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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The Critical Role of AlInP Window Design in III–V Rear-Emitter Solar Cells

This article highlights the critical role of window design on short circuit carrier collection in rear-emitter solar cells, as demonstrated through modeling and experiment using metamorphic GaAs y P 1-y . Ultimately, if the window design is not carefully considered, surface depletion caused by Fermi level pinning at the window/air interface can extend into regions of active collection resulting in a large increase in effective window/base interface recombination velocity. This was experimentally shown here to result in a potential AM1.5G photocurrent loss of 8.1 mA/cm 2 , or nearly 50%, based on integrated internal quantum efficiency (IQE). Associated IQE modeling and curve fitting indicate that the effective IRV at the GaAs 0.75 P 0.25 /Al 0.64 In 0.36 P interface is increased by multiple orders of magnitude when the window is not sufficiently thick or doped to fully contain the surface depletion to within the window layer. Calculations of the surface depletion depth as a function of doping and the surface Fermi pinning energy level provides insight into the fundamental limits of window thickness. As a result, this allows the estimation of the Al 0.64 In 0.36 P surface pinning level to be at least 1.25 eV below the conduction band edge, or in the bottom half of the bandgap.

14 SOLAR ENERGY↗
DOE OSTI2024

Composition and in situ structure of the Methanospirillum hungatei cell envelope and surface layer

Archaea share genomic similarities with Eukarya and cellular architectural similarities with Bacteria, though archaeal and bacterial surface layers (S-layers) differ. Using cellular cryo–electron tomography, we visualized the S-layer lattice surroundingMethanospirillum hungatei, a methanogenic archaeon. Though more compact than known structures,M. hungatei’s S-layer is a flexible hexagonal lattice of dome-shaped tiles, uniformly spaced from both the overlying cell sheath and the underlying cell membrane. Subtomogram averaging resolved the S-layer hexamer tile at 6.4-angstrom resolution. By fitting an AlphaFold model into hexamer tiles in flat and curved conformations, we uncover intra- and intertile interactions that contribute to the S-layer’s cylindrical and flexible architecture, along with a spacer extension for cell membrane attachment.M. hungateicell’s end plug structure, likely composed of S-layer isoforms, further highlights the uniqueness of this archaeal cell. These structural features offer advantages for methane release and reflect divergent evolutionary adaptations to environmental pressures during early microbial emergence.

Science & Technology - Other Topics↗
DOE OSTI2021

Quantifying Uncertainty in Tortuosity Estimates for Porous Electrodes

Measuring tortuosity in porous electrodes is important for understanding rate capability and optimizing design. Here, we describe an approach to determine electrode tortuosities and quantify the associated uncertainties by fitting a P2D model to discharge profiles from a standard rate capability test. A dimensionless current is identified as a design-of-experiment parameter that can be used to identify experiments that return confident estimates of tortuosity, even when other model parameters are not known with certainty. This approach is applied to analysis of L i x V 3 O 8 (LVO) electrodes and L i x N i 0.33 M n 0.33 C o 0.33 O 2 (NMC) electrodes. The details of the assumptions made in these measurements and their impact on the reported uncertainties are discussed. We also perform an uncertainty analysis on the standard method for quantifying tortuosity in the literature: electrochemical impedance spectroscopy collected under blocking electrolyte conditions. We find that confident estimates can be obtained using this approach even when uncertainties in equivalent circuit model parameters are considered.

25 ENERGY STORAGE↗
DOE OSTI2024

Integrating ytopt and libEnsemble to autotune OpenMC

Ytopt is a Python machine-learning-based autotuning software package developed within the ECP PROTEAS-TUNE project. The ytopt software adopts an asynchronous search framework that consists of sampling a small number of input parameter configurations and progressively fitting a surrogate model over the input-output space until exhausting the user-defined maximum number of evaluations or the wall-clock time. libEnsemble is a Python toolkit for coordinating workflows of asynchronous and dynamic ensembles of calculations across massively parallel resources developed within the ECP PETSc/TAO project. libEnsemble helps users take advantage of massively parallel resources to solve design, decision, and inference problems and expands the class of problems that can benefit from increased parallelism. In this paper we present our methodology and framework to integrate ytopt and libEnsemble to take advantage of massively parallel resources to accelerate the autotuning process. Specifically, we focus on using the proposed framework to autotune the ECP ExaSMR application OpenMC, an open source Monte Carlo particle transport code. OpenMC has seven tunable parameters some of which have large ranges such as the number of particles in-flight, which is in the range of 100,000 to 8 million, with its default setting of 1 million. Setting the proper combination of these parameter values to achieve the best performance is extremely time-consuming. Therefore, we apply the proposed framework to autotune the MPI/OpenMP offload version of OpenMC based on a user-defined metric such as the figure of merit (FoM) (particles/s) or energy efficiency energy-delay product (EDP) on Crusher at Oak Ridge Leadership Computing Facility. In conclusion, the experimental results show that we achieve the improvement up to 29.49% in FoM and up to 30.44% in EDP.

