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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Quantitative measurements of density in shock-compressed silver up to 330 GPa using x-ray diffraction

This work presents a structural study of shock-compressed states in Ag to 331 GPa, accessed via laser shock compression. Structures of the resulting crystalline phases and the average atomic distribution of the liquid state are determined using in situ x-ray diffraction. We employ structure factor analysis, adapted for a non-monochromatic x-ray source, to determine the density of the liquid phase from analysis of x-ray diffraction data for the first time in shock compressed Ag. We also present a detailed analysis of the crystalline phases, which shows good agreement with the phase boundaries reported in previous experimental and theoretical works. We utilize the whole powder pattern fitting approach implemented in the MAUD package to constrain stacking faults in the face centered cubic structure. We observe the ambient fcc structure up to a stress of 146 GPa before a transition to a body-centered cubic structure and liquid phase at 179 GPa, with full melting above 212 GPa.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Quantifying the regime of thermodynamic control for solid-state reactions during ternary metal oxide synthesis

The success of solid-state synthesis often hinges on the first intermediate phase that forms, which determines the remaining driving force to produce the desired target material. Recent work suggests that when reaction energies are large, thermodynamics primarily dictates the initial product formed, regardless of reactant stoichiometry. Here, we validate this principle and quantify its constraints by performing in situ characterization on 37 pairs of reactants. These experiments reveal a threshold for thermodynamic control in solid-state reactions, whereby initial product formation can be predicted when its driving force exceeds that of all other competing phases by ≥60 milli–electron volt per atom. In contrast, when multiple phases have a comparable driving force to form, the initial product is more often determined by kinetic factors. Analysis of the Materials Project data shows that 15% of possible reactions fall within the regime of thermodynamic control, highlighting the opportunity to predict synthesis pathways from first principles.

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

Confidentiality-preserving machine learning algorithms for soft-failure detection in optical communication networks

Automated fault management is at the forefront of next-generation optical communication networks. The increase in complexity of modern networks has triggered the need for programmable and software-driven architectures to support the operation of agile and self-managed systems. In these scenarios, the European Telecommunications Standards Institute zero-touch network and service management approach is imperative. The need for machine learning algorithms to process the large volume of telemetry data brings safety concerns as distributed cloud-computing solutions become the preferred approach for deploying reliable communication network automation. This paper’s contribution is twofold. First, we propose a simple yet effective method to guarantee the confidentiality of the telemetry data based on feature scrambling. The method allows the operation of third-party computational services without direct access to the full content of the collected data. Additionally, the effectiveness of four unsupervised machine learning algorithms for soft-failure detection is evaluated when applied to the scrambled telemetry data. The methods are based on factor analysis, principal component analysis, nonlinear principal component analysis, and singular value decomposition. Most dimensionality reduction algorithms have the common property that they can maintain similar levels of fault classification performance while hiding the data structure from unauthorized access. Evaluations of the proposed algorithms demonstrate this capability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Data and scripts associated with a manuscript investigating impacts of solid phase extraction on freshwater organic matter optical signatures and mass spectrometry pairing

