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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Quantitative elemental imaging in eukaryotic algae

Abstract All organisms, fundamentally, are made from the same raw material, namely the elements of the periodic table. Biochemical diversity is achieved by how these elements are utilized, for what purpose, and in which physical location. Determining elemental distributions, especially those of trace elements that facilitate metabolism as cofactors in the active centers of essential enzymes, can determine the state of metabolism, the nutritional status, or the developmental stage of an organism. Photosynthetic eukaryotes, especially algae, are excellent subjects for quantitative analysis of elemental distribution. These microbes utilize unique metabolic pathways that require various trace nutrients at their core to enable their operation. Photosynthetic microbes also have important environmental roles as primary producers in habitats with limited nutrient supplies or toxin contaminations. Accordingly, photosynthetic eukaryotes are of great interest for biotechnological exploitation, carbon sequestration, and bioremediation, with many of the applications involving various trace elements and consequently affecting their quota and intracellular distribution. A number of diverse applications were developed for elemental imaging, allowing subcellular resolution, with X-ray fluorescence microscopy (XFM, XRF) being at the forefront, enabling quantitative descriptions of intact cells in a non-destructive method. This Tutorial Review summarizes the workflow of a quantitative, single-cell elemental distribution analysis of a eukaryotic alga using XFM.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Bayesian analysis for estimating statistical parameter distributions of elasto-viscoplastic material models

High temperature design methods rely on constitutive models for inelastic deformation and failure typically calibrated against the mean of experimental data without considering the associated scatter. Variability may arise from the experimental data acquisition process, from heat-to-heat material property variations, or both and need to be accurately captured to predict parameter bounds leading to efficient component design. Applying the Bayesian Markov Chain Monte Carlo (MCMC) method to produce statistical models capturing the underlying uncertainty in the experimental data is an area of ongoing research interest. This work varies aspects of the Bayesian MCMC method and explores their effect on the posterior parameter distributions for a uniaxial elasto-viscoplastic damage model using synthetically generated reference data. From our analysis with the uniaxial inelastic model we determine that an informed prior distribution including different types of test conditions results in more accurate posterior parameter distributions. The parameter posterior distributions, however, do not improve when increasing the number of similar experimental data. Additionally, changing the amount of scatter in the data affects the quality of the posterior distributions, especially for the less sensitive model parameters. Moreover, we perform a sensitivity study of the model parameters against the likelihood function prior to the Bayesian analysis. The results of the sensitivity analysis help to determine the reliability of the posterior distributions and reduce the dimensionality of the problem by fixing the insensitive parameters. The comprehensive study described in this work demonstrates how to efficiently apply the Bayesian MCMC methodology to capture parameter uncertainties in high temperature inelastic material models. Quantifying these uncertainties in inelastic models will improve high temperature engineering design practices and lead to safer, more effective component designs.

42 ENGINEERING↗
DOE OSTI2026

First simultaneous global QCD analysis of kaon and pion parton distributions with lattice QCD constraints

We perform the first simultaneous global QCD analysis of pion and kaon parton distribution functions (PDFs) constrained by pion- and kaon-induced Drell-Yan (DY) and leading neutron electroproduction data together with lattice QCD data on pion and kaon PDF moments. The analysis indicates a softer valence u ¯ distribution in the K − than in the π − and a significantly more peaked valence s -quark density in K − compared with the u ¯ . The effective exponent governing the high- x behavior of the PDF is found to be larger for u ¯ in the kaon, β u ¯ K − = 1.6 ( 2 ) , than in the pion, β u ¯ π − = 1.16 ( 4 ) , in the range 0.7 ≤ x ≤ 0.95 . From the gluon momentum fractions, we find the pion’s gluon content accounts for ≈ 1 / 3 of the mass budget of the pion at μ = 2 GeV , but only ≈ 1 / 4 for the kaon.

