inside surface of the RDE.

VanOsdol, John↗
DOE OSTI2025

Closing the Loop between In Situ Stress Complexity and EGS Fracture Complexity

We present an agent-guided approach to CAD geometry decomposition that automates hex/hybrid meshing with graph neural networks (GNNs) to accelerate next-generation ModSim workflows. Our end-to-end pipeline (i) reduces 3D boundary-representation (B-Rep) models to a 2D chordal axis skeleton (CAT) and then to a 1D bipartite graph of surface and curve nodes, (ii) assigns per node labels as Cubit® WebCut actions, (iii) trains a multi-action GNN under supervised learning, and (iv) predicts five surface-node and three curve-node actions on out-of-distribution test geometries. Each graph node carries geometric, topological, and meshing attributes drawn from the B-Rep “skin” and CAT “skeleton,” with two-way mappings across 3D↔2D↔1D representations to maintain traceability back to 3D CAD. The supervised learning model exhibits stable convergence of the binary cross-entropy loss and achieves 98.7% accuracy on unseen lattice models. To operationalize decision-making, we rank predicted commands by geometric significance and prototyped the agent-guided workflow through the Cubit® Meshing PowerTool GUI. As a stretch goal, we explore reinforcement learning (RL) to reduce or remove label requirements and to learn policies for action sequences that maximize total reward (e.g., size of hex-meshable regions and resulting hex mesh quality). When all-hex meshing is not feasible, the agent assists in producing hybrid meshes—prioritizing hex in critical regions and transitioning to tetrahedral elements (tets) elsewhere—maintaining fidelity while ensuring robustness. The overarching objective is to replace manual, heuristics-based decomposition with data-driven, reproducible automation, cutting meshing turnaround time by orders of magnitude. We anticipate direct impact on simulation workflows through intelligent, scalable decomposition of complex CAD models into hex-meshable subdomains.

42 ENGINEERING↗
DOE OSTI2023

Mechanisms of Ethylene Epoxidation over Silver from Machine Learning-Accelerated First-Principles Modeling and Microkinetic Simulations

In this work we employed machine learning-augmented density functional theory (DFT) thermodynamic calculations to assess the stability of different AgO x structures under catalytic ethylene epoxidation reaction conditions. We found that there are multiple AgO x surface motifs that could co-exist under the relevant conditions. These included Ag surface oxides (e.g., AgO_p(4 × 4) and Ag 1.83 O) and atomic oxygen-covered Ag(111) surfaces. Furthermore, we employed DFT calculations to evaluate the energetics of different reaction mechanisms by which ethylene and oxygen can react on these surfaces. These studies revealed several energetically viable reaction pathways for ethylene epoxidation. Microkinetic modeling analyses, based on the DFT-calculated reaction pathways, showed that ethylene epoxidation can proceed on all surfaces and that multiple pathways, including those involving Langmuir–Hinshelwood and Eley–Rideal mechanisms, could be involved in selective and unselective reactions. The diversity of mechanisms that we discovered in the context of the relatively simple ethylene epoxidation reaction on Ag suggests that the richness and complexity of surface chemistry are most likely a rule rather than an exception in heterogeneous catalytic chemical transformations on metal surfaces and that the concept of a single or even a dominant mechanism and reaction intermediates might need to be revisited for many reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Predicting Pulsed-Laser Deposition SrTiO 3 Homoepitaxy Growth Dynamics Using High-Speed Reflection High-Energy Electron Diffraction

Pulsed-laser deposition (PLD) is a powerful technique for growing complex oxides with controlled stoichiometry. To understand growth dynamics therein, it is common to leverage in situ spectroscopies, such as reflection high-energy electron diffraction (RHEED), to monitor surface crystallinity. Most commercial systems rely on video-rate cameras operating at 60-120 Hz that lack sufficient temporal resolution to capture growth dynamics at practical deposition frequencies. Here, a high-speed platform to record in situ dynamics via RHEED at >500 Hz is implemented. An open-source analysis package is designed to fit diffraction spots to 2D Gaussians, allowing single-pulse surface reconstruction kinetics extraction. Using homoepitaxially deposited (001)-oriented SrTiO 3 as a model system, we demonstrate how high-speed RHEED can provide real-time insight into growth processes obscured by slower acquisition systems. By fitting the single-pulse intensity to a set of exponential functions, we observe changes in the characteristic decay time and mechanism correlated to the substrate step width and surface termination. We observe distinct surface effects, with diffraction intensity decaying on lower-energy TiO 2 -terminated surfaces and stabilizing on SrO- or mixed-terminated surfaces. Similarly, using an exponential model, the extracted characteristic time of adatom deposition decreases with increased density of bonding sites associated with mixed termination and narrower step widths. Ultimately, this work shows how increasing RHEED temporal resolution can uncover new insights into growth processes, with practical implications for the design and control of PLD processes. This experimental platform provides new capabilities to enable data-driven machine learning analysis and autonomous control systems to enhance the complexity and fecundity of PLD.

(SrO)↗
DOE OSTI2020

Soil Respiration Response to Rainfall Modulated by Plant Phenology in a Montane Meadow, East River, Colorado, USA

Soil respiration is a primary component of the terrestrial carbon cycle. However, predicting the response of soil respiration to climate change remains a challenge due to the complex interactions between environmental drivers, especially plant phenology, temperature, and soil moisture. In this study, we use a 1-D diffusion-reaction model to calculate depth-resolved CO 2 production rates from soil CO 2 concentrations and surface efflux observations in a subalpine meadow in the East River watershed, CO. Modeled rates are compared to in situ soil temperature and moisture conditions and MODIS satellite enhanced vegetation index (EVI) representing plant phenology across three hydrologically distinct growing seasons from 2016-2018. While soil respiration correlated with temperature on diel timescales (p<0.05), seasonal variability was dominated by soil moisture and plant phenology (p<0.05). We observed significant respiration increases in response to precipitation events; however, magnitude and duration were significantly higher in 2017 than 2016 despite similar wetting characteristics. Based on MODIS EVI, we suggest the respiration response to rainfall is controlled by plant phenology, which in turn reflects the capacity of plants to respond to precipitation via increased photosynthesis and autotrophic respiration, behavior that is not captured in typical soil respiration pulse models. Projected changes in montane climate such as earlier snowmelt and prolonged fore-summer drought may decrease soil respiration fluxes by decreasing the overlap between peak productivity and the summer monsoon. Lastly, we observed significant late-season CO 2 fluxes from the deep sub-soil (>165 cm) that support growing evidence for the importance of sub-soil processes in driving integrated respiration fluxes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Anolyte Enhances Catalyst Utilization and Ion Transport Inside a CO 2 Electrolyzer Cathode

Electrochemical CO 2 reduction is a promising technology to capture and convert CO 2 to valuable chemicals. High Faradaic efficiencies of CO 2 reduction products are achieved with zero-gap alkaline CO 2 electrolyzers with a supporting electrolyte at the anode (anolyte). Herein, we investigate the effect of anolyte on the electrode properties such as catalyst utilization, ionic accessibility etc. of a CO 2 reduction cathode using electrochemical techniques and cell configurations that avoid the complexities related to co-electrolysis. Using 1M KOH as the anolyte and a Cu gas-diffusion-electrode with low Nafion content as the model CO 2 reduction electrode, we find that electrode capacitance (proxy for electrochemically active surface area) and ionic conductivity inside the cathode increase approximately 4 and 447 times, respectively, in presence of KOH. Liquid anolyte wets the electrode’s pore structure more efficiently than capillary condensation of feed water vapor. The ionomer coverage is very low, and its distribution inside the electrode is highly fragmented. Surface ion conduction mechanisms inside the electrode are orders of magnitude lower than the bulk ion conduction in presence of anolyte. This study shows that when an anolyte (e.g., KOH) is used, catalyst utilization and ionic accessibility inside the electrode increase significantly.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Experimental and Numerical Investigations on Dynamic Mechanical Properties of TPMS Structures

Triply Periodic Minimal Surface (TPMS) lattice structures have been of increasing interest due to their light weighting, enhanced mechanical properties, and energy absorption characteristics for automotive and biomedical applications. With the advent of additive manufacturing and geometric modeling software, TPMS lattices with complex geometries can be realized. In this work, TPMS lattice structures were fabricated with PLA using fused filament fabrication (FFF) and their dynamic properties are characterized through drop tower experiments. Although lightweight TPMS lattices are beneficial for their impact absorption capability, most of the existing works are limited to quasi-static compression and dynamic impact tests are rarely performed. The current study investigates the stress-strain and energy absorption characteristics of TPMS lattices through drop tower testing and numerical modeling. Finite element modeling for TPMS lattices is carried out to validate the experimental responses. The mechanical properties, deformation, and failure mechanisms of TPMS lattices under dynamic impact are summarized for potential future applications.

Pokkalla, Deepak↗
DOE OSTI2021

Evaluating Probability of Containment Effectiveness at a GCS Sites using integrated assessment modeling approach with Bayesian decision Networks

Improved scientific and engineering understanding of the behavior of geologic CO2 storage together with established regulatory framework and incentive structures raise the prospects for accelerated, large-scale deployment of this greenhouse gas emissions reduction approach. Incentive structures call for the establishment of appropriate verification and accounting approaches to support claims of the integrity of a geologic storage complex and to justify taking credit for long-term storage. In this study, we present a framework for assessing the probability of containment effectiveness over the lifetime of a geologic carbon storage site (e.g., after 70 years of injection and post-injection site performance) using forward stochastic model realizations based on site characterization data and using a monitoring-informed Bayesian network based on hypothetical detectability from surface seismic surveys over the site injection and post-injection phases. The National Risk Assessment Partnership’s open-source Integrated Assessment Model (NRAP-Open-IAM) was utilized to develop an ensemble of 10,000 a priori stochastic forecasts of CO2 containment. Those simulations were used to train the Bayesian network model to estimate the prior probabilities of the CO2 leakage mass into overlying, monitorable aquifers considering the uncertainties in the reservoir properties, permeability of potentially leaky wells and the overlying aquifers. The conditional probabilities in the Bayesian network were either learned from the NRAP-Open-IAM simulations or derived from the predefined detection thresholds for the monitoring method. Observations obtained from monitoring, over time during the site operation phases were then used to generate updated posterior probabilities of containment (and any loss from containment) in the Bayesian network by propagating the prior probabilities through the conditional probabilities. We demonstrate how to construct and use the Bayesian network for verifying the long-term storage complex effectiveness informed by monitoring based on the NRAP-Open-IAM simulations previously developed for the FutureGen 2.0 site. This approach may have relevance for stake holders to demonstrate secure geologic storage, provide a defensible, probabilistic approach to claim credit for geologic storage, and to estimate the likelihood that any fraction of the claimed credit may need to be refunded to the creditor based on available monitoring information.

Bayesian network, Risk assessment, Monitoring, car↗
DOE OSTI2022

Molecular-level understanding of metal ion retention in clay-rich materials

Clay minerals retain or adsorb metal ions in the Earth’s critical zone. Rocks, sediments and soils rich in clay minerals can concentrate rare earth elements (REEs) in ion adsorption-type deposits (IADs) and are similarly effective at metallic contaminant remediation. However, the molecular-scale chemical and physical mechanisms of metal ion retention remain only partly understood. Here, we describe the nature, location and energy requirements of metal retention at clay mineral surfaces. Retention originates mainly from electrostatic interactions during cation exchange at low pH and chemical bonding in surface complexation and precipitation at neutral and high pH. Surface complexation can induce surface redox reactions and precipitation mechanisms including neoformation of clay mineral layered structures. In IADs, outer-sphere adsorption is the major retention mechanism of REE ions. By contrast, the use of clay minerals in pollution control relies on various mechanisms that can coexist, including cation exchange, surface complexation and nucleation growth. To more effectively leverage clay mineral–metal interactions in resource recovery and contaminant remediation, complex mechanisms such as surface precipitation and redox reactions must be better understood; for instance, by utilizing advances in quantum mechanical calculations, close combination between synchrotron and simulation techniques, and upscaling of molecular-level information in macroscopic thermokinetic predictive models.

54 ENVIRONMENTAL SCIENCES↗