This data package is associated with the publication “Investigating the impacts of solid phase extraction on dissolved organic matter optical signatures and the pairing with high-resolution mass spectrometry data in a freshwater system” submitted to “Limnology and Oceanography: Methods.” This data is an extension of the River Corridor and Watershed Biogeochemistry SFA’s Spatial Study 2021 (https://doi.org/10.15485/1898914). Other associated data and field metadata can be found at the link provided. The goal of this manuscript is to assess the impact of solid phase extraction (SPE) on the ability to pair ultra-high resolution mass spectrometry data collected from SPE extracts with optical properties collected on ambient stream samples. Forty-seven samples collected from within the Yakima River Basin, Washington were analyzed dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC), absorbance, and fluorescence. Samples were subsequently concentrated with SPE and reanalyzed for each measurement. The extraction efficiency for the DOC and common optical indices were calculated. In addition, SPE samples were subject to ultra-high resolution mass spectrometry and compared with the ambient and SPE generated optical data. Finally, in addition to this cross-platform inter-comparison, we further performed and intra-comparison among the high-resolution mass spectrometry data to determine the impact of sample preparation on the interpretability of results. Here, the SPE samples were prepared at 40 milligrams per liter (mg/L) based on the known DOC extraction efficiency of the samples (ranging from ~30 to ~75%) compared to the common practice of assuming the DOC extraction efficiency of freshwater samples at 60%. This data package folder consists of one main data folder with one subfolder (Data_Input). The main data folder contains (1) readme; (2) data dictionary (dd); (3) file-level metadata (flmd); (4) final data summary output from processing script; and (5) the processing script. The R-markdown processing script (SPE_Manuscript_Rmarkdown_Data_Package.rmd) contains all code needed to reproduce manuscript statistics and figures (with the exception of that stated below). The Data_Input folder has two subfolders: (1) FTICR and (2) Optics. Additionally, the Data_Input folder contains dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data (SPS_NPOC_Summary.csv) and relevant supporting Solid Phase Extraction Volume information (SPS_SPE_Volumes.csv). Methods information for the optical and FTICR data is embedded in the header rows of SPS_EEMs_Methods.csv and SPS_FTICR_Methods.csv, respectively. In addition, the data dictionary (SPS_SPE_dd.csv), file level metadata (SPS_SPE_flmd.csv), and methods codes (SPS_SPE_Methods_codes.csv) are provided. The FTICR subfolder contains all raw FTICR data as well as instructions for processing. In addition, post processed FTICR molecular information (Processed_FTICRMS_Mol.csv) and sample data (Processed_FTICRMS_Data.csv) is provided that can be directly read into R with the associated R-markdown file. The Optics subfolder contains all Absorbance and Fluorescence Spectra. Fluorescence spectra have been blank corrected, inner filter corrected, and undergone scatter removal. In addition, this folder contains Matlab code used to make a portion of Figure 1 within the manuscript, derive various spectral parameters used within the manuscript, and used for parallel factor analysis (PARAFAC) modeling. Spectral indices (SPS_SpectralIndices.csv) and PARAFAC outputs (SPS_PARAFAC_Model_Loadings.csv and SPS_PARAFAC_Sample_Scores.csv) are directly read into the associated R-markdown file. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data for Kim et al., "Variations in the optical and molecular composition of dissolved organic matter exported from coastal wetlands"

Knowledge about sources and composition of marsh-derived dissolved organic matter (DOM) is critical for understanding the role of marshes in coastal biogeochemical cycling and the fate of marsh-derived DOM in the ocean. To investigate tidal variability in composition of marsh-derived DOM, Kim et al. examined the optical and molecular characteristics of hourly surface water samples at three tidal creeks in the Chesapeake Bay. Groundwater samples along the terrestrial landscape gradient as well as estuarine water from the adjacent estuary at each site were also collected to help resolve sources of surface water DOM. Samples were collected in summer 2024 at three sites – SWH: Sweet Hall Marsh, GCW: Kirkpatrick Marsh, and GWI: Goodwin Islands – which are part of synoptic sites in the Chesapeake Bay region of the COMPASS-FME (Coastal Observations, Mechanisms, and Predictions Across Systems and Scales - Field, Measurements, and Experiments) project. Surface water samples were collected hourly over a 48-hour period at each site. Groundwater and estuarine water samples were collected once. This dataset includes- Surface water depth and salinity- Dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) concentrations- Optical indices and relative composition of parallel factor analysis (PARAFAC) components- High resolution mass spectrometry data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Eu(III) and Cm(III) Complexation by the Aminocarboxylates NTA, EDTA, and EGTA Studied with NMR, TRLFS, and ITC—An Improved Approach to More Robust Thermodynamics

The complex formation of Eu(III) and Cm(III) was studied via tetradentate, hexadentate, and octadentate coordinating ligands of the aminopolycarboxylate family, viz., nitrilotriacetate (NTA 3- ), ethylenediaminetetraacetate (EDTA 4- ), and ethylene glycol-bis(2-aminoethyl ether)-N,N,N',N'-tetraacetate (EGTA 4- ), respectively. Based on the complexones’ pK a values obtained from 1 H nuclear magnetic resonance (NMR) spectroscopic pH titration, complex formation constants were determined by means of the parallel-factor-analysis-assisted evaluation of Eu(III) and Cm(III) time-resolved laser-induced fluorescence spectroscopy (TRLFS). This was complemented by isothermal titration calorimetry (ITC), providing the enthalpy and entropy of the complex formation. This allowed us to obtain genuine species along with their molecular structures and corresponding reliable thermodynamic data. The three investigated complexones formed 1:1 complexes with both Eu(III) and Cm(III). Besides the established Eu(III)–NTA 1:1 and 1:2 complexes, we observed, for the first time, the existence of a Eu(III)–NTA 2:2 complex of millimolar metal and ligand concentrations. Demonstrated for thermodynamic studies on Eu(III) and Cm(III) interaction with complexones, the utilized approach is commonly applicable to many other metal–ligand systems, even to high-affinity ligands.

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

Measurement report: Molecular composition, optical properties, and radiative effects of water-soluble organic carbon in snowpack samples from northern Xinjiang, China

Abstract. Water-soluble organic carbon (WSOC) in the cryosphere has an important impact on the biogeochemistry cycling and snow–ice surface energy balance through changes in the surface albedo. This work reports on the chemical characterization of WSOC in 28 representative snowpack samples collected across a regional area of northern Xinjiang, northwestern China. We employed multimodal analytical chemistry techniques to investigate both bulk and molecular-level composition of WSOC and its optical properties, informing the follow-up radiative forcing (RF) modeling estimates. Based on the geographic differences and proximity of emission sources, the snowpack collection sites were grouped as urban/industrial (U), rural/remote (R), and soil-influenced (S) sites, for which average WSOC total mass loadings were measured as 1968 ± 953 ng g−1 (U), 885 ± 328 ng g−1 (R), and 2082 ± 1438 ng g−1 (S), respectively. The S sites showed the higher mass absorption coefficients at 365 nm (MAC365) of 0.94 ± 0.31 m2 g−1 compared to those of U and R sites (0.39 ± 0.11 m2 g−1 and 0.38 ± 0.12 m2 g−1, respectively). Bulk composition of WSOC in the snowpack samples and its basic source apportionment was inferred from the excitation–emission matrices and the parallel factor analysis featuring relative contributions of one protein-like (PRLIS) and two humic-like (HULIS-1 and HULIS-2) components with ratios specific to each of the S, U, and R sites. Additionally, a sample from site 120 showed unique pollutant concentrations and spectroscopic features remarkably different from all other U, R, and S samples. Molecular-level characterization of WSOC using high-resolution mass spectrometry (HRMS) provided further insights into chemical differences among four types of samples (U, R, S, and 120). Specifically, many reduced-sulfur-containing species with high degrees of unsaturation and aromaticity were uniquely identified in U samples, suggesting an anthropogenic source. Aliphatic/protein-like species showed the highest contribution in R samples, indicating their biogenic origin. The WSOC components from S samples showed high oxygenation and saturation levels. A few unique CHON and CHONS compounds with high unsaturation degree and molecular weight were detected in the 120 sample, which might be anthraquinone derivatives from plant debris. Modeling of the WSOC-induced RF values showed warming effects of 0.04 to 0.59 W m−2 among different groups of sites, which contribute up to 16 % of that caused by black carbon (BC), demonstrating the important influences of WSOC on the snow energy budget.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Emerging low-cloud feedback and adjustment in global satellite observations

From mid-2003 to mid-2024, a global decrease in low-cloud amount enhanced the absorption of solar radiation by 0.22±0.07 W m −2 per decade (±1σ range), accelerating the energy imbalance trend during that period (0.44 W m −2 per decade). Through controlling factor analysis, here we show that the low-cloud trend is due to a combination of cloud feedback and adjustments to greenhouse gases and aerosols (respectively 0.09±0.02, 0.05±0.03, and 0.03±0.03 W m −2 per decade), which jointly account for 74 % of the trend. The contribution of natural climate variability is weak but uncertain (0.01±0.08 W m −2 per decade), owing to a poorly constrained trend in boundary-layer inversion strength. Importantly, the observed low-cloud radiative trend lies well within the range of values simulated by contemporary global climate models under conditions close to present day. Any systematic model error in the representation of present-day global energy imbalance trends is thus likely to originate in processes unrelated to low clouds.

Geosciences↗
DOE OSTI2022

Sea ice breakup and freeze-up indicators for users of the Arctic coastal environment

Abstract. The timing of sea ice retreat and advance in Arctic coastal waters varies substantially from year to year. Various activities, ranging from marine transport to the use of sea ice as a platform for industrial activity or winter travel, are affected by variations in the timing of breakup and freeze-up, resulting in a need for indicators to document the regional and temporal variations in coastal areas. The primary objective of this study is to use locally based metrics to construct indicators of breakup and freeze-up in the Arctic and subarctic coastal environment. The indicators developed here are based on daily sea ice concentrations derived from satellite passive-microwave measurements. The “day of year” indicators are designed to optimize value for users while building on past studies characterizing breakup and freeze-up dates in the open pack ice. Relative to indicators for broader adjacent seas, the coastal indicators generally show later breakup at sites known to have landfast ice. The coastal indicators also show earlier freeze-up at some sites in comparison with freeze-up for broader offshore regions, likely tied to earlier freezing of shallow-water regions and areas affected by freshwater input from nearby streams and rivers. A factor analysis performed to synthesize the local indicator variations shows that the local breakup and freeze-up indicators have greater spatial variability than corresponding metrics based on regional ice coverage. However, the trends towards earlier breakup and later freeze-up are unmistakable over the post-1979 period in the synthesized metrics of coastal breakup and freeze-up and the corresponding regional ice coverage. The findings imply that locally defined indicators can serve as key links between pan-Arctic or global indicators such as sea ice extent or volume and local uses of sea ice, with the potential to inform community-scale adaptation and response.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Uncertainties in greenhouse gas emission factors: A comprehensive analysis of switchgrass‐based biofuel production

Abstract This study investigates uncertainties in greenhouse gas (GHG) emission factors related to switchgrass‐based biofuel production in Michigan. Using three life cycle assessment (LCA) databases—US lifecycle inventory (USLCI) database, GREET, and Ecoinvent—each with multiple versions, we recalculated the global warming intensity (GWI) and GHG mitigation potential in a static calculation. Employing Monte Carlo simulations along with local and global sensitivity analyses, we assess uncertainties and pinpoint key parameters influencing GWI. The convergence of results across our previous study, static calculations, and Monte Carlo simulations enhances the credibility of estimated GWI values. Static calculations, validated by Monte Carlo simulations, offer reasonable central tendencies, providing a robust foundation for policy considerations. However, the wider range observed in Monte Carlo simulations underscores the importance of potential variations and uncertainties in real‐world applications. Sensitivity analyses identify biofuel yield, GHG emissions of electricity, and soil organic carbon (SOC) change as pivotal parameters influencing GWI. Decreasing uncertainties in GWI may be achieved by making greater efforts to acquire more precise data on these parameters. Our study emphasizes the significance of considering diverse GHG factors and databases in GWI assessments and stresses the need for accurate electricity fuel mixes, crucial information for refining GWI assessments and informing strategies for sustainable biofuel production.

Kim, Seungdo↗
DOE OSTI2021

Theoretical analysis of key factors achieving reversed magnetic shear q-profiles sustained with lower hybrid waves on EAST

The phase space analysis technique is applied to provide new insights into the fully non-inductive lower hybrid current driven (LHCD) discharges on EAST (Garofalo et al 2017 Nucl. Fusion 57 076037). The analysis shows that there are bounded and unbounded topologies of lower hybrid (LH) waves in phase space. For typical parameters on EAST, the propagation domain for 4.6 GHz LH waves is bounded, while unbounded for 2.45 GHz LH waves and one of the conditions is recognized to be good for achieving an off-axis current profile driven by 4.6 GHz LH waves on EAST. The parametric analysis on the potential power deposition (PPD) region for those experiments demonstrates that the reversed magnetic shear dominates the wave behavior, and confines the LH power absorption to the far off-axis region as long as it occurs in the 4.6 GHz dominated LHCD discharge. GENRAY/CQL3D simulations also confirm this effect of reversed shear on the power absorption of 4.6 GHz waves. A bounded propagation domain and a positive feedback loop between magnetic shear reversal and off-axis LHCD profile could explain the LH-only-sustained strong reversed magnetic shear observed in experiments on multiple machines. In contrast, there is no such effect for 2.45 GHz waves on EAST since the PPD region is less sensitive to the change of reversed shear due to the unbounded propagation domain.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Insights from Optimizing HPL Performance on Exascale Systems: A Comparative Analysis of Panel Factorization

