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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Capture of volatile RuO 4 from oxidized simulated used nuclear fuel solutions

Ruthenium is a challenging fission product in used nuclear fuel (UNF) reprocessing due to its complex redox chemistry, variable speciation in nitric acid, partial extractability, and volatility. This work presents a strategy for Ru removal based on the volatilization of RuO 4 using the strong oxidant sodium bismuthate, followed by RuO 2 deposition onto various substrates. Among the materials tested, polymer-based substrates such as polyolefin wax film (Parafilm®), exhibited superior performance, achieving up to near-quantitative Ru removal from solution. After dissolution of the substrate, 99.6% of the Ru was recovered as RuO 2 . The deposition mechanism onto the polyolefin wax film involves both physisorption and chemical reaction through oxidative cleavage of olefinic bonds within the polymer. In contrast, on inorganic substrates such as Al foil, RuO 4 undergoes incomplete surface adsorption and reduction, as confirmed by FTIR and XPS analyses. This approach remains effective under conditions of simulated oxidation of UNF solutions, selectively removing Ru while leaving other fission products in solution. As a result, capture of RuO 4 offers a practical and efficient strategy for ruthenium decontamination and recovery, offering a route for integration into existing UNF reprocessing flowsheets to enhance overall process safety and performance.

Ruthenium↗
DOE OSTI2022

Can Common Pool Resource Theory Catalyze Stakeholder-Driven Solutions to the Freshwater Salinization Syndrome?

Freshwater salinity is rising across many regions of the United States as well as globally, a phenomenon called the freshwater salinization syndrome (FSS). The FSS mobilizes organic carbon, nutrients, heavy metals, and other contaminants sequestered in soils and freshwater sediments, alters the structures and functions of soils, streams, and riparian ecosystems, threatens drinking water supplies, and undermines progress toward many of the United Nations Sustainable Development Goals. There is an urgent need to leverage the current understanding of salinization’s causes and consequences–in partnership with engineers, social scientists, policymakers, and other stakeholders–into locally tailored approaches for balancing our nation’s salt budget. In this feature, we propose that the FSS can be understood as a common pool resource problem and explore Nobel Laureate Elinor Ostrom’s social-ecological systems framework as an approach for identifying the conditions under which local actors may work collectively to manage the FSS in the absence of top-down regulatory controls. We adopt as a case study rising sodium concentrations in the Occoquan Reservoir, a critical water supply for up to one million residents in Northern Virginia (USA), to illustrate emerging impacts, underlying causes, possible solutions, and critical research needs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Probing Active Sites in Cu x Pd y Cluster Catalysts by Machine-Learning-Assisted X-ray Absorption Spectroscopy

Size-selected clusters are important model catalysts because of their narrow size and compositional distributions, as well as enhanced activity and selectivity in many reactions. Still, their structure-activity relationships are, in general, elusive. The main reason is the difficulty in identifying and quantitatively characterizing the catalytic active site in the clusters when it is confined within subnanometric dimensions and under the continuous structural changes the clusters can undergo in reaction conditions. Using machine learning approaches for analysis of the operando X-ray absorption near-edge structure spectra, we obtained accurate speciation of the Cu x Pd y cluster types during the propane oxidation reaction and the structural information about each type. As a result, we elucidated the information about active species and relative roles of Cu and Pd in the clusters.

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

Heterostructured Au–Ir Catalysts for Enhanced Oxygen Evolution Reaction

Electrochemical water splitting operated under acidic conditions provides a clean approach to generate hydrogen fuels. Currently, the sluggish kinetics of oxygen evolution reaction (OER) at the anode is a bottleneck limiting the acidic water splitting. Here, we report that the OER activity of Ir, one of the most commonly used OER catalysts, can be boosted by forming phase boundaries with Au. Mixed Au and Ir catalysts were synthesized on carbon paper electrodes, which underwent structural evolution under the OER environment to form an Au-Ir interface-rich structure. Compared with Ir catalyst, which requires an overpotential of ~393 mV to achieve a current density of 10 mA/cm 2 in 0.1 M HClO 4 electrolyte, the evolved Au-Ir catalyst shows a lower overpotential at ~351 mV. X-ray photoelectronic spectrum (XPS) study, in conjunction with electrochemical analysis on the surface-site-normalized activity, reveals that the improved OER performance is due to the presence of Au/Ir interfaces in the catalysts. In addition to Ir, the strategy of accelerating OER via Au/Ir interfaces has been further applied to IrCo, IrNi, and IrCu alloy catalysts. Here, with the broad applicability of the strategy demonstrated, this study opens a new route to design OER catalysts for efficient acidic water splitting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Reduction of CO to Methanol with Recyclable Organic Hydrides

