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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Industrial deposition of wavelength-shifting films for liquid argon photon detection systems

The Deep Underground Neutrino Experiment (DUNE) Phase-II Far Detector is considering an approximately 2000 m 2 photon detection system to achieve a target mean light yield of 180 PE/MeV. Meeting this requirement demands scalable, cost-effective, and high-quality wavelength-shifter (WLS) coatings capable of converting 127 nm liquid-argon scintillation light into visible photons with controlled and reproducible optical performance. We report on the successful realization of an industrial physical vapor deposition (PVD) process forp-terphenyl (pTP) coatings, adapted from vacuum deposition techniques developed for OLED display manufacturing, to produce uniform WLS layers on large-area inorganic substrates, a task traditionally challenged by adhesion and uniformity issues at organic-inorganic interfaces. Surface characterization by profilometry and spectroscopic measurements demonstrates edge-region thickness variation below 10% and emission spectra consistent with high-quality pTP reference samples. The industrial process demonstrates reproducibility, scalability, and significantly reduced production time compared to laboratory-based methods, while maintaining optical characteristics consistent with established pTP reference samples. These results establish a viable pathway for mass production of high-performance pTP coatings for DUNE FD3 and future neutrino experiments, from a coating manufacturing and process standpoint. Detector-level performance validation, including quantitative VUV conversion efficiency measurements at 127 nm, is identified as future work.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Durability of Highly Active PGM Catalyst MEA Tested Via Nitrogen and Air AST Cycling Under HDV Condition

PEMFCs are widely considered as the most promising power sources, particularly for heavy-duty vehicles (HDVs). Unfortunately, the degradation of MEAs under HDV condition remains insufficiently studied. In this work, we systematically investigated two MEAs with catalysts of Pt nanoparticles (NPs) supported over high surface area carbon black. These MEAs were tested for durability under HDV condition in nitrogen using a DOE AST protocol for 180,000 cycles, which is equivalent to 30,000 hours or 1 million miles of operation. The commercial Catalyst MEA also underwent 6,000 AST cycles in air under M2FCT condition. We comprehensively investigated the degradation of catalysts. Our results indicate that both MEAs undergo continuous performance degradation in H 2 /air and H 2 /O 2 during the AST cycling in nitrogen, where analysis employing scanning transmission electron microscopy (STEM) and inductively coupled plasma mass spectrometry (ICP-MS) reveal significant degradation behavior for Pt catalysts. The MEA exhibits more significant degradation, especially within mass transfer region, during the AST process in air. In conclusion, this study describes the long-term degradation behavior and mechanism with AST cycling in nitrogen or air governing highly efficient and durable PGM-catalyst MEA design under HDV conditions.

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

Quantum-Inspired Bayesian Sampling for Uncertainty Quantification and Machine Learning (Final Technical Report)

With increasing simulation and measurement data, machine learning and artificial intelligence have been widely used in computational decision-making of complex engineering systems. The resulting tools, such as uncertainty quantification solvers, reinforcement learning, and physics-informed machine learning, have achieved great success in critical DOE tasks such as material discovery and design, energy system modeling and control, and numerical weather and climate prediction. A core topic in scientific machine learning and artificial intelligence is Bayesian inference: given an observed data set, people want to estimate the posterior distribution of a (possibly large) number of hidden parameters. Due to the flexibility and weak assumptions, Bayesian sampling has been the mainstream Bayesian inference solvers despite the rapid progress of approximate Bayesian inference. Classical Bayesian sampling methods such as Markov-chain Monte Carlo suffer from a low-acceptance rate due to the random walk nature, therefore state-of-the-art techniques use Hamiltonian Monte Carlo and its variants to efficiently draw posterior samples in a high dimension. The key idea of Hamiltonian Monte Carlo and its variants is to simulate the Hamiltonian dynamics of a classical particle with a fixed mass, and their performance significantly degrades when the posterior distribution is highly spiky or has multiple modes. Leveraging the idea of quantum physics, this project has investigated new theory, algorithms and applications of Bayesian inference (especially Bayesian sampling). The main results include: (1) novel quantum-inspired Bayesian sampling methods that can lead to better accuracy for challenging multi-modal or spiky distributions, (2) more scalable machine learning framework leveraging tensor-compressed Bayesian inference, and (3) Bayesian and sampling approaches for verifying the robustness of continuous and binary neural networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Avancando na Transicao Energetica: Desafios e Estrategias para a Implantacao Sustentavel de FV