Barry, P. C. [Argonne National Laboratory] (ORCID:↗
DOE OSTI2024

Powered by PRECISE [Slides]

This presentation is part of the National Renewable Energy Laboratory's (NREL's) Powered By webinar series, hosted by the Grid Planning and Analysis Center. The series highlights NREL's impressive suite of grid planning and analysis tools to help attendees better understand their capabilities and applications. In this presentation, NREL power grid researchers, Killian McKenna and Darice Guittet, and the principal electrical distribution engineer at Sacramento Municipal Utility District, Sheikh Hassan, discuss NREL's PRECISE interconnection tool. PRECISE automates holistic distributed energy resource interconnection studies for distribution utilities by leveraging diverse utility datasets.

14 SOLAR ENERGY↗
DOE OSTI2020

Variations of the physical parameters of the blazar Mrk 421 based on analysis of the spectral energy distributions

Abstract We report on the variations of the physical parameters of the jet observed in the blazar Mrk 421, and discuss the origin of X-ray flares in the jet, based on analysis of several spectral energy distributions (SEDs). The SEDs are modeled using the one-zone synchrotron self-Compton model, its parameters determined using a Markov chain Monte Carlo method. The lack of data at TeV energies means many of the parameters cannot be uniquely determined and are correlated. These are studied in detail. We find that the optimal solution can be uniquely determined only when we apply a constraint to one of four parameters: the magnetic field (B), the Doppler factor, the size of the emitting region, and the normalization factor of the electron energy distribution. We used 31 sets of SEDs from 2009 to 2014 with optical–UV data observed with UVOT/Swift and the Kanata telescope, X-ray data with XRT/Swift, and γ-ray data with the Fermi Large Area Telescope. The result of our SED analysis suggests that, in the X-ray faint state, the emission occurs in a relatively small area (∼1016 cm) with a relatively strong magnetic field (B ∼ 10−1 G). The X-ray bright state shows a tendency opposite to that of the faint state, that is, a large emitting area (∼1018 cm), probably downstream of the jet, and a weak magnetic field (B ∼ 10−3 G). The high X-ray flux was due to an increase in the maximum energy of electrons. On the other hand, the presence of two kinds of emitting areas implies that the one-zone model is unsuitable for reproducing at least part of the observed SEDs.

Yamada, Yurika↗
DOE OSTI2022

Supervised Learning for Distribution Secondary Systems Modeling: Improving Solar Interconnection Processes

The current interconnection process and hosting capacity analysis for distributed energy resources (DERs), such as photovoltaics (PV) and battery energy storage systems, are based on analyzing grid network constraints (voltage and thermal) using only medium-voltage distribution network models. This is because most utilities do not have secondary low-voltage system models that connect service transformers and residential customers. This is important because in many cases the main impact of interconnecting DERs could occur on the low-voltage distribution systems. This paper proposes a supervised learning method to approximate local secondary models to improve the interconnection process. The proposed supervised learning method includes a decision tree model that predicts the secondary topology and a logistic regression model that predicts conductor types. The case studies demonstrate the benefits of including secondary low-voltage circuits in the interconnection process. We report the proposed modeling methodology is readily scalable and thus can reduce the cost and effort of PV interconnection for the industry and stakeholders.

14 SOLAR ENERGY↗
DOE OSTI2021

Microbial Taxa Distribution Data From 16S rRNA Analysis Of Desalination Operations At Carlsbad, CA And Tampa Bay, FL

This data set list the distribution of microbial taxa from three sets of sampling campaigns from unit operations in two large desalination facilities in the US conducted between March and May 2021. The desalination plants include the Claude "Bud" Lewis Carlsbad Desalination Plant in Carlsbad, California and the Seater Desalination facility in Tampa Bay, Florida.

16s rRNA gene analysis↗
DOE OSTI2021

Tunable Broad Light Emission from 3D “Hollow” Bromide Perovskites through Defect Engineering

We report hybrid halide perovskites consisting of corner-sharing metal halide octahedra and small cuboctahedral cages filled with counter cations have proven to be prominent candidates for many high-performance optoelectronic devices. The stability limits of their three-dimensional perovskite framework are defined by the size range of the cations present in the cages of the structure. In some cases, the stability of the perovskite-type structure can be extended even when the counterions violate the size and shape requirements, as is the case in the so-called "hollow" perovskites. In this work, we engineered a new family of 3D highly defective yet crystalline "hollow" bromide perovskites with general formula (FA) 1-x (en) x (Pb) 1-0.7x (Br) 3-0.4x (FA = formamidinium (FA + ), en = ethylenediammonium (en 2+ ), x = 0-0.44). Pair distribution function analysis shed light on the local structural coherence, revealing a wide distribution of Pb-Pb distances in the crystal structure as a consequence of the Pb/Br-deficient nature and en inclusion in the lattice. By manipulating the number of Pb/Br vacancies, we finely tune the optical properties of the pristine FAPbBr 3 by blue shifting the band gap from 2.20 to 2.60 eV for the x = 0.42 en sample. A most unexpected outcome was that at x > 0.33 en incorporation, the material exhibits strong broad light emission (1% photoluminescence quantum yield (PLQY)) that is maintained after exposure to air for more than a year. This is the first example of strong broad light emission from a 3D hybrid halide perovskite, demonstrating that meticulous defect engineering is an excellent tool for customizing the optical properties of these semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Towards understanding the magnetic properties of the breathing pyrochlore compound Ba3Yb2Zn5O11through single-crystal studies

Abstract Ba 3 Yb 2 Zn 5 O 11 is exceptional among breathing pyrochlore compounds for being in the nearly-decoupled limit where inter-tetrahedron interactions are weak, hosting isolated clusters or molecular magnet-like tetrahedra of magnetic ytterbium (Yb 3+ ) ions. In this work, we present the study carried out on single-crystal samples of the breathing pyrochlore Ba 3 Yb 2 Zn 5 O 11 , using a variety of magnetometry and neutron scattering techniques along with theoretical modeling. We employ inelastic neutron scattering to investigate the magnetic dynamics as a function of applied field (with respect to both magnitude and direction) down to a temperature of 70 mK, where inelastic scattering reveals dispersionless bands of excitations as found in earlier powder sample studies, in good agreement with a single-tetrahedron model. However, diffuse neutron scattering at zero field and dc-susceptibility at finite field exhibit features suggesting the presence of excitations at low-energy that are not captured by the single tetrahedron model. Analysis of the local structure down to 2 K via pair distribution function analysis finds no evidence of structural disorder. We conclude that effects beyond the single tetrahedron model are important in describing the low-energy, low-temperature physics of Ba 3 Yb 2 Zn 5 O 11 , but their nature remains undetermined.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Local order of orthorhombic weberite-type Y 3 TaO 7 as determined by neutron total scattering and density functional theory calculations

Weberite-type oxides are a family of oxides with A 3 BO 7 stoichiometry that can adopt different space groups depending on chemical composition. There is a discrepancy in previous studies as to whether Y 3 TaO 7 is the orthorhombic C222 1 or the Ccmm space group. Here, we describe the short- and long-range structural properties of weberite-type Y 3 TaO 7 using neutron total scattering data, which has a high sensitivity to the oxygen sublattice. Simultaneous analysis of both short- and long-range structural data via conventional Rietveld and small box modelling demonstrates that Y 3 TaO 7 is best modeled as C222 1 . While the Ccmm describes equally well the long-range structure, pair distribution function analysis revealed that the local atomic configuration can be best modelled as C222 1 . This is corroborated by first-principles calculations that confirm the energetic preference of the C222 1 over Ccmm. Further, neutron total scattering data are reported for the first time for the Y 3 TaO 7 weberite-type ceramics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

La 2 ⁢O 3 ⁢Mn 2 ⁢Se 2 : A correlated insulating layered d-wave altermagnet

Altermagnets represent a new class of magnetic phases without net magnetization, invariant under a combination of rotation and time reversal. Unlike conventional collinear antiferromagnets (AFM), altermagnets could lead to new correlated states and important material properties deriving from their nonrelativistic spin-split band structure. Indeed, they serve as the magnetic analogue of unconventional superconductors and can yield spin-polarized electrical currents in the absence of external magnetic fields, making them promising candidates for next-generation spintronics. Here, we report altermagnetism in the correlated insulator, magnetically ordered tetragonal oxychalcogenide, L⁢a 2 ⁢O 3⁢ M⁢n 2 ⁢S⁢e 2 . Symmetry analysis reveals a 𝑑 𝑥 2 −𝑦 2 -wave-like spin-momentum locking arising from the M⁢n 2 ⁢O Lieb lattice, supported by density functional theory (DFT) calculations. Magnetic measurements confirm the AFM transition below ∼166K while neutron pair distribution function analysis reveals a 2D short-range magnetic order that persists above the Néel temperature. Single crystals are grown and characterized using x-ray diffraction, optical and electron microscopy, and micro-Raman spectroscopy to confirm the crystal structure, stoichiometry, and uniformity. Furthermore, our findings establish L⁢a 2⁢ O 3 ⁢M⁢n 2⁢ S⁢e 2 as a model altermagnetic system realized on a Lieb lattice.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Interactively Assessing Disentanglement in GANs

Abstract Generative adversarial networks (GAN) have witnessed tremendous growth in recent years, demonstrating wide applicability in many domains. However, GANs remain notoriously difficult for people to interpret, particularly for modern GANs capable of generating photo‐realistic imagery. In this work we contribute a visual analytics approach for GAN interpretability, where we focus on the analysis and visualization of GAN disentanglement. Disentanglement is concerned with the ability to control content produced by a GAN along a small number of distinct, yet semantic, factors of variation. The goal of our approach is to shed insight on GAN disentanglement, above and beyond coarse summaries, instead permitting a deeper analysis of the data distribution modeled by a GAN. Our visualization allows one to assess a single factor of variation in terms of groupings and trends in the data distribution, where our analysis seeks to relate the learned representation space of GANs with attribute‐based semantic scoring of images produced by GANs. Through use‐cases, we show that our visualization is effective in assessing disentanglement, allowing one to quickly recognize a factor of variation and its overall quality. In addition, we show how our approach can highlight potential dataset biases learned by GANs.

Jeong, Sangwon↗
DOE OSTI2022

Forecasting Distributed PV Adoption in Barranquilla, Colombia [Slides]

The objective of the dGen Colombia project is to provide projections to 2050 on distributed PV deployment by sector for a range of scenarios for Barranquilla, Colombia. NREL used the open-source Distributed Generation Market Demand Model (dGen) adapted for international projects for this analysis. As part of this analysis, technical potential, economic potential, and adoption projections of rooftop and groundmount PV for the city of Barranquilla are presented. Five main scenarios and their combinations were modeled to provide insight on the impact of increased demand from electric vehicles, air conditioning, and time-of-use tariffs.

14 SOLAR ENERGY↗
DOE OSTI2023

Quantitative investigation of the short-range magnetic correlations in the candidate quantum spin liquid NaYbO 2

Here, we present a neutron diffraction study of NaYbO 2 , a candidate quantum spin-liquid (QSL) compound hosting a geometrically frustrated triangular lattice of magnetic Yb 3+ ions. We observe diffuse magnetic scattering that persists to at least 20 K, demonstrating the presence of short-range magnetic correlations in this system up to a relatively high-energy scale. Using a reverse Monte Carlo and magnetic pair distribution function analysis, we confirm the predominant antiferromagnetic nature of these correlations and show that the diffuse scattering data can be well described by noninteracting layers of Heisenberg or XY spins on the triangular lattice. We rule out Ising spins and short-range-ordered stripe or 120° phases as candidate ground states of NaYbO 2 . These results are consistent with a possible QSL ground state in NaYbO 2 and showcase the benefit of a combined reciprocal- and real-space analysis of materials with short-range magnetic correlations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Long-range and local crystal structures of the S r 1 - x C a x Ru O 3 perovskites

Here, the crystal structures of the Sr 1–x Ca x RuO 3 (0 ≤ x ≤ 1) perovskites are investigated using both long-range and local structural probes. High-resolution synchrotron powder x-ray-diffraction characterization at ambient temperature shows that the materials have orthorhombic long-range crystal structures to high precision, and we support previous work showing that Ca 2+ substitution for Sr 2+ primarily changes the tilting of rigid corner-sharing RuO 6 octahedra at their shared oxygen vertices. X-ray pair-distribution function analysis for SrRuO 3 , CaRuO 3 , and one intermediate composition show them to display monoclinic symmetry at the local level; when averaged over different domain orientations this yields orthorhombic symmetry in the long range, and no long-range or local phase transitions are observed between 80 and 300 K for materials with intermediate compositions. High-resolution transmission electron microscopy shows that the Sr/Ca distribution is random at the nanoscale. Lastly, we plot magnetic characteristics such as the ferromagnetic T c , Curie-Weiss theta, effective moment, and ambient temperature susceptibility vs the octahedral tilt and unit-cell volume.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Light Water Reactor Sustainability Program: Use of Time Distributions to Predict Operator Procedure Performance in Dynamic Human Reliability Analysis

The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework affords software capable of conducting human reliability analysis (HRA) using a dynamic approach built around operating procedures (OPs) from nuclear power plants (NPPs). Previous HUNTER reports document the development of this software tool, the coupling of HUNTER to the simulator code, the collection of operator performance data by using simulators to calibrate HUNTER models, and linking HUNTER to probabilistic risk assessment (PRA) software. The present report largely addresses two topics. The first is a new function in HUNTER called the HUNTER Procedure Performance Predictor (P3). HUNTER P3 uses HUNTER’s built in Monte Carlo tools featuring human performance variability to identify potential error traps in procedures. The second topic is time distribution analysis to generate time inputs for dynamic HRA. The current analysis was performed to investigate time distributions for task primitives, which are the minimum task unit of analysis used in dynamic HRA modeling. Using the time distribution data, the elapsed time for human actions in an extended loss of AC power (ELAP) scenario is then investigated. Time data and prediction are essential for modeling procedure performance.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method

Electrochemical impedance spectroscopy (EIS) is a key tool across various scientific disciplines, including energy sciences, chemistry, and biology, enabling the analysis of electrochemical systems. However, conventional methods for interpreting EIS data are often complex and model dependent. The distribution of relaxation times (DRT) offers a non-parametric approach that simplifies the interpretation process by providing a timescale interpretation of EIS data. This article provides a comprehensive review of current methods for DRT inversion. Additionally, a survey of practitioners highlights key challenges in the field. Here, the findings underscore the need for standardized DRT analysis and benchmarks, as well as the development of automated analysis tools. These advancements would improve the usability and interpretability of EIS data. Ultimately, implementing these improvements could not only propel the field forward but also expand the application of DRT in scientific research by making it accessible to a broader range of researchers, including those without specialized expertise in programming or statistics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

K-space algorithmic reconstruction (KAREN): a robust statistical methodology to separate Bragg and diffuse scattering

Diffuse scattering occurring in the Bragg diffraction pattern of a long-range-ordered structure represents local deviation from the governing regular lattice. However, interpreting the real-space structure from the diffraction pattern presents a significant challenge because of the dramatic difference in intensity between the Bragg and diffuse components of the total scattering function. In contrast to the sharp Bragg diffraction, the diffuse signal has generally been considered to be a weak expansive or continuous background signal. In this paper, using 1D and 2D models, it is demonstrated that diffuse scattering in fact consists of a complex array of high-frequency features that must not be averaged into a low-frequency background signal. To evaluate the actual diffuse scattering effectively, an algorithm has been developed that uses robust statistics and traditional signal processing techniques to identify Bragg peaks as signal outliers which can be removed from the overall scattering data and then replaced by statistically valid fill values. This method, described as a 'K-space algorithmic reconstruction' (KAREN), can identify Bragg reflections independent of prior knowledge of a system's unit cell. KAREN does not alter any data other than that in the immediate vicinity of the Bragg reflections, and reconstructs the diffuse component surrounding the Bragg peaks without introducing discontinuities which induce Fourier ripples or artifacts from underfilling `punched' voids. The KAREN algorithm for reconstructing diffuse scattering provides demonstrably better resolution than can be obtained from previously described punch-and-fill methods. The superior structural resolution obtained using the KAREN method is demonstrated by evaluating the complex ordered diffuse scattering observed from the neutron diffraction of a single plastic crystal of CBr 4 using pair distribution function analysis.

36 MATERIALS SCIENCE↗