We report the reaction steps for the selective conversion of a transition metal carbonyl complex to a hydroxymethyl complex that releases methanol upon irradiation with visible light have been successfully quantified in acetonitrile solution with dihydrobenzimidazole organic hydride reductants. Dihydrobenzimidazole reductants have been shown to be inactive toward H 2 generation in the presence of a wide range of proton sources and have been regenerated electrochemically or photochemically. Specifically, the reaction of cis-[Ru(bpy) 2 (CO) 2 ] 2+ (bpy = 2,2'-bipyridine) with one equivalent of a dihydrobenzimidazole quantitatively yields a formyl complex, cis-[Ru(bpy) 2 (CO)(CHO)] + , and the corresponding benzimidazolium on a seconds time scale. Kinetic experiments revealed a first-order dependence on the benzimidazole hydride concentration and an unusually large kinetic isotope effect, inconsistent with direct hydride transfer and more likely to occur by an electron transfer-proton-coupled electron transfer (EΤ-PCET) or related mechanism. Further reduction/protonation of cis-[Ru(bpy) 2 (CO)(CHO)] + with two equivalents of the organic hydride yields the hydroxymethyl complex cis-[Ru(bpy) 2 (CO)(CH 2 OH)] + . Visible light excitation of cis-[Ru(bpy) 2 (CO)(CH 2 OH)] + in the presence of excess organic hydride was shown to yield free methanol. Identification and quantification of methanol as the sole CO reduction product was confirmed by 1 H NMR spectroscopy and gas chromatography. The high selectivity and mild reaction conditions suggest a viable approach for methanol production from CO, and from CO 2 through cascade catalysis, with renewable organic hydrides that bear similarities to Nature's NADPH/NADP + .

14 SOLAR ENERGY↗
DOE OSTI2020

Universal and versatile morphology engineering via hot fluorous solvent soaking for organic bulk heterojunction

After explosive growth of efficiency in organic solar cells (OSCs), achieving ideal morphology of bulk heterojunction remains crucial and challenging for advancing OSCs into consumer market. Herein, by utilizing the amphiphobic nature and temperature-dependent miscibility of fluorous solvent, hot fluorous solvent soaking method is developed to optimize the morphology with various donor/acceptor combinations including polymer/small-molecule, all-polymer and all-small-molecule systems. By immersing blend film into hot fluorous solvent which is utilized as liquid medium with better thermal conductivity, the molecular reorganization is accelerated. Furthermore, fluorous solvent can be miscible with the residue of chloroform and chloronaphthalene above upper critical solution temperature. This mixed solvent diffuses around inside the active layer and selectively promotes molecular reorganization, leading to optimized morphology. Compared to widely-used thermal annealing, this approach processed under mild conditions achieves superior photovoltaic performance, indicating the practicality and universality for morphological optimization in OSCs as well as other optoelectronic devices.

14 SOLAR ENERGY↗
DOE OSTI2022

In situ electrochemical recomposition of decomposed redox-active species in aqueous organic flow batteries

