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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

Critical assessment of the recent report on the gigaparsec-scale correlation of the orientations of large quasar groups

ABSTRACT Recently, it was reported that large quasar groups (LQGs) identified from the Sloan Digital Sky Survey (SDSS) data release seven catalogue are not randomly oriented but preferentially aligned or orthogonal over scales 1–2 Gpc. To confirm this claim, I reproduced the same LQG sample and performed Sobolev tests of uniformity on the LQG orientation axes in the redshift space. Contrary to the original report based on the bimodal distribution of the LQG position angles in the sky, I found no departure from uniformity in the distribution of the LQG orientation axes. I also examined whether the LQGs are physical structures using a statistically more reliable data set constructed from the SDSS data release 16 (DR16) large-scale structure (LSS) quasar catalogue. Considering the Gaussian primordial density fluctuations and shot noise, I estimated the mass density contrasts of the LQGs from the number counts of the DR16 LSS quasars and found that most of the LQGs do not trace statistically significant high-density regions. I conclude that the LQG sample is a collection of unphysical chance associations and should not be used for any cosmological studies.

Fujii, Hirokazu (ORCID:0000000161473512)↗
DOE OSTI2025

Universality of Rényi Entropy in Conformal Field Theory

We use the thermal effective theory to prove that, for the vacuum state in any conformal field theory in 𝑑 dimensions, the 𝑛th Rényi entropy 𝑆$^{(𝑛)}_{𝐴}$ behaves as 𝑆$^{(𝑛)}_{𝐴}$ = [𝑓⁡/(2⁢𝜋⁢𝑛) 𝑑−1 ]⁢[Area⁡(∂𝐴)/(𝑑−2)⁢𝜀 𝑑−2 ]⁢(1+𝑂⁡(𝑛)) in the 𝑛 → 0 limit when the boundary of the entanglement domain 𝐴 is spherical with the UV cutoff 𝜀. The theory dependence is encapsulated in the cosmological constant 𝑓 in the thermal effective action. Using this result, we estimate the density of states for large eigenvalues of the modular Hamiltonian for the domain 𝐴. In two dimensions, we can use the hot spot idea, which describes the effective action in the high-temperature limit when the temperature is position-dependent, to derive more powerful formulas valid for arbitrary positive 𝑛. We discuss the difference between two and higher dimensions and clarify the applicability of the hot spot idea. We also use the thermal effective theory to derive an analog of the Cardy formula for boundary operators in higher dimensions.

Conformal field theory↗
DOE OSTI2023

Quasiparticle Spectroscopy, Transport, and Magnetic Properties of Nb Films Used in Superconducting Qubits

Niobium thin films on silicon substrate used in the fabrication of superconducting qubits have been characterized using scanning and transmission electron microscopy, electrical transport, magnetization, the London penetration depth - based quasiparticle spectroscopy, and real-space real-time magneto-optical imaging. Here we study niobium films to provide an example of a comprehensive analytical set that may benefit superconducting circuits such as those used in quantum computers. The films have a superconducting transition temperature of T c = 9.35 K and a fairly clean superconducting gap. The estimated superfluid density is enhanced at intermediate temperatures. These observations are consistent with the recent theory of anisotropic strong-coupling superconductivity in Nb and indicate outstanding quality. However, the response to the magnetic field is complicated, exhibiting significantly irreversible behavior and insufficient heat dissipation (to a substrate), leading to thermomagnetic instabilities. This may present a challenge for further improvement of transmon quantum coherence. Possible mitigation strategies are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Mixed-State Entanglement from Local Randomized Measurements

In this work, we propose a method for detecting bipartite entanglement in a many-body mixed state based on estimating moments of the partially transposed density matrix. The estimates are obtained by performing local random measurements on the state, followed by postprocessing using the classical shadows framework. Our method can be applied to any quantum system with single-qubit control. We provide a detailed analysis of the required number of experimental runs, and demonstrate the protocol using existing experimental data [Brydges et al., Science 364, 260 (2019)].

1-dimensional spin chains↗
DOE OSTI2026

Spray-Coated Silver as Backside Metal for III–V Photovoltaic Devices on GaAs and Ge Substrates

The accelerated increase in demand for III-V space photovoltaics on GaAs and Ge substrates, as well as growing interests in terrestrial applications, motivate the development of cost-effective, high-throughput processing routes of these materials. Here, in this study, we assess spray-coated silver (Ag) back contact metallization as a substitute for electron-beam-evaporated metals currently used in industry. We find that the spray-coated Ag films are dense and continuous. By means of quantum efficiency, dark current-voltage, and illuminated current-voltage characterizations, we show that spray-coated GaAs and Ge solar cells perform similarly to baseline devices with electroplated Au, including under high current densities. We estimate that the thresholds for specific contact resistance below which back contacts do not significantly contribute to resistive loss are 2.1 x 10 -1 Ω•cm 2 for GaAs and 4.7 x 10 -2 Ω•cm 2 for Ge. We experimentally confirm that our spray-coated samples meet these requirements. Peel tests show that the adhesion of plain spray-coated Ag films to the back of p-type Ge substrates used in III-V solar cells is currently insufficient, whereas adhesion to p-type GaAs substrates is outstanding and requires no further optimization.

14 SOLAR ENERGY↗
DOE OSTI2020

A genoscape–network model for conservation prioritization in a migratory bird

Migratory animals are declining worldwide and coordinated conservation efforts are needed to reverse current trends. We devised a novel genoscape-network model that combines genetic analyses with species distribution modeling and demographic data to overcome challenges with conceptualizing alternative risk factors in migratory species across their full annual cycle. We applied our method to the long distance, Neotropical migratory bird, Wilson's Warbler (Cardellina pusilla). Despite a lack of data from some wintering locations, we demonstrated how the results can be used to help prioritize conservation of breeding and wintering areas. For example, we showed that when genetic, demographic, and network modeling results were considered together it became clear that conservation recommendations will differ depending on whether the goal is to preserve unique genetic lineages or the largest number of birds per unit area. More specifically, if preservation of genetic lineages is the goal, then limited resources should be focused on preserving habitat in the California Sierra, Basin Rockies, or Coastal California, where the 3 most vulnerable genetic lineages breed, or in western Mexico, where 2 of the 3 most vulnerable lineages overwinter. Alternatively, if preservation of the largest number of individuals per unit area is the goal, then limited conservation dollars should be placed in the Pacific Northwest or Central America, where densities are estimated to be the highest. Overall, our results demonstrated the utility of adopting a genetically based network model for integrating multiple types of data across vast geographic scales and better inform conservation decision-making for migratory animals.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Combined Data and Deep Learning Model Uncertainties: An Application to the Measurement of Solid Fuel Regression Rate

In complex physical process characterization, such as the measurement of the regression rate for solid hybrid rocket fuels, where both the observation data and the model used have uncertainties originating from multiple sources, combining these in a systematic way for quantities of interest (QoI) remains a challenge. In this paper, we present a forward propagation uncertainty quantification (UQ) process to produce a probabilistic distribution for the observed regression rate r. We characterized two input data uncertainty sources from the experiment (the distortion from the camera U c and the non-zero-angle fuel placement U Y ), the prediction and model form uncertainty from the deep neural network (U m ), as well as the variability from the manually segmented images used for training it (U s ). Here, we conducted seven case studies on combinations of these uncertainty sources with the model form uncertainty. The main contribution of this paper is the investigation and inclusion of the experimental image data uncertainties involved, and how to include them in a workflow when the QoI is the result of multiple sequential processes.

42 ENGINEERING↗
DOE OSTI2023

Estimating Compressional Velocity and Bulk Density Logs in Marine Gas Hydrates Using Machine Learning

Compressional velocity (Vp) and bulk density (ρb) logs are essential for characterizing gas hydrates and near-seafloor sediments; however, it is sometimes difficult to acquire these logs due to poor borehole conditions, safety concerns, or cost-related issues. We present a machine learning approach to predict either compressional Vp or ρb logs with high accuracy and low error in near-seafloor sediments within water-saturated intervals, in intervals where hydrate fills fractures, and intervals where hydrate occupies the primary pore space. We use scientific-quality logging-while-drilling well logs, gamma ray, ρb, Vp, and resistivity to train the machine learning model to predict Vp or ρb logs. Of the six machine learning algorithms tested (multilinear regression, polynomial regression, polynomial regression with ridge regularization, K nearest neighbors, random forest, and multilayer perceptron), we find that the random forest and K nearest neighbors algorithms are best suited to predicting Vp and ρb logs based on coefficients of determination (R2) greater than 70% and mean absolute percentage errors less than 4%. Given the high accuracy and low error results for Vp and ρb prediction in both hydrate and water-saturated sediments, we argue that our model can be applied in most LWD wells to predict Vp or ρb logs in near-seafloor siliciclastic sediments on continental slopes irrespective of the presence or absence of gas hydrate.

Naim, Fawz↗
DOE OSTI2022

CLASSY IV. Exploring UV Diagnostics of the Interstellar Medium in Local High- z Analogs at the Dawn of the JWST Era

The Cosmic Origins Spectrograph (COS) Legacy Archive Spectroscopic SurveY (CLASSY) provides the first high resolution spectral catalog of 45 local high-z analogs in the ultraviolet (UV; 1200–2000 Å) to investigate their stellar and gas properties. Here we present a toolkit of UV interstellar medium (ISM) diagnostics, analyzing the main emission lines of CLASSY spectra (N IV] λλ1483,87, C IV λλ1548,51, He IIλ1640, O III]λλ1661,6, Si III] λλ1883,92, C III] λ1907,9). Specifically, our aim is to provide accurate diagnostics for the reddening E(B - V), electron density n e , electron temperature T e , metallicity 12+log(O/H), and ionization parameter log(U), taking the different ISM ionization zones into account. We calibrate our UV toolkit using well-known optical diagnostics, analyzing archival optical spectra for all CLASSY targets. We find that UV density diagnostics estimate n e values that are ~1–2 dex higher (e.g., n e (C III] λλ1907,9) ~ 10 4 cm -3 ) than those inferred from their optical counterparts (e.g., n e ([S II]λλ6717,31) ~ 10 2 cm -3 ; n e ([Ar IV]λλ4714,41) ~ 10 3 cm -3 ). T e derived from the hybrid ratio [O III] λ1666/λ5007 proves to be reliable, implying differences in determining 12+log(O/H) compared to the optical counterpart O III] λ4363/[O III] λ5007 within ~ ±0.3 dex. We also investigate the relation between the stellar and gas E(B - V), finding consistent values at high specific star formation rates (sSFRs; log sSFR ≳ -8 yr -1 ), while at low sSFRs we confirmed an excess of dust attenuation in the gas. Finally, we investigate UV line ratios and equivalent widths to provide correlations with 12+log (O/H) and log(U), but note that there are degeneracies between the two. With this suite of UV-based diagnostics, we illustrate the pivotal role CLASSY plays in understanding the chemical and physical properties of high-z systems that JWST can observe in the rest-frame UV.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Verification and Validation of the Stakeholder Tool for Assessing Radioactive Transportation (START) – 22323

The U.S. Department of Energy (DOE) Office of Integrated Waste Management is planning for the eventual transportation, storage, and disposal of spent nuclear fuel (SNF) and high-level radioactive waste (HLW) from nuclear power plant and DOE sites. The Stakeholder Tool for Assessing Radioactive Transportation (START) is a web-based, geospatial decision-support tool developed for evaluating routing options and other aspects of transporting SNF and HLW, covering rail, truck, barge, and intermodal infrastructure and operations in the continental United States. The verification and validation (V&V) process is intended to independently assess START to provide confidence in the ability of START to accurately provide intended results. The V&V process checks the START tool using a variety of methods, ranging from independent hand calculations to comparison of START performance and results to those of other codes. The V&V activity was conducted independently from the START development team with opportunities to provide feedback and collaborate throughout the process. The V&V analyzed attributes of transportation routes produced by START, including route distance and both population and population density captured within buffer zones around routes. Population in the buffer zone, population density in the buffer zone, and route distance were all identified as crucial outputs of the START code and were subject to V&V tasks. Some of the improvements identified through the V&V process were standardizing the underlying population data in START, changing the projection of the population raster data, and changes to the methodology used for population density to improve its applicability for expected users. This collaboration also led to suggested improvements to some of the underlying shape file segments within START. A formal series of test routes went through the V&V process from START version 3.2.1 following the implementation of the recommended improvements to START. The V&V of the buffer zone population and distance reported in START were achieved by utilizing a custom workflow developed in QGIS. This platform was chosen because it is fully independent of START. The buffer zone population and route distances in START showed excellent agreement to independent V&V test results. Over 200 route test cases were run; in all cases, the percent difference in the population within the buffer zone was less than +/- 5%, and the majority of cases were below +/- 1%. These cases were also duplicated in ArcMap, which is Environmental Systems Research Institute’s (ESRI) GIS desktop application. The ArcMap results also show good agreement; however, they cannot be considered independent of START because START also uses ESRI software. The V&V tasks are currently addressing population density and estimated radiation dose in START as well as implementing further automation of the V&V process to allow larger suites of test routes to be run more easily and quickly by less experienced GIS users. These improvements to the V&V process will make it a valuable tool for the development team and the stakeholders so that each new iteration of START can easily be checked for quality and consistency. This paper and presentation will describe the V&V process, findings and implications, and ongoing V&V activities.

START, DOE, Transporation, dose, GIS↗
DOE OSTI2025

Socio-Techno-Economic Feasibility of Deep Geothermal with EGS for Residential District Heating in the Northeastern United States

In this paper, we present socio-techno-economic simulation results for enhanced geothermal system (EGS) district heating systems in the northeastern United States. We applied the geospatial Distributed Geothermal Market Demand (dGeo) tool coupled with GEOPHIRES to evaluate the feasibility of geothermal deep direct-use, utilizing EGS reservoirs for providing residential heating with district heating systems. The results were combined with JEDI results to assess social impacts. Simulation results assuming doublet EGS reservoirs with target production temperature of 80 degrees C and newly constructed district heating systems indicate a wide range in system levelized cost of heat (LCOH) values ranging from ~$15/MMBtu to over $1,000/MMBtu, with most the attractive regions urban areas with high total thermal demand and high thermal demand density. We estimate about 60 GWth in potential installed capacity with LCOH values under $50/MMBtu and 100 GWth in potential capacity with LCOH values under $100/MMBtu, respectively.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Three dimensional cluster analysis for atom probe tomography using Ripley’s K-function and machine learning

The size and structure of spatial molecular and atomic clustering can significantly impact material properties and is therefore important to accurately quantify. Ripley’s K-function (K(r)), a measure of spatial correlation, can be used to perform such quantification when the material system of interest can be represented as a marked point pattern. This work demonstrates how machine learning models based on K (r)-derived metrics can accurately estimate cluster size and intra-cluster density in simulated three dimensional (3D) point patterns containing spherical clusters of varying size; over 90% of model estimates for cluster size and intra-cluster density fall within 11% and 18% error of the true values, respectively. These K (r)-based size and density estimates are then applied to an experimental APT reconstruction to characterize MgZn clusters in a 7000 series aluminum alloy. Here we find that the estimates are more accurate, consistent, and robust to user interaction than estimates from the popular maximum separation algorithm. Using K (r) and machine learning to measure clustering is an accurate and repeatable way to quantify this important material attribute.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Addressing the impact of Lyman opacity in inference of divertor plasma conditions with 2D spectroscopic camera analysis of Balmer emission during detachment in JET L-mode plasmas

The impact of re-absorption of the deuterium Lyman series emission was addressed in inferring divertor plasma conditions from Balmer series emission with 2D spectroscopic camera analysis during detachment in JET L-mode plasmas. The previously presented methodology was amended by modifying the standard photon emission coefficients and ionization and recombination rate coefficients of the ADAS database to consider the re-population of excited states due to Lyman opacity. This resulted in the estimate for the atomic density near the outer strike point to decrease by up to 75% at the onset of detachment at strike point temperatures of T e,osp ≈ 1.0–3.0 eV with respect to the strongly overestimated previously obtained values, whereas the estimated electron temperature and density were unaffected by the opacity correction within the scatter of the data and only a moderate reduction by up to 20% was observed in the estimate for the molecularly induced fraction of the Balmer emission. No noticeable change was seen in the ionization rate, calculated from the estimated outer strike point conditions, due to the decrease in the atomic density estimate compensating for the increased values of the opacity-corrected ADAS rate coefficients for ionization. In detached conditions at T e,osp ≈ 0.5–1.0 eV, 25%–35% lower recombination rates were provided by the opacity-corrected model. The observed effects on the experimental analysis were supported by a corresponding synthetic analysis based on EDGE2D-EIRENE simulations.

Balmer emission↗
DOE OSTI2021

Recalculation of Soil Bulk Density Used in the Scorpius MCNP6 Model

The soil composition used in the Scorpius MCNP6.2 (Ref. 1) model was recently recalculated. Originally, it was “determined using the United States Geological Survey (USGS) Mercury Core Library and the Nevada National Security Site U.S. Geological Survey Databases (NNSS USGS) and Nevada National Security Site Petrographic, Geochemical, and Geophysical Database (NNSS PGG),” but the details had been lost. Reference 2 documents the updated soil composition determination. Reference 2 estimated the grain density of the soil instead of the bulk density. This report corrects that error. I am indebted to Garrett Euler (EES-17) for reading Ref. 2, pointing out its errors, and guiding me through the correct calculations. This report is organized as follows. For completeness, the composition calculations from Ref. 2 are repeated: Sec. II discusses the data that are reported in the PGG Access database, and Sec. III uses the data in the PGG Access database to compute the composition of the soil. Section IV estimates the bulk density of the soil. Section V evaluates the soil wall thickness in the Scorpius model. Section VI estimates the effect of the soil density change on previously calculated results. Section VII presents a summary and conclusions. Input files and output files are listed in appendices.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

Efficient screening of rare large pit anomalies on polished surfaces using a minimalist sampling scheme

Lawrence Livermore National Laboratory (LLNL) has made significant strides in generating clean energy through its inertial confinement fusion (ICF) experiments. These experiments rely on high-density carbon (HDC) coated shells to encapsulate the fusion fuel. The success of these experiments is heavily dependent on the surface quality of these shells, as even minor imperfections, such as deep pits, can negatively impact fusion yield. Ensuring the required smoothness involves an extensive surface-finishing process that spans approximately 20 stages, making it both time-intensive and resource-demanding. A critical challenge in this process is the need for high-resolution scans to detect rare deep pits, which can be costly and impractical if performed on every shell. This highlights the necessity of developing more efficient scanning methods to optimize time and cost without compromising accuracy. To address these challenges, we introduce a novel approach that employs the multivariate Dvoretzky–Kiefer–Wolfowitz (DKW) inequality to provide a probabilistic upper bound on the error in estimating pit distribution characteristics via a Kernel Density Estimator (KDE). This error bound enables efficient and reliable estimation of pit distribution characteristics at a specified statistical confidence level using a minimal number of surface scans. The integrated DKW-KDE approach was validated through surface-finishing experiments across two batches of HDC-coated shells, demonstrating consistent and robust performance across multiple stages of the surface-finishing experiments. The validation studies suggest that the integrated DKW-KDE approach achieves comparable accuracy in estimating the risk of deleterious large pits with six scans, thus conserving time and resources. Further evaluations show that performance remains consistent across batches and over multiple polishing stages. In conclusion, based on these findings, one can leverage the minimal-scan insights to strategically improve the bottleneck inspection process, thus enhancing the productivity and quality of shell polishing and similar challenging manufacturing processes.

Inertial confinement fusion↗
DOE OSTI2024

An Overview of the Molten Salt Thermal Properties Database--Thermophysical, Version 3.1 (MSTDB-TP v.3.1)

This report presents the current status of the Molten Salt Thermal Properties Database–Thermophysical (MSTDB-TP). Information regarding version 3.1 is provided herein, which contains 820 individual salt entries (data from 180+ independent studies); the thermophysical properties contained in the database include density, viscosity, thermal conductivity, and heat capacity. The major updates to the database include a significant expansion of pseudobinary and higher-order chloride salt mixtures, many of which bearing actinides, and an incorporation of more recent literature data (i.e., that within the past 5 years). Also, modifications have been made to the pure compound data in the database as a consequence of an external quality assessment of duplicate datasets. The user-facing API for the MSTDB-TP, Saline, has been updated to include viscosity estimation capabilities based on the Redlich–Kister formalism; this is an advancement with respect to the existing density estimation capabilities. The graphical user interface was also updated to include a density estimation capability, backed by Saline. Finally, additional preliminary efforts to include surface tension into the database, as well as an investigation on formalisms that would be appropriate for thermal conductivity estimation, are reported herein.

36 MATERIALS SCIENCE↗
DOE OSTI2021

NO x adsorption with CO and C 2 H 4 on Pd/SSZ-13: Experiments and modeling

A transient monolith model containing microkinetic schemes for NO uptake and release over Pd/SSZ-13 without and with reductants CO or C2H4 is presented. The scheme involves three cationic Pd species (Z – [PdOH] + , Z – Pd 2+ Z – , Z – Pd + ) as the active sites during uptake of NO, CO and C 2 H 4 , and their desorption and conversion at higher temperature. Kinetic parameters are estimated through a combination of density functional theory (DFT) estimates and a fit of uptake, desorption and conversion data. The tuned model is validated at different uptake temperatures, ramp rates, and flowrates. A “degