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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Feasibility Study of Spectrophotometry to Support a Promethium Production Program at ORNL

Optical spectroscopy can be used to optimize analytical measurements for lanthanide elements and provide real-time feedback to help guide production operations. This study evaluates spectrophotometry for the determination of samarium (Sm 3+ ) and neodymium (Nd 3+ ) in aqueous and organic solutions at concentrations relevant to a promethium (Pm) program separation scheme. Detection limits approached 0.5 mM for Nd 3+ and 2 mM for Sm 3+ using Ocean Insight spectrophotometers. Additionally, Sm 3+ detection limits using laser fluorescence spectra for Sm 3+ approached single ppm (mg∙L -1 ) levels. An absorption spectrum containing Nd and Pm is also reported and discussed. This work demonstrates proofof-principle concepts for applying spectrophotometry to online monitoring applications in support of a future Pm production program.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Oil and Gas Recovery Capability

Oil and gas recovery increasingly relies on stimulation and production strategies that involve complex interactions between rock deformation, fractures, and fluid flow underground. Conventional modeling approaches often simplify or separate these effects, which can limit their ability to accurately predict performance in fractured or geologically complex reservoirs.

02 PETROLEUM↗
DOE OSTI2024

Machine learning opportunities for nucleosynthesis studies

Nuclear astrophysics is an interdisciplinary field focused on exploring the impact of nuclear physics on the evolution and explosions of stars and the cosmic creation of the elements. While researchers in astrophysics and in nuclear physics are separately using machine learning approaches to advance studies in their fields, there is currently little use of machine learning in nuclear astrophysics. We briefly describe the most common types of machine learning algorithms, and then detail their numerous possible uses to advance nuclear astrophysics, with a focus on simulation-based nucleosynthesis studies. We show that machine learning offers novel, complementary, creative approaches to address many important nucleosynthesis puzzles, with the potential to initiate a new frontier in nuclear astrophysics research.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Integrated Transmission-and-Distribution System Modeling of Power Systems: State-of-the-Art and Future Research Directions

Integrated transmission-and-distribution (T&D) modeling is a new and developing method for simulating power systems. Interest in integrated T&D modeling is driven by the changes taking place in power systems worldwide that are resulting in more decentralized power systems with increasingly high levels of distributed energy resources. Additionally, the increasing role of the hitherto passive energy consumer in the management and operation of power systems requires more capable and detailed integrated T&D modeling to understand the interactions between T&D systems. Although integrated T&D modeling has not yet found widespread commercial application, its potential for changing the decades-old power system modeling approaches has led to several research efforts in the last few years that tried to (i) develop algorithms and software for steady-state and dynamic modeling of power systems and (ii) demonstrate the advantages of this modeling approach compared with traditional, separated T&D system modeling. In this paper, we provide a review of integrated T&D modeling research efforts and the methods employed for steady-state and dynamic modeling of power systems. We also discuss our current research in integrated T&D modeling and the potential directions for future research. This paper should be useful for power systems researchers and industry members because it will provide them with a critical summary of current research efforts and the potential topics where research efforts are needed to further advance and demonstrate the utility of integrated T&D modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Ab Initio Many Body Quantum Embedding and Local Correlation in Crystalline Materials using Interpolative Separable Density Fitting

We present an efficient implementation of ab initio many-body quantum embedding and local correlation methods for infinite periodic systems through translational symmetry adapted interpolative separable density fitting, an approach which reduces the scaling of the calculations to only linear with the number of k-points. Employing this methodology, we compute correlated ground-state coupled cluster energies within density matrix embedding and local natural orbital correlation frameworks for both weakly and strongly correlated solids, using up to 1000 k-points. By extrapolating the local correlation domains and k-point sampling we further obtain estimates of the full coupled cluster with singles, doubles, and perturbative triples ground-state energies in the thermodynamic limit.

Chemical Physics (physics.chem-ph)↗
DOE OSTI2022

Evaluation of hydrograph separation techniques with uncertain end-member composition

Hydrograph separation is one of many approaches used to analyse shifts in source water contributions to stream flow resulting from climate change in remote watersheds. Understanding these shifts is vital, as shifts in source water contributions to a stream can shape water management decisions. Because remote watersheds are often inaccessible and have poorly characterized contributing water sources, or end-members, it is critical to understand the implications of using different hydrograph separation techniques in these data-limited environments. To explore the uncertainty associated with different techniques, results from two hydrograph separation techniques, mass balance and principle component analysis, were compared using 3 years of aqueous geochemical data from the East River watershed located in the Elk Mountains of Central Colorado. Solute concentrations of the end-members were characterized by both a limited set of direct chemical measurements of different sources and detailed seasonal instream chemistry to examine the influences of uncertain end-member compositions in a data-limited environment. Annual volumetric end-member contributions to stream flow had relatively good agreement across separation techniques. Large variations in time were observed in the hydrograph separations, depending on the end-member type, and estimated flow contributions varied between the selected solutes. End-member concentrations characterized by stream chemistry showed several limitations including a reduced number of distinguishable end-members and differences in timing of flow contributions. Here the results highlight the benefits of using multiple hydrograph separation techniques by providing a ‘weight-of-evidence’ approach to environments with limited end-member concentration data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Constructing Regulatory Networks to Compare Axenic and Interspecies Microbial Gene Transcription

In this preliminary study, we constructed gene regulatory networks (GRNs) from transcriptional expression data of axenic and interspecies microbial cultures with the goal of predicting how cocultivation affected greenhouse gas respiration by these species. The specific strains of Methylotuvimicrobium alkaliphilum 20Z, a methylotroph, and Cyanobacterium stanieri HL-69, a phototroph, were chosen for their viability in industrial bioprocessing. We ranked directed interactions between gene pairs based on the ability of the input gene to predict the expression of a target gene relative to their transcriptomes. While we were able to identify topological differences between conditions, our initial findings require validation through experimental analysis and further modeling. We aimed to develop a systematic thresholding approach to optimize the accuracy of our networks. We filtered out trial networks separately from top gene interactions of the scored rankings. Parameters of unfiltered and filtered networks were used to test and develop thresholding approaches. Knee point detection of edge weight distributions was explored as an approach for separating significant interactions from insignificant interactions in unfiltered networks. While knee detection failed to produce analogous networks for broad cross-condition comparisons, the results informed us about the proportions of significant edges present in unfiltered networks. We also calculated the average mean degree for nodes in a selection of trial networks to find a thresholding value characteristic to all groups. While we did not reach a definitive conclusion, we gained insight into the coregulatory structures of our groups and made critical evaluations of systematic methods for filtering networks. We recommend an iterative process for the inference of GRNs, where the most significant results from preliminary explorations are used to improve the efficiency with which regulatory motifs are chosen for experimental characterization. Experimental results can then inform the framework of adjusted models to improve broad interpretations of GRNs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The utility of Bayesian data reconciliation for separations

Data reconciliation methods for separation processes typically rely on classical statistical approaches to generate estimates of true mass flow rates from measurements. Knowledge regarding the uncertainty of these estimates has value in decision making, but is often not acquired. Bayesian approaches intrinsically quantify uncertainty; however, literature for Bayesian data reconciliation of separation processes is scarce. This publication outlines two Bayesian data reconciliation models and provides details for how the models were implemented for the BayesMassBal (V 1.0.0) software package written in R. To demonstrate the advantages of this approach for data reconciliation, the models were first applied to simulated data and then compared to a classical model through a Monte Carlo experiment. In this example, the Bayesian models were found to provide more accurate estimates of the simulated data, while also providing quantitative information on the estimate uncertainty. To demonstrate the use of the technique in a practical problem, the models were also applied to real data collected from a pilot-scale rare earth solvent extraction process. Here, this publication provides a small window into how Bayesian methods can be used for data reconciliation, but findings suggest Bayesian data reconciliation models for separation processes have distinct advantages over classical alternatives.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Dynamic time-warping correction for shifts in ultrahigh resolving power ion mobility spectrometry and structures for lossless ion manipulations

Detection of arrival time shifts between ion mobility spectrometry (IMS) separations can limit achievable resolving power (Rp), particularly when multiple separations are summed or averaged, as commonly practiced. Such variations are more apparent in higher Rp measurements, and are particularly evident in long path length traveling wave structures for lossless ion manipulations (SLIM) IMS due to their typically much longer separation times. Here we explore the utility of a data processing approaches employing linear alignment (LA) and nonlinear dynamic time warping (DTW) of IMS separations to correct for variations between separations, such as due to pressure fluctuations. For multipass SLIM IMS separations, where narrow mobility range measurements have arrival times that can extend to several seconds, the LA approach effectively corrected for such variations, and significantly improvement Rp for summed separations. However, LA was much less effective for high Rp broad mobility range separations, such as obtained with multilevel SLIM IMS. Changes in IMS arrival times ions were observed to be correlated with small pressure changes, with approximately 0.6% relative arrival time shifts being common, sufficient to result in a loss of Rp for summed separations. Comparison of the approaches showed DTW alignment performed similarly to LA when used over a narrow mobility range, but was significantly better (providing narrower peaks and higher signal intensities) for wide mobility range data. We found the DTW approach increased Rp by as much as 115% for measurements in which 50 IMS separations over 2 seconds were summed, and leading to a large improvement in effective Rp. We conclude that DTW is superior to LA for ultrahigh resolution broad mobility range SLIM IMS separations, correcting for ion arrival time shifts regardless of the cause. Our tool is publicly available for use with universal ion mobility format (.UIMF) and text (.txt) files.

Data alignment, dynamic time warping, ion mobility↗
DOE OSTI2024

Performance enhancement of aqueous ionic liquids with lower critical solution temperature (LCST) behavior through ternary mixtures

Thermally responsive ionic liquids (ILs) exhibit liquid–liquid phase separation when mixed with water and heated above a lower critical solution temperature (LCST), resulting in a water-rich (WR) and an IL-rich (ILR) phase. These binary IL–water mixtures can be employed in a variety of thermodynamic processes such as forward osmosis (FO) desalination, for which two solution properties are desirable: low phase separation temperature and high osmotic strength (osmolality). However, these two properties are interlinked, with ILs that exhibit higher osmotic strengths typically requiring higher phase separation temperatures. This behavior tends to arise from the hydrophilicity of the IL cations, which enhances osmotic strength while also elevating the phase separation temperature. In this work, we highlight a pathway to overcome this tradeoff by developing ternary IL mixtures (two ILs with varying cation hydrophilicity mixed with water), which lowers the phase separation temperature while maintaining and even enhancing the osmotic strength of the solution. We characterize the mixing behavior (osmolality, phase separation temperature, WR phase purity, and WR to ILR phase mass ratio) of four ILs as a function of their concentration in solution. We find that an enhancement of up to 81.6% in the osmolality with a concomitant reduction of up to 15.4% in the phase separation temperature can be achieved using this approach. The ternary mixture is also shown to improve the phase separation kinetics by nearly 95% compared to the binary mixture. Overall, this work highlights a new pathway to improve the performance of LCST ILs for water and energy applications.

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

Crystallization-assisted water adsorption in amorphous molecular adsorbents

Efficient and stable water adsorbents are essential for removing moisture from natural gas and olefins during their production. Industrial desiccants such as alumina and zeolites require high regeneration temperatures, while metal-organic frameworks often suffer from limited long-term stability and reusability. Here, we introduce a new type of molecular desiccants (M-PyC) that, in principle, can be reused indefinitely. These simple molecular coordination complexes undergo fully reversible phase transitions between crystalline and amorphous states through the decoordination (bond breaking) and recoordination (bond reforming) of water molecules. They exhibit high water uptake (30 wt%) and superb selectivity, excluding hydrocarbons entirely. Their effectiveness for dehydration, combined with low regeneration temperature, fast desorption kinetics, low-cost and green synthesis, easy scalability to kilogram quantities, and essentially unlimited recyclability, makes them truly competitive dehydration agents for industrial separations. The use of amorphous molecular adsorbents, where crystallinity and porosity are no longer stringent requirements, and the adsorption-desorption process entirely under ambient air, offers a conceptually different approach to adsorption-based separation science and potentially realistic solution to the long-standing challenge of sustained stability in coordinate-bonded adsorbents.

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

Microscale Electrochemical Corrosion of Uranium Oxide Particles

Understanding the corrosion of spent nuclear fuel is important for the development of long-term storage solutions. However, the risk of radiation contamination presents challenges for experimental analysis. Adapted from the system for analysis at the liquid–vacuum interface (SALVI), we developed a miniaturized uranium oxide (UO 2 )-attached working electrode (WE) to reduce contamination risk. To protect UO 2 particles in a miniatured electrochemical cell, a thin layer of Nafion was formed on the surface. Atomic force microscopy (AFM) shows a dense layer of UO 2 particles and indicates their participation in electrochemical reactions. Particles remain intact on the electrode surface with slight redistribution. X-ray photoelectron spectroscopy (XPS) reveals a difference in the distribution of U(IV), U(V), and U(VI) between pristine and corroded UO 2 electrodes. The presence of U(V)/U(VI) on the corroded electrode surface demonstrates that electrochemically driven UO 2 oxidation can be studied using these cells. Our observations of U(V) in the micro-electrode due to the selective semi-permeability of Nafion suggest that interfacial water plays a key role, potentially simulating a water-lean scenario in fuel storage conditions. This novel approach offers analytical reproducibility, design flexibility, a small footprint, and a low irradiation dose, while separating the α-effect. This approach provides a valuable microscale electrochemical platform for spent fuel corrosion studies with minimal radiological materials and the potential for diverse configurations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Review of Multifunctional Separators: Stabilizing the Cathode and the Anode for Alkali (Li, Na, and K) Metal–Sulfur and Selenium Batteries

Alkali metal batteries based on lithium, sodium, and potassium anodes and sulfur-based cathodes are regarded as key for next-generation energy storage due to their high theoretical energy and potential cost effectiveness. However, metal–sulfur batteries remain challenged by several factors, including polysulfides’ (PSs) dissolution, sluggish sulfur redox kinetics at the cathode, and metallic dendrite growth at the anode. Functional separators and interlayers are an innovative approach to remedying these drawbacks. Here we critically review the state-of-the-art in separators/interlayers for cathode and anode protection, covering the Li–S and the emerging Na–S and K–S systems. The approaches for improving electrochemical performance may be categorized as one or a combination of the following: Immobilization of polysulfides (cathode); catalyzing sulfur redox kinetics (cathode); introduction of protective layers to serve as an artificial solid electrolyte interphase (SEI) (anode); and combined improvement in electrolyte wetting and homogenization of ion flux (anode and cathode). It is demonstrated that while the advances in Li–S are relatively mature, less progress has been made with Na–S and K–S due to the more challenging redox chemistry at the cathode and increased electrochemical instability at the anode. Throughout these sections there is a complementary discussion of functional separators for emerging alkali metal systems based on metal–selenium and the metal–selenium sulfide. The focus then shifts to interlayers and artificial SEI/cathode electrolyte interphase (CEI) layers employed to stabilize solid-state electrolytes (SSEs) in metal–sulfur solid-state batteries (SSBs). The discussion of SSEs focuses on inorganic electrolytes based on Li- and Na-based oxides and sulfides but also touches on some hybrid systems with an inorganic matrix and a minority polymer phase. The review then moves to practical considerations for functional separators, including scaleup issues and Li–S technoeconomics. The review concludes with an outlook section, where we discuss emerging mechanics, spectroscopy, and advanced electron microscopy (e.g. cryo-transmission electron microscopy (cryo-TEM) and cryo-focused ion beam (cryo-FIB))-based approaches for analysis of functional separator structure–battery electrochemical performance interrelations. Finally, throughout the review we identify the outstanding open scientific and technological questions while providing recommendations for future research topics.

25 ENERGY STORAGE↗
DOE OSTI2020

Accelerating nuclear fuel development and qualification: Modeling and simulation integrated with separate-effects testing

In this work, an approach to transform and accelerate nuclear fuel development and qualification is outlined. The approach exploits advanced modeling and simulation at the outset to inform constituent and system selection and to enable integral fuel performance analyses. Analyses using these tools identify and prioritize the most important fuel performance parameters and phenomena for subsequent targeted characterization with separate-effects tests. Separate-effects testing spans out-of-pile and in-pile tests and is meant to iterate with and inform engineering-scale integral fuel performance analyses throughout the development process. Exercising this cycle in an agile fashion will increase confidence in the integral fuel performance predictions while reducing uncertainties. This process sets the stage for executing a much more limited set of well-defined integral irradiation tests designed to validate engineering-scale fuel performance codes and to confirm the performance and safety of the fuel system under prototypic conditions. This approach will reduce the time for development and qualification of a new fuel system, and it will also reduce associated costs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Finely tunable dynamical coloration using bicontinuous micrometer-domains

Nanostructures similar to those found in the vividly blue wings of Morpho butterflies and colorful photonic crystals enable structural color through constructive interference of light waves. Different from commonly studied structure-colored materials using periodic structures to manipulate optical properties, we report a previously unrecognized approach to precisely control the structural color and light transmission via a novel photonic colloidal gel without long-range order. Nanoparticles in this gel form micrometer-sized bicontinuous domains driven by the microphase separation of binary solvents. This approach enables dynamic coloration with a precise wavelength selectivity over a broad range of wavelengths extended well beyond the visible light that is not achievable with traditional methods. The dynamic wavelength selectivity is thermally tunable, reversible, and the material fabrication is easily scalable.

42 ENGINEERING↗
DOE OSTI2022

Recycling rare earths: Perspectives and recent advances

Abstract Rare-earth element (REE) demand is expected to increase by a factor of up to 7 by 2040. Recycling avoids the significant hurdles associated with opening new mines, but collection and disassembly of REE-containing devices are barriers. Absolute and relative abundances of REEs and co-occurring constituents differ significantly in secondary compared to primary sources, presenting challenges and opportunities. REE concentrations are typically low, but manufactured devices include only the desired REE, avoiding the “REE balance problem” that besets natural ores. Fewer REEs need to be separated, as compared to separation of the entire lanthanide series. Co-recovery of precious (e.g., Au, Ag, Pt) or base metals (e.g., Cu, Sn, Zn) from e-wastes can offset recycling costs. Some examples of recently developed approaches for REE extraction and separation are presented here, with an emphasis on methods offering environmental benefits such as lower toxic chemical usage and reduced energy costs. Graphical abstract

36 MATERIALS SCIENCE↗
DOE OSTI2021

The challenge of blending in large sky surveys

The increasing sensitivity of modern sky surveys allow ever fainter emissions of light to be detected, but it also increases the chances of noticeable overlap between multiple sources of light, a phenomenon called blending. Furthermore, the consequences of blending are expected to be among the leading systematic measurement uncertainties of future surveys, such as the Legacy Survey of Space and Time. This Perspective discusses two main approaches to addressing blending: attempting to separate individual sources and statistically correcting for the presence of blending at the population level. For both approaches, simultaneous access to data of multiple surveys will be critical to construct a joint data set that combines the strengths of each individual survey.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Quantifying spatial and vertical variations in soil C:N relationships in permafrost-affected landscapes

Permafrost regions are experiencing rapid changes that affect carbon (C) and nitrogen (N) cycles, with implications for vegetation dynamics and gas exchanges with the atmosphere. Soil C:N ratio is a key indicator of organic matter quality, yet spatial estimates of N stocks and C:N ratios lag behind those for C. We used quantile regression forests to compare direct and indirect digital soil mapping approaches for predicting soil C:N ratios at 0–30, 30–60, and 60–100 cm depths across a latitudinal transect in Alaska. The indirect approach – deriving C:N from separately predicted C and N stocks – outperformed direct mapping for the surface layer (0–30 cm), while direct mapping was marginally better at greater depths. However, prediction accuracy decreased with depth for both methods. Temperature and topography were the most important predictors. Both approaches overestimated low and underestimated high C:N ratios, with direct mapping showing greater bias. Our results underscore the challenges of modeling C:N ratios in heterogeneous, data-sparse permafrost soils, but also suggest that indirect mapping holds promise if supported by more extensive datasets.

54 ENVIRONMENTAL SCIENCES↗