Aqueous organic redox flow batteries (AORFBs) offer a safe and potentially inexpensive solution to the problem of storing massive amounts of electricity produced from intermittent renewables. However, molecular decomposition is the major barrier preventing AORFBs from being commercialized. Structural modifications can improve molecular stability at the expense of increased synthetic cost and molecular weight. Utilizing 2,6-dihydroxy-anthraquinone (DHAQ), without further structural modification, we demonstrate that electrochemical regeneration could be a viable route to achieve low-cost, long-lifetime AORFBs. In situ (online) NMR and EPR and complementary electrochemical analyses reveal that decomposition compounds i.e., 2,6-dihydroxy-anthrone (DHA) and its tautomer, 2,6-dihydroxy-anthranol (DHAL), can be converted back to DHAQ in two steps: first DHA(L) 2- are oxidized to the dimer (DHA) 2 4- at - 0.32 V vs. SHE by one-electron transfer; subsequently, the (DHA) 2 4- is oxidized to DHAQ 2- at +0.57 V vs. SHE by three-electron transfer. Electrochemical regeneration rejuvenates not only DHAQ 2- , but also the positive electrolyte – rebalancing the states of charge of both electrolytes without introducing extra ions. We demonstrate the repeated capacity recovery with DHAQ | potassium ferro-/ferricyanide flow battery in basic conditions, and show the approach is also effective for anthraquinone-2,7-disulfonate in acid. Electrochemical regeneration strategies may extend the useful lifetime of many water-soluble organic molecules with anthraquinone core structures in electrochemical cells.

25 ENERGY STORAGE↗
DOE OSTI2020

Electronic band contraction induced low temperature methane activation on metal alloys

The catalytic conversion of methane under mild conditions is an appealing approach to selectively produce value-added products from natural gas. Catalysts which can chemisorb methane can potentially overcome challenges associated with its high stability and achieve facile activation. Although transition metals can activate C–H bonds, chemisorption and low-temperature conversion remain elusive on these surfaces. The broad electronic bands of metals can only weakly interact with the methane orbitals, in contrast to specific transition metal oxide and supported metal cluster surfaces which are now recognized to form methane σ-complexes. Here, we report methane chemisorption can, remarkably, occur on metal surfaces via electronic band contraction and localization from metal alloying. From a broad screening including single atom and intermetallic alloys in various substrates, we find early transition metals as promising metal solutes for methane chemisorption and low-temperature activation. These findings demonstrate a combinatorial diversity of possible candidates in earth abundant metal alloys with this attractive catalytic behavior.

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

Plasma expansion and relativistic filamentation in intense laser-irradiated cone targets

We report that compound parabolic concentrator (CPC) cone targets have been shown to produce increased MeV photons on the NIF-ARC by 10× over flat targets. Multiple x-ray frames can potentially be generated by firing the NIF-ARC's beamlets into distinct cone targets at few nanosecond relative delays. This requires that the cone targets with delayed beams are not degraded by their proximity to previous targets. One concern is that the spatial wings of a beam fired into one target can fall on neighboring targets, producing a preformed plasma that may interfere with laser light reaching the tip of the cone. In this work, 3D hydra simulations of realistic targets and beam parameters show that hundreds of micrometer scale length preplasmas are produced in cones within 1 mm of the laser spot. 2D particle-in-cell simulations of the intense main pulse in this preplasma indicate a density threshold for the onset of relativistic filamentation in our conditions. Applying our modeling approach to a NIF-ARC shot with an intentional 15 J prepulse yields good agreement with experimental results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Polariton-assisted incoherent to coherent excitation energy transfer between colloidal nanocrystal quantum dots

Here, we explore the dynamics of energy transfer between two nanocrystal quantum dots placed within an optical microcavity. By adjusting the coupling strength between the cavity photon mode and the quantum dots, we have the capacity to fine-tune the effective coupling between the donor and acceptor. Introducing a non-adiabatic parameter, γ, governed by the coupling to the cavity mode, we demonstrate the system’s capability to shift from the overdamped Förster regime (γ $\ll$ 1) to an underdamped coherent regime (γ $\gg$ 1). In the latter regime, characterized by swift energy transfer rates, the dynamics are influenced by decoherence time. To illustrate this, we study the exciton energy transfer dynamics between two closely positioned CdSe/CdS core/shell quantum dots with sizes and separations relevant to experimental conditions. Employing an atomistic approach, we calculate the excitonic level arrangement, exciton–phonon interactions, and transition dipole moments of the quantum dots within the microcavity. These parameters are then utilized to define a model Hamiltonian. Subsequently, we apply a generalized non-Markovian quantum Redfield equation to delineate the dynamics within the polaritonic framework.

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

A high-resolution large-eddy simulation framework for wildland fire predictions using TensorFlow

Background: Wildfires are becoming more severe, so we need improved tools to predict them over a wide range of conditions and scales. One approach towards this goal entails the use of coupled fire/atmosphere modelling tools. Although significant progress has been made in advancing their physical fidelity, existing tools have not taken full advantage of emerging programming paradigms and computing architectures to enable high-resolution wildfire simulations. Aims: The aim of this study was to present a new framework that enables landscape-scale wildfire simulations with physical representation of combustion at an affordable cost. Methods: We developed a coupled fire/atmosphere simulation framework using TensorFlow, which enables efficient and scalable computations on Tensor Processing Units. Key Results: Simulation results for a prescribed fire were compared with experimental data. Predicted fire behavior and statistical analysis for fire spread rate, scar area, and intermittency showed overall reasonable agreement. Scalability analysis was performed, showing close to linear scaling. Conclusions: While mesh refinement was shown to have less impact on global quantities, such as fire scar area and spread rate, it benefits predictions of intermittent fire behavior, buoyancy-driven dynamics, and small-scale turbulent motion. Implications: This new simulation framework is efficient in capturing both global quantities and unsteady dynamics of wildfires at high spatial resolutions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Machine Learning in Infectious Disease for Risk Factor Identification and Hypothesis Generation: Proof of Concept Using Invasive Candidiasis

Machine learning (ML) models can handle large data sets without assuming underlying relationships and can be useful for evaluating disease characteristics, yet they are more commonly used for predicting individual disease risk than for identifying factors at the population level. We offer a proof of concept applying random forest (RF) algorithms to Candida-positive hospital encounters in an electronic health record database of patients in the United States. Candida-positive encounters were extracted from the Cerner HealthFacts database; invasive infections were laboratory-positive sterile site Candida infections. Features included demographics, admission source, care setting, physician specialty, diagnostic and procedure codes, and medications received before the first positive Candida culture. We used RF to assess risk factors for 3 outcomes: any invasive candidiasis (IC) vs non-IC, within-species IC vs non-IC (eg, invasive C. glabrata vs noninvasive C. glabrata), and between-species IC (eg, invasive C. glabrata vs all other IC). Fourteen of 169 (8%) variables were consistently identified as important features in the ML models. When evaluating within-species IC, for example, invasive C. glabrata vs non-invasive C. glabrata, we identified known features like central venous catheters, intensive care unit stay, and gastrointestinal operations. In contrast, important variables for invasive C. glabrata vs all other IC included renal disease and medications like diabetes therapeutics, cholesterol medications, and antiarrhythmics. Known and novel risk factors for IC were identified using ML, demonstrating the hypothesis-generating utility of this approach for infectious disease conditions about which less is known, specifically at the species level or for rarer diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Optimal function estimation with photonic quantum sensor networks

The problem of optimally measuring an analytic function of unknown local parameters each linearly coupled to a qubit sensor is well understood, with applications ranging from field interpolation to noise characterization. Here we resolve a number of open questions that arise when extending this framework to Mach-Zehnder interferometers and quadrature displacement sensing. In particular, we derive lower bounds on the achievable mean square error in estimating a linear function of either local phase shifts or quadrature displacements. In the case of local phase shifts, these results prove, and somewhat generalize, a conjecture by Proctor []. For quadrature displacements, we extend proofs of lower bounds to the case of arbitrary linear functions. We provide optimal protocols achieving these bounds up to small (multiplicative) constants and describe an algebraic approach to deriving new optimal protocols, possibly subject to additional constraints. Using this approach, we prove necessary conditions for the amount of entanglement needed for any optimal protocol for both local phase and displacement sensing. Published by the American Physical Society 2024

Bringewatt, Jacob↗
DOE OSTI2024

Ultrafast Annealing Improves SNR and Long-Term Stability of a Highly Multiplexed Line-by-Line FBG Array Inscribed by Femtosecond Laser in a Coreless Fiber for Extreme-Temperature Applications

This study reports the fabrication of a fourth-order line-by-line fiber Bragg grating (FBG) array using femtosecond laser inscription within a highly multimode coreless optical fiber, with a particular focus on achieving substantial multiplexing capabilities. An ultrafast annealing procedure is employed, resulting in an impressive enhancement of the FBG sensor’s fringe visibility by approximately 13 dB, signifying a notable improvement of approximately ~4 dB. This substantial enhancement contributes to the long-term stability and performance of the multiplexed FBG array in extreme-temperature conditions. The systematic fabrication approach employed for the multiplexed FBG array guarantees a high signal-to-noise ratio (SNR) for each individual FBG within the array. This FBG array is intended for extreme-temperature applications, addressing limitations associated with traditional FBGs based on doped optical fibers, including SNR degradation and temperature-induced fringe drift. Testing at temperatures up to 1120 °C demonstrates the FBG array’s stability without fluctuations in readings. Furthermore, it endures seven heat cycles, spanning from 500 °C to 1120 °C, over 60 h, exhibiting outstanding thermal stability. Furthermore, this highly multiplexed FBG array with an ultrafast annealing approach holds promise for extreme-temperature environments, such as steelmaking, where precise and reliable distributed temperature monitoring is imperative.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

To Fail or not to Fail: An Exploration of Machine Learning Techniques for Predictive Maintenance

Predictive maintenance refers to the ability to predict when machinery or systems need to be maintained. Making an accurate prediction is quite challenging given the costs for both over-estimating (unnecessary maintenance and reduction in availability of assets) and under-estimating (untimely breakdowns and possible loss of equipment or lives). To address these challenges researchers were able to develop new approaches for analyzing oil samples taken extracting samples from oil-wetted machinery that may provide information critical to developing predictive capabilities. We consider the problem from both supervised (though data limited) and unsupervised approaches and provide a first look into a data driven approach for identification of condition indicators. Through this work we identify a collection of candidate features that can form the basis of condition indicators for both a high level discrimination of failure vs. normal operation as well as a set for potential failure mode identification. Finally, we present an anomaly detection framework for detecting failures which can be a viable solution for an onboard analysis tool in deployed systems.

predictive maintenance, anomaly detection, Laserne↗
DOE OSTI2024

Subsampling of Parametric Models with Bifidelity Boosting

Least squares regression is a ubiquitous tool for building emulators (a.k.a. surrogate models) of problems across science and engineering for purposes such as design space exploration and uncertainty quantification. When the regression data are generated using an experimental design process (e.g., a quadrature grid) involving computationally expensive models, or when the data size is large, sketching techniques have shown promise at reducing the cost of the construction of the regression model while ensuring accuracy comparable to that of the full data. However, random sketching strategies, such as those based on leverage scores, lead to regression errors that are random and may exhibit large variability. To mitigate this issue, we present a novel boosting approach that leverages cheaper, lower-fidelity data of the problem at hand to identify the best sketch among a set of candidate sketches. This in turn specifies the sketch of the intended high-fidelity model and the associated data. We provide theoretical analyses of this bifidelity boosting (BFB) approach and discuss the conditions the low- and high-fidelity data must satisfy for a successful boosting. In doing so, we derive a bound on the residual norm of the BFB sketched solution relating it to its ideal, but computationally expensive, high-fidelity boosted counterpart. Finally, empirical results on both manufactured and PDE data corroborate the theoretical analyses and illustrate the efficacy of the BFB solution in reducing the regression error, as compared to the nonboosted solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Architecture-Based Control of Temperature Gradient-Driven Water Transport in Polymer Electrolyte Fuel Cells

Temperature gradients can move water within the porous media of a polymer electrolyte fuel cell through phase-change-induced (PCI) flow. It is critical to understand PCI flow so that control and distribution of water within a fuel cell can be accomplished. This work investigates the role of architecture, specifically anode land width, on overall cell water content and distribution in the through-plane direction. A specially-designed 4.8 cm 2 fuel cell with precise thermal boundary conditions was imaged with neutrons using two different anode flow field configurations. A new, non-dimensional thermal transport number was developed which quantifies the relative influence of PCI flow on cell water transport. It was found that anode lands larger than the cathode lands cause large thermal gradients that instigate net water flux from the cathode to the anode. An asymmetric configuration with larger anode lands was found to have large changes in water content that were strongly sensitive to cell operating conditions. The thermal transport number developed here enables deduction of the net flux condition based on operating conditions and architecture. This approach enables design of high-performance systems with balanced water management.

25 ENERGY STORAGE↗