As the world embarks on an ambitious journey towards global decarbonization, the spotlight turns to photovoltaic (PV) technology as a cornerstone for sustainable energy solutions. This talk delves into the current status and projections of PV for the World, US and Brasil, and the necessary considerations to do this increase in manufacturing and deployment sustainably. With the projected scale of deployment, the industry faces significant challenges related to material demand and the management of PV modules at their end of life. The principles of the Circular Economy (CE) and its associated R-Actions - Reduce, Reuse, Recycle, among others - present a promising framework to address these challenges by mitigating end-of-life management and material sourcing concerns. However, traditional CE metrics, often focused solely on mass, fall short by excluding vital energy flow considerations. In this talk, we will highlight how various metrics are needed to understand sustainable PV solutions, how continuing the search for increased efficiency can significantly reduce material demands and enhance energy metrics, while strategies around material circularity and module lifetime and reliability improvements will offer substantial reductions in both material and energy demands.

Brasil↗
DOE OSTI2024

Electrothermal vaporization as a new method for pre-inspection check samples

The use of electrothermal vaporization (ETV) has not been readily applied to nuclear safeguards or pre inspection check (PIC) sample analysis, even though the technique is ideally suited for low level (pg) isotopic quantification due to its high analyte transport efficiency. Here demonstrate the ETV method for PIC safeguard analysis. The ETV system is an automated, commercial of the shelf (COTS) technology, with the capability to introduce solid samples to a mass spectrometer platform. The system has been shown to simultaneously determine uranium assay, and the major isotopic ratios for uranium and plutonium. The ETV unit has demonstrated analysis up to 50 samples a day autonomously. The utilization of this ETV methodology provide a secondary option to the current PIC analysis and offers high throughput, enhanced sensitivity, and broader isotopic detection platform.

Hexel, Cole↗
DOE OSTI2020

Gamma ray Imaging Based Methods to Improve the Accuracy of Uranium Holdup Quantification

Deposits in commercial uranium processing facilities of interest to nuclear safeguards are predominantly low enriched uranium (LEU). The shapes and sizes of holdup deposits can vary significantly, thus making it difficult to model the deposits accurately for calibration purposes. This presents a challenge to currently employed methods such as the Generalized Geometry Holdup (GGH) that rely on quantifying 235U mass by simplifying deposit shapes as a point, a line, or an area. In this work, gamma ray imaging using high energy resolution Germanium Gamma Imagers (GeGI™) is employed to determine the distribution of uranium inside the source containment. Two types of imaging methods are employed; coded-aperture imaging and Compton imaging. Gamma-ray emissions seen in different regions of the image are quantified using an inverse gamma-ray transport solver being developed at ORNL. Using measured data, the inverse method will be used to solve for unknown source parameters such as source matrix thickness, density, and attenuation due to container wall and shielding. The intrinsic efficiency of the detector is determined based on a library of built-in response functions and key dimensions of the detector (e.g., thickness and radius of the detector crystal). Measurements are performed in both imaging modalities using uranium sources of well-known masses and enrichments configured inside mocked-up holdup fixtures. Results from the two imaging modalities are intercompared. The paper presents preliminary results of the imaging measurements and the progress made in the computational methods to quantify uranium mass.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2020

Development of a Testbed for Pipeline Flushing - 20425

Pipelines which carry high-level waste within the DOE complex should be properly flushed in the cases where stationary or moving beds of solid sediment occur, or lines are prone to hydrogen gas buildup. Present guidelines establish a minimum for the amount of water (flush volume) and flush velocity values used for post-transfer flushing operations to achieve satisfactory cleaning of pipelines. However, further studies are needed to find optimal operating velocity modes/values in order to minimizing the flush volume and consequent downstream waste. These efforts are significantly helpful to DOE waste remediation sites by preserving tank storage, preventing additional waste processing, and minimizing dilution and changes in waste chemistry. An experimental test loop was recently developed for study of non-Newtonian slurry flushing at the Florida International University (FIU). This loop was designed to create sediment beds of various materials and bed heights and investigate parameters that effect the efficiency of flushing operations. The objective is to find flush velocity values/modes which lead to satisfactory cleaning of transport lines with a minimum amount of water usage. A 165 ft experimental test loop made of 3-inch carbon steel pipes was constructed and used in initial testing campaigns. This pipe loop was equipped with real-time monitoring instruments to record variation of pressure, density, mass flow rate, and temperature during testing. Post-flush in-situ no-flow evaluations were performed using ultrasonic, endoscopy, and visual inspection. Additional post-flush evaluations were conducted using filtration and density monitoring of residuals within a designated circulations loop. These provisions enable comparison of pipeline cleanness before the start and after termination of flushing operations for efficiency evaluation. This paper presents efforts associated with flushing of kaolin-water mixtures at different concentrations and with various flush volume and flush velocity values/modes. In initial testing, efforts focused on creating repeatable sediment beds inside the pipeline in both fully-flooded (no pre-flush drainage) and gravity-drained (pre-flush drained) systems. Bed characterization (i.e., measurement of sediment height and solids concentration) was conducted to ensure about consistency of initial conditions between tests. Preliminary results for flushing study of 10% vol. kaolin-water mixtures starting from a fully-flooded initial condition showed that flushing with 1-line volume (65 gallons) could remove up to 72 percent of solids from the pipeline. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Efficient and Selective Chemical Transformations in Highly Charged and Confined Nanodroplets

The acceleration of chemical reaction rates and the increased product selectivity in microdroplets compared to that in bulk solutions has become a topic of increasing interest that has been extensively characterized by electrospray ionization mass spectrometry (ESI-MS). However, the sources of this acceleration and the detailed relationships between droplet properties and resulting reaction rate acceleration are still under debate. Moreover, droplet properties are governed by multiple interrelated experimental parameters, i.e., electrospray voltage, solution flow rate, etc., which makes it difficult and time-consuming to explore this diverse parameter space using traditional manual experimental or computational approaches. In this work, we developed an automated experimental platform integrating reactions in controlled charged microdroplet environments with ESI-MS characterization and sequential hybrid Bayesian modeling, as well as an optimal experimental design framework, to achieve multidimensional parameter optimization for higher reaction turnover rates, based on a model reaction of tetraethylenepentamine (TEPA) with carbon dioxide. With the current platform, we have achieved automated scans with a range of electrospray voltages and solution flow rates, and determined and optimized parameter settings to achieve increased reaction turnovers. We have also linked this platform to the underlying properties of droplets via a hybrid model incorporating physics, high-level theoretical calculations, and machine learning (ML) approaches. The autonomous platform is broadly applicable to a range of chemical reactions relevant to DOE’s mission in chemical separations, catalysis, and materials synthesis.

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

Enabling Ultralow Volume Analysis with a High-Resolution Ion Mobility Mass Spectrometry Platform

Of all the molecules thought to exist in the universe, it is estimated that researchers only know the chemical structures of 5% of them. Identifying the chemical structures of the remaining 95% has proven extremely challenging because many molecules exhibit low abundance, are contained in small volumes (e.g., <10 nL), do not readily ionize, exhibit similar structures to other molecules, etc. No single analytical technique exists to definitively identify the structure of an unknown molecule, and thus multiple different molecular measurements are typically made (i.e., multi-modal approach). Ion mobility (IMS) and mass spectrometry (MS) are two key tools that researchers use to determine the chemical structures of unknown molecules, and recently high-resolution and ultrahigh resolution IMS-MS instruments have provided greater confidence than ever before. However, HR-IMS-MS instruments typically exhibit low ion utilization efficiency, meaning they require large amounts of sample for an analysis (e.g., >10 µL). Unfortunately, this limitation prohibits the analysis of small volume samples where many unknown molecules exist. Described herein are the efforts made to enable the analysis of ultralow volumes with an HR-IMS-MS platform. A new scanning technique, termed a ‘stuttered traveling wave scan’, was developed as a replacement for the dual-gated scanning technique and works by halting the traveling waves after allowing ions to separate and then repeatedly restarting and stopping the traveling waves to incrementally move ions from the SLIM to the Orbitrap. Ions were stored inside the SLIM while the TWs were stopped, allowing the Orbitrap to perform high-resolution mass analysis. When the Orbitrap was ready, the TWs were restarted for short periods of time (<10 ms) to move ions from the SLIM to the Orbitrap. It was discovered that lower TW amplitudes and speeds than used during IMS separation were required to produce IMS peaks with the highest signal intensities and best resolving powers. The stuttered TW scan was found to produce similar resolutions and signal intensities compared to the dual-gated scanning technique. A new IMS design possessing an intersecting ‘tee’ with a reversible traveling wave was also developed to improve ion utilization efficiency during cyclic operation, which is necessary when only a single IMS spectrum can be acquired, such as when analyzing ultralow volume samples. The new capabilities described in this report lay the groundwork for acquiring HR-IMS-MS spectra of ultralow volume biological samples, such as single cells, where HR-IMS-MS can help elucidate the structures of unknown compounds.

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

NETL’s Perspective on Storage Efficiency and CO2-SCREEN

Carbon capture and storage (CCS) is a process that captures carbon dioxide (CO2) by separating it from anthropogenic emissions sources before atmospheric release and storing that CO2 in deep geologic reservoirs. CCS is a powerful method for reducing anthropogenic CO2 which can ultimately diminish the effects of climate change. Prospective CO2 storage resource is the amount of carbon dioxide that can be stored in a given geologic formation typically given as a mass (e.g., metric tons). Obtaining accurate estimates of CO2 storage resources is necessary for governments and industries to make energy-related policy decisions. Researchers at the National Energy Technology Laboratory (NETL) under the Department of Energy (DOE) developed a methods and a tool [CO2-SCREEN (Storage prospeCtive Resource Estimation Excel aNalysis) to estimate prospective carbon storage resources for saline formations, unconventional shale formations, and residual oil zones. The methods and tool provide CO2 storage and efficiency outputs in the form of probability estimates (i.e. P10 and P90) as well as partitioning storage and efficiency estimates based on storage mechanism (total, free phase, sorbed phase, and dissolution phase). This presentation will focus on how storage efficiency is calculated based on numerical modeling efforts, how it’s applied in the storage methods and tool, and then highlighting needs for future development.

Hanson, Angela Goodman↗
DOE OSTI2020

Dynamical Instabilities in Systems of Multiple Short-period Planets Are Likely Driven by Secular Chaos: A Case Study of Kepler-102

We investigated the dynamical stability of high-multiplicity Kepler and K2 planetary systems. Our numerical simulations find instabilities in ∼20% of the cases on a wide range of timescales (up to 5 × 10{sup 9} orbits) and over an unexpectedly wide range of initial dynamical spacings. To identify the triggers of long-term instability in multiplanet systems, we investigated in detail the five-planet Kepler-102 system. Despite having several near-resonant period ratios, we find that mean-motion resonances are unlikely to directly cause instability for plausible planet masses in this system. Instead, we find strong evidence that slow inward transfer of angular momentum deficit (AMD) via secular chaos excites the eccentricity of the innermost planet, Kepler-102 b, eventually leading to planet–planet collisions in ∼80% of Kepler-102 simulations. Kepler-102 b likely needs a mass ≳0.1 M {sub ⊕}, hence a bulk density exceeding about half Earth’s, in order to avoid dynamical instability. To investigate the role of secular chaos in our wider set of simulations, we characterize each planetary system’s AMD evolution with a “spectral fraction” calculated from the power spectrum of short integrations (∼5 × 10{sup 6} orbits). We find that small spectral fractions (≲0.01) are strongly associated with dynamical stability on long timescales (5 × 10{sup 9} orbits) and that the median time to instability decreases with increasing spectral fraction. Our results support the hypothesis that secular chaos is the driver of instabilities in many nonresonant multiplanet systems and also demonstrate that the spectral analysis method is an efficient numerical tool to diagnose long-term (in)stability of multiplanet systems from short simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Pushing Lithium–Sulfur Batteries towards Practical Working Conditions through a Cathode–Electrolyte Synergy

Abstract The commercialization of lithium–sulfur (Li−S) batteries is still hindered by the unsatisfactory cell performance under practical working conditions, which is mainly caused by the sluggish cathode redox kinetics, severe polysulfide shuttling, and poor Li stripping/plating reversibility. Herein, we report an effective strategy by combining Se‐doped S hosted in an ordered macroporous framework with a highly fluorinated ether (HFE)‐based electrolyte to simultaneously address the aforementioned issues in both cathode and anode. A reversible and stable high areal capacity of >5.4 mAh cm −2 with high Coulombic efficiency >99.2 % can be achieved under high areal Se/S loading (5.8 mg cm −2 ), while the underlying mechanism was further revealed through synchrotron X‐ray probes and Time‐of‐Flight Secondary Ion Mass Spectrometry (ToF‐SIMS). The practical application potential was further evaluated at low (0 °C) and high (55 °C) temperatures under high areal Se/S loading (>5.0 mg cm −2 ) and thin Li metal (40 μm).

Zhao, Chen↗
DOE OSTI2023

Quantitative Analysis of The High‐Yield Hydrolysis of Kelp by Laminarinase and Alginate Lyase

Abstract Kelp is an abundant, farmable biomass‐containing laminarin and alginate as major polysaccharides, providing an excellent model substrate to study their deconstruction by simple enzyme mixtures. Our previous study showed strong reactivity of the glycoside hydrolase family 55 during hydrolysis of purified laminarin, raising the question of its reactivity with intact kelp. In this study, we determined that a combination of a single glycoside hydrolase family 55 β‐1,3‐exoglucanase with a broad‐specificity alginate lyase from the polysaccharide lyase family 18 gives efficient hydrolysis of untreated kelp to a mixture of simple sugars, that is, glucose, gentiobiose, mannitol‐end glucose, and mannuronic and guluronic acids and their soluble oligomers. Quantitative assignments from nanostructure initiator mass spectrometry (NIMS) and 2D HSQC NMR spectroscopy and analysis of the reaction time‐course are provided. The data suggest that binary combinations of enzymes targeted to the unique polysaccharide composition of marine biomass are sufficient to deconstruct kelp into soluble sugars for microbial fermentation.

2D HSQC NMR↗
DOE OSTI2020

Probing non-standard neutrino interactions with supernova neutrinos at Hyper-K

Non-standard neutrino self interactions (NSSI) could be stronger than Fermi interactions. We investigate the ability to constrain these four-neutrino interactions by their effect on the flux of neutrinos originating from a galactic supernova. In the dense medium of a core collapse supernova, these new self interactions can have a significant impact on neutrino oscillations, leading to changes at the flavor evolution and spectra level. We use simulations of the neutrino flux from a 13 solar mass, core collapse supernova at 10 kpc away, and numerically propagate these neutrinos through the stellar medium taking into account vacuum/MSW oscillations, SM ν – ν scattering as well as ν – ν interactions that arise from NSSI. We pass the resulting neutrino flux to a simulation of the future Hyper-Kamiokande detector to see what constraints on NSSI parameters are possible when the next galactic supernova becomes visible. We find that these constraints depend strongly on the neutrino mass hierarchy and if the NSSI is flavor-violating or preserving. Sensitivity to NSSI in the normal hierarchy (NH) at Hyper-K is limited by the experiment’s ability to efficiently detect ν e , but deviations from no NSSI could be seen if the NSSI is particularly strong. In the inverted hierarchy (IH) scenario, Hyper-K can significantly improve constraints on flavor-violating NSSI down to O(10 –1 )G F .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Effects of Hydrogen Redistribution at High Temperatures in Yttrium Hydride Moderator Material

We report advanced materials development, manufacturing, and modeling capabilities for innovative reactor designs support nuclear security and mission-focused science through enhanced technology for safer and more efficient and secure production of nuclear energy. The high temperature moderator material yttrium hydride poses a significant enhancement in small reactor design by thermalizing (slowing down) neutrons and decreasing the required fuel mass for a system. The research presented here supports understanding hydrogen distribution in yttrium hydride through: (1) the development of neutron-based hydrogen imaging and crystallographic characterization that allows us to understand fundamental diffraction behaviors and to observe changes in hydrogen distribution as a function of temperature and (2) subsequent neutron multiplication (reactivity) effects of changes in hydrogen distribution using measurement-based cross sections in a sample microreactor design. The main conclusions from the work are that: (1) hydrogen does not redistribute significantly below temperatures of 800°C in yttrium hydride and (2) hydrogen redistribution affects the reactivity slightly but not significantly.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Nuclear–Electronic Orbital General Rate Theory: Predicting Hydrogen Kinetic Isotope Effects in the Deep Tunneling Regime

Hydrogen transfer is a critical component of many chemical and biological processes. The ratio of rate constants for hydrogen and deuterium transfer defines the H/D kinetic isotope effect (KIE), which is a powerful tool for elucidating hydrogen transfer mechanisms. Interpretation of experimental H/D KIEs relies on accurate and affordable computational methods. However, due to their light mass, hydrogen and deuterium can undergo tunneling, which is challenging to describe in multidimensional molecular systems. Herein, we introduce the nuclear–electronic orbital general rate theory (NEO-GRT), which enables the efficient prediction of H/D KIEs based on full-dimensional molecular quantum chemistry calculations. The NEO-GRT approach describes the hydrogen transfer rate constant with a general expression that spans the vibrationally adiabatic and nonadiabatic hydrogen tunneling regimes. The input quantities are computed using NEO density functional theory, which treats the transferring hydrogen or deuterium nucleus quantum mechanically on the same level as the electrons. We investigate two intramolecular proton transfer reactions in organic molecules at temperatures down to 50 K to evaluate the performance of NEO-GRT by comparison to transition state theory and ring-polymer instanton theory. The KIEs computed with NEO-GRT agree with those calculated using ring-polymer instanton theory for the full-dimensional molecular systems at the same level of electronic structure theory. This agreement indicates that NEO-GRT captures the deep hydrogen tunneling effects, in contrast to transition state theory, which neglects such effects. Given its relatively low computational cost, NEO-GRT is a promising approach for predicting H/D KIEs in large organic and organometallic systems.

Hydrogen↗
DOE OSTI2025

Carbon nanotube nanofluidics

Fluid flow under extreme spatial confinement exhibits unusual physical behaviors. This nanofluidic transport regime is relevant to a variety of mass transport, separation, and energy production processes in biological and industrial systems. Carbon nanotubes (CNTs) offer a nearly ideal platform for exploring nanofluidic transport because of their extremely narrow, smooth, hydrophobic inner pores, which enable very fast molecular flow while providing strong selectivity. In this review, we aim to provide a comprehensive understanding of nanofluidics in CNTs, focusing on the basic physics of mass transport in CNTs, various experimental platforms developed to investigate these phenomena, and key results on the permeation of water, protons, and ions. We focus on the critical factors that influence transport efficiency and selectivity, such as slip flow and charge regulation in CNTs, and the roles of entrance effects, dehydration processes and ion–charge interactions at the CNT entrances. We also explore the confinement effects, highlighting how the unique one-dimensional structure of CNTs imposes distinct constraints on fluid behavior and leads to novel single-file transport phenomena. Finally, we address current challenges and future directions of CNT nanofluidics.

Li, Zhongwu [Lawrence Livermore National Laborator↗