Autotuning↗
DOE OSTI2021

An adaptable technique for comparative image assessment: Application to crosswell electromagnetic survey design for fluid monitoring

Reservoir integrity stewardship accompanying carbon capture and sequestration considers fluid extraction and reinjection as a risk-mitigating method against overpressuring that could lead to caprock damage and ensuing [Formula: see text] leakage. Crosswell electromagnetics offers a technically viable monitoring method with the spatial volume coverage necessary for reservoir-encompassing pressure management. However, a certain logistic dilemma for deep gas sequestration into saline and thus electrically conductive aquifers is that crosswell magnetic-field measurements underperform in the imaging of more resistive plume bodies, further exacerbated when vertical arrays intersect, as opposed to surround, plumes. Furthermore, comparative synthetic-data plume imaging of such scenarios rates the information content of magnetic-field versus electric-field 3D crosswell layouts for reservoir and infrastructure conditions of a representative pilot site in a coastal area in Florida. The image quality of the resulting plume replications can be ranked numerically through a newly proposed semblance qualifier, appraising the model goodness of fit to a given reference. In contrast to common least-squares measures for goodness of fit, the semblance formulation uses classifying logistic function types, thus enabling a better distinction of predefined anomaly features.

58 GEOSCIENCES↗
DOE OSTI2020

Optimizing hybrid rotational femtosecond/picosecond coherent anti-Stokes Raman spectroscopy in nitrogen at high pressures and temperatures

We demonstrate the use of hybrid rotational femtosecond/picosecond (fs/ps) coherent anti-Stokes Raman spectroscopy (HR-CARS) as a technique for temperature measurements in nitrogen gas at high pressures and temperatures. A broadband pulse shaper-adjusted 42 fs pulse interacts with a narrow-bandwidth, frequency-upconverted 5.5 ps pulse in a cell containing N 2 at pressures of 1–70 atm and temperatures of 300–1000 K. A computational code is used to model spectra and fit experimental results to obtain best-fit temperatures. We demonstrate good qualitative fits as well as good accuracy and precision between thermocouple measured and best-fit temperatures over the explored pressure and temperature regimes. The overall average percentage temperature difference between thermocouple measurements and best-fit temperatures is − <#comment/> 0 . 3 % <#comment/> with a standard deviation of 7.1%, showing the suitability of HR-CARS for characterizing high-pressure and -temperature environments.

Torge Mecker, Nils (ORCID:0000000238977170)↗
DOE OSTI2020

Models of SIV rebound after treatment interruption that involve multiple reactivation events

In order to assess the efficacy of novel HIV-1 treatments leading to a functional cure, the time to viral rebound is frequently used as a surrogate endpoint. The longer the time to viral rebound, the more efficacious the therapy. In support of such an approach, mathematical models serve as a connection between the size of the latent reservoir and the time to HIV-1 rebound after treatment interruption. The simplest of such models assumes that a single successful latent cell reactivation event leads to observable viremia after a period of exponential viral growth. Here we consider a generalization developed by Pinkevych et al. and Hill et al. of this simple model in which multiple reactivation events can occur, each contributing to the exponential growth of the viral load. We formalize and improve the previous derivation of the dynamics predicted by this model, and use the model to estimate relevant biological parameters from SIV rebound data. We confirm a previously described effect of very early antiretroviral therapy (ART) initiation on the rate of recrudescence and the viral load growth rate after treatment interruption. We find that every day ART initiation is delayed results in a 39% increase in the recrudescence rate (95% credible interval: [18%, 62%]), and a 11% decrease of the viral growth rate (95% credible interval: [4%, 20%]). We show that when viral rebound occurs early relative to the viral load doubling time, a model with multiple successful reactivation events fits the data better than a model with only a single successful reactivation event.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Wave vector and field vector orientation dependence of Fe K pre-edge X-ray absorption features in clinopyroxenes

Abstract Pre-edge X-ray absorption features are commonly used to derive redox states for transition metal oxides in crystals and glasses. Several calibrations for Fe2+ and Fe3+ in silicate glasses have utilized the general relationships among pre-edge peak intensity, energy, and redox state. However, absorption variations complicate those relationships in anisotropic crystals. Although absorption anisotropy at and above the energy of the rising edge adheres to the typical cos2 relationship observed in absorption spectroscopies at other energies, the anisotropy of the pre-edge is far more complicated. Prior studies focusing on pre-edge absorption anisotropy demonstrate a 1-cos4φ dependence of absorption magnitudes with rotation. Experiments presented here show that absorption magnitudes of the pre-edge vary as a function of both electric field vector orientation and wave vector direction. However, rotations around the field vector axis or wave vector axis individually result in cos2 dependence of absorption magnitudes. Rotations where both wave vector and field vector orientation are varied are not well fit by either model in the pre-edge. The resulting anisotropy complicates the process of measuring characteristic absorption in the pre-edge, making valence state determinations challenging for strongly anisotropic crystal structures such as pyroxene.

Geochemistry & Geophysics↗
DOE OSTI2021

Assessing First-Order Dependence of Thermolytic HGR on Glycolate at Low Glycolate Concentrations

This report describes the results of testing performed to investigate the assumed first-order behavior of glycolate at low concentrations in the current Glycolate Thermolytic Hydrogen Generation Rate (HGR) expression. Four experiments were performed at 100 °C using a simulant based on a Tank 28 supernate sample, and the glycolate concentration in the experiments ranged from 5 - 175 mg/L. The thermolytic HGR results from all tests were well-described by the current Glycolate Thermolytic HGR Model. A linear fit of the Ln(HGR) and Ln(Gly) gave a suggested reaction order of 1.15. Additionally, by taking into account prior knowledge on how varying chemistry impacts the HGR, a reaction order of 0.99 was obtained. Both cases suggest that the data validates the assumed first-order dependence of HGR on glycolate.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Primer for OTERR Core Reloading Optimization

OTERR (Optimization of Test Reactor Reloading) is a software tool which assists in finding optimal fuel assembly reloading patterns for nuclear reactors. It was created specifically to support the Versatile Test Reactor (VTR) program, but its functionality is general enough to be applied to most fast spectrum reactors which use hexagonal prismatic fuel elements. This document is meant to be a primer for new users of OTERR to walk through example workflows for core reloading optimization cases. Simple cases are followed step-by-step to discuss what needs to be done to complete a reloading optimization sequence. Note that the intent of this document is to provide practical examples for users to follow along with so they can quickly start using OTERR and then make changes to fit their own modeling needs. Detail is limited in terms of addressing additional features not used in these examples and especially lacking in discussion of theory used in the code. To better address these points, users are highly encouraged to refer to the OTERR User Manual and the OTERR Theory Manual.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Centrifugal Pump Model for System Codes for Advanced NPP Designs

In this document, a homologous model and one-dimensional line model for centrifugal pump are described to provide the theoretical background of a pump model to be developed in system-level codes. Input and output parameters are proposed, along with a summary of the governing equations for each model. Furthermore, hydraulic performance degradation of centrifugal pump is also modeled in the homologous pump model. This document suggests that system codes provide a homologous and one-dimensional line model for centrifugal pumps, allowing the users to choose the model that best fits their purposes.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Unlocking Metamaterials At The Macro Scale (CRADA Final Report)

This project was part of the Cyclotron Road program, which supports scientific entrepreneurs in their efforts to commercialize novel technologies with potential to address energy, manufacturing and climate related issues. The participants' technology is a lightweight cellular material system which could be applied to a range of products and markets and offer benefits of reduced weight, cost, waste, and carbon footprint. The objective of the project was to investigate potential opportunities and de-risk technical and market barriers in pursuit of successful commercialization. This project’s purpose was to find market pathways and technical roadmaps for commercializing the lightweight cellular material technology. The main problems to overcome are the risks in both tech and market. On the technical side, performance, weight, cost and speed of manufacturing, and other scaleup problems needed to be addressed. On the market side, the challenges included finding product/market fit, developing business models and go to market strategies, and developing commercial relationships within various industries. Our approach typically started with market analysis, in order to identify potential applications where our technology could solve problems and address pain points. To do this, we performed customer discovery, interviewing hundreds of industry stakeholders along all parts of the value chain for a given product or industry. From here, we would develop technoeconomic models which combined aspects of numerical modeling for structural and mechanical performance based on criteria from customers or industry guidelines such as stiffness, strength, weight, and other physical properties. Then, this would be combined with detailed cost models to translate the engineering solution into a manufacturable, scalable product. The challenge here was to have equal or better performance at lower cost and higher speed than existing solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Segmentation Model Distillation [Poster]

The process of training object detection (OD) or image segmentation model requires both a substantial amount of data and technical knowledge, which often creates challenges in applying these types of models to their full potential. In order to streamline the process of developing these models, we propose a new pipeline where a foundation model assists in the dataset generation. Then this resulting dataset is used to fine-tune a fast light-weight model to perform the custom segmentation or OD. This resulting model is also fit for real-time image segmentation, such as in a video stream.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Solar Decarbonization of Paraffin Dehydrogenation Through Particle Heat Carriers (Final Technical Report)

This project focuses on solutions to decarbonize high-temperature catalytic processes using solar thermal heat. The primary project goal is to show the validity of a moving packed bed reactor for propane dehydrogenation using catalyst particles as the heat carrier for the reaction, which can be heated by concentrated solar energy in a particle receiver. This concept, if further developed, may provide a cost-effective pathway for converting lower value gases to important chemical precursors for industrial materials using only renewable energy. The project was divided into six tasks. In Task 1, DFT calculations were performed to understand the role of Pt and Sn in the catalytic dehydrogenation reaction. In Task 2 chemical kinetics measurements were made for several catalyst formulations at high temperatures. In Task 3, the solar absorptance of catalyst particles was compared to the absorptance of commonly used materials in particle receivers. In Task 4, numerical models were developed which could predict performance of the complete system and predict specific temperatures in the system. In Task 5, a prototype system was designed, fabricated, and tested to show the validity of the concept. Task 6 concerned project management activities. Experiments with the prototype showed repeatable thermal performance at temperatures targeted for the reaction. A limited set of tests were done with active catalyst and propane dehydrogenation, showing conversion of propane to propylene with a range of conversions and selectivities. The results are promising, and the prototype designed was reliable during testing, and the team expects that further development of the prototype would yield improved results. A numerical model framework based on coupled fluid and particle mechanics was developed with high computational efficiency using GPU calculations. The model may prove highly useful for evaluating other high-temperature particle systems. However, it was determined that simpler porous media models were good fits for the needs of the current moving packed bed concept. Data showing strong solar absorption of the particles validates the plan of using existing solar particle receivers with only a change in the particle type. Catalyst investigation showed that Pt 1 Sn 3 is the most viable candidate for developing PtSn catalysts for high temperature propane dehydrogenation, considering the balance of activity, selectivity, and deactivation. This project completed an initial study of various factors needed to incorporate a moving bed catalytic reactor for propane dehydrogenation into a concentrated solar thermal particle system. Future developments may allow this technology to be scaled up and help to use solar thermal energy to decarbonize not only the propane dehydrogenation reaction, but other gas-solid catalytic reactions at similar temperatures.

14 SOLAR ENERGY↗
DOE OSTI2024

Weak Gravitational Lensing around Low Surface Brightness Galaxies in the DES Year 3 Data

We present galaxy-galaxy lensing measurements using a sample of low surface brightness galaxies (LSBGs) drawn from the Dark Energy Survey Year 3 (Y3) data as lenses. LSBGs are diffuse galaxies with a surface brightness dimmer than the ambient night sky. These dark-matter-dominated objects are intriguing due to potentially unusual formation channels that lead to their diffuse stellar component. Given the faintness of LSBGs, using standard observational techniques to characterize their total masses proves challenging. Weak gravitational lensing, which is less sensitive to the stellar component of galaxies, could be a promising avenue to estimate the masses of LSBGs. Our LSBG sample consists of 23,790 galaxies separated into red and blue color types at g - i ≥ 0.60 and g - i < 0.60 , respectively. Combined with the DES Y3 shear catalog, we measure the tangential shear around these LSBGs and find signal-to-noise ratios of 6.67 for the red sample, 2.17 for the blue sample, and 5.30 for the full sample. We use the clustering redshifts method to obtain redshift distributions for the red and blue LSBG samples. Assuming all red LSBGs are satellites, we fit a simple model to the measurements and estimate the host halo mass of these LSBGs to be log(M host /M ⊙ ) = $12.98^{+0.10}_{-0.11}$. We place a 95% upper bound on the subhalo mass at log(M sub /M ⊙ ) < 11.51. By contrast, we assume the blue LSBGs are centrals, and place a 95% upper bound on the halo mass at log(M host /M ⊙ ) < 11.84. We find that the stellar-to-halo mass ratio of the LSBG samples is consistent with that of the general galaxy population. This work illustrates the viability of using weak gravitational lensing to constrain the halo masses of LSBGs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Biomembrane Structure and Material Properties Studied With Neutron Scattering

Cell membranes and their associated structures are dynamical supramolecular structures where different physiological processes take place. Detailed knowledge of their static and dynamic structures is therefore needed, to better understand membrane biology. The structure–function relationship is a basic tenet in biology and has been pursued using a range of different experimental approaches. In this review, we will discuss one approach, namely the use of neutron scattering techniques as applied, primarily, to model membrane systems composed of lipid bilayers. An advantage of neutron scattering, compared to other scattering techniques, is the differential sensitivity of neutrons to isotopes of hydrogen and, as a result, the relative ease of altering sample contrast by substituting protium for deuterium. This property makes neutrons an ideal probe for the study of hydrogen-rich materials, such as biomembranes. In this review article, we describe isotopic labeling studies of model and viable membranes, and discuss novel applications of neutron contrast variation in order to gain unique insights into the structure, dynamics, and molecular interactions of biological membranes. We specifically focus on how small-angle neutron scattering data is modeled using different contrast data and molecular dynamics simulations. We also briefly discuss neutron reflectometry and present a few recent advances that have taken place in neutron spin echo spectroscopy studies and the unique membrane mechanical data that can be derived from them, primarily due to new models used to fit the data.

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

Evaluating the Benefits of Bayesian Hierarchical Methods for Analyzing Heterogeneous Environmental Datasets: A Case Study of Marine Organic Carbon Fluxes

Large compilations of heterogeneous environmental observations are increasingly available as public databases, allowing researchers to test hypotheses across datasets. Statistical complexities arise when analyzing compiled data due to unbalanced spatial sampling, variable environmental context, mixed measurement techniques, and other reasons. Hierarchical Bayesian modeling is increasingly used in environmental science to describe these complexities, however few studies explicitly compare the utility of hierarchical Bayesian models to simpler and more commonly applied methods. Here we demonstrate the utility of the hierarchical Bayesian approach with application to a large compiled environmental dataset consisting of 5,741 marine vertical organic carbon flux observations from 407 sampling locations spanning eight biomes across the global ocean. We fit a global scale Bayesian hierarchical model that describes the vertical profile of organic carbon flux with depth. Profile parameters within a particular biome are assumed to share a common deviation from the global mean profile. Individual station-level parameters are then modeled as deviations from the common biome-level profile. The hierarchical approach is shown to have several benefits over simpler and more common data aggregation methods. First, the hierarchical approach avoids statistical complexities introduced due to unbalanced sampling and allows for flexible incorporation of spatial heterogeneitites in model parameters. Second, the hierarchical approach uses the whole dataset simultaneously to fit the model parameters which shares information across datasets and reduces the uncertainty up to 95% in individual profiles. Third, the Bayesian approach incorporates prior scientific information about model parameters; for example, the non-negativity of chemical concentrations or mass-balance, which we apply here. We explicitly quantify each of these properties in turn. We emphasize the generality of the hierarchical Bayesian approach for diverse environmental applications and its increasing feasibility for large datasets due to recent developments in Markov Chain Monte Carlo algorithms and easy-to-use high-level software implementations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Relationships between Vehicle Pricing and Features: Data Driven Analysis of the Chinese Vehicle Market

A full-scale understanding of the dynamics of the Chinese vehicle market can benefit stakeholders with respect to rational decision-making and effective long-term investment. This study attempts to discover the common vehicle pricing patterns in the Chinese market by quantifying statistical correlations among critical vehicle features from intrinsic powertrain systems to extrinsic market positioning. The data samples involve almost all passenger vehicle models sold in 2013 to 2019. After comparing multiple statistical methodologies, a log-transformation variant of the multinomial linear regression model was found to be the best one, and the goodness of fit shows that this model can offer stable estimates, which were validated using 2019 market data. The insights achieved are: (1) The price and major performance features of SUVs/crossovers are similar to those of sedans; (2) If all other explicit features remain the same, the price of a Japanese midsize sedan is 62% higher than that of a Chinese midsize sedan, and European midsize vehicles have the highest prices overall. (3) The incremental price of fuel consumption varies by vehicle class and fuel economy. For example, from 30 to 50 MPG, the vehicle price increases by $119 for a Chinese brand sedan vehicle, by $69 for a Chinese brand SUV.

33 ADVANCED PROPULSION SYSTEMS↗