High performance LINPACK (HPL) remains the primary benchmark for evaluating supercomputing performance. It includes many parts with substantial internal complexity, and its performance is affected by a large number of parameters that interact in ways that are difficult to predict on large-scale heterogeneous supercomputer systems. We present a comprehensive performance analysis of HPL on Frontier, the world’s first exascale supercomputer, which achieved HPL performance of 1.35 exaflops. Through empirical parameter tuning, detailed modeling, and comparative evaluation, we uncover critical performance insights, share lessons learned, and outline best practices for effective parameter tuning on exascale systems. We introduce and evaluate two novel PDFACT strategies: a dedicated-thread (DT) variant and a GPU-based variant (GPUPDFACT) implementation using HIP cooperative groups, demonstrating that GPU-based factorization outperforms conventional CPU-based PDFACT on Frontier’s architecture. Our findings establish key performance factors for HPL on exascale systems and offer valuable guidance for future high-performance computing and benchmarking efforts.

Lu, Hao [ORNL] (ORCID:000000018941870X)↗
DOE OSTI2020

Novel AC Distribution Factor for Efficient Outage Analysis

We propose novel line outage distribution factors under AC power flow (AC-LODF) for providing very efficient approximate post-outage power flow solution. The AC-LODF is derived by using holomorphic embedding (HE) approach, and the approximate post-outage power flow solution is obtained with Pad approximation (PA). In this work, tests on IEEE 14-bus system, and Polish 2383-bus system verify that the proposed AC-LODF is effective on most outages, and can significantly speed up outage analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

A mathematical approach to using the forgetting curve to evaluate experience and training factors in human reliability analysis

Traditional human reliability analysis (HRA) methods have difficulty dealing with the dynamic nature of factors such as time and rely on static and expert-judgment-based assessments of performance-shaping factors (PSFs) across limited levels. In this study, we introduce a mathematical approach for dynamically evaluating the experience and training PSF. Our proposed method integrates the psychological concept of the “forgetting curve” to evaluate how PSFs are impacted by the number of trainings and the time elapsed since training. To confirm the validity of the model, we provide experimental data fitted by identifying the quantitative relationship between training and human performance. This research enables dynamic and objective assessments, thus reducing reliance on subjective expert judgment and improving the accuracy of HRA.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Top-Performing Photovoltaic Cells Compared to the Shockley–Queisser Limit

Top-performing single-junction and two-terminal tandem devices that include at least one polycrystalline cell are compared with each other and their ideal limits. The parameters of open-circuit voltage, short-circuit current, and fill-factor are individually compared to the Shockley–Queisser limit to investigate where different technologies have room to improve. Technologies, such as silicon and cadmium telluride have the most room for improvement in open-circuit voltage currently utilizing 87% and 81% of their maxima, respectively. Detailed diode and fill-factor loss analysis is presented for single-junction devices to give further insight on how they compare and where efficiency is lost. Single-crystal technologies demonstrate a fill-factor closer to the Shockley–Queisser limit than polycrystalline devices. The high diode quality factor of polycrystalline devices is the leading cause of the decreased fill-factor. Similar analysis on tandem cells with at least one thin-film cell shows that although their efficiency exceeds that of the single-junction cells, the fraction of their ideal efficiency is smaller. Here, by comparing parameters to the Shockley–Queisser limit, it becomes clearer where certain technologies have the potential for improvement.

High efficiency↗
DOE OSTI2022

An Application of a Modified Beta Factor Method for the Analysis of Software Common Cause Failures

This paper presents an approach for modeling software common cause failures (CCFs) within digital instrumentation and control (I&C) systems. CCFs consist of a concurrent failure between two or more components due to a shared failure cause and coupling mechanism. This work emphasizes the importance of identifying software-centric attributes related to the coupling mechanisms necessary for simultaneous failures of redundant software components. The groups of components that share coupling mechanisms are called common cause component groups (CCCGs). Most CCF models rely on operational data as the basis for establishing CCCG parameters and predicting CCFs. This work is motivated by two primary concerns: (1) a lack of operational and CCF data for estimating software CCF model parameters; and (2) the need to model single components as part of multiple CCCGs simultaneously. A hybrid approach was developed to account for these concerns by leveraging existing techniques: a modified beta factor model allows single components to be placed within multiple CCCGs, while a second technique provides software-specific model parameters for each CCCG. This hybrid approach provides a means to overcome the limitations of conventional methods while offering support for design decisions under the limited data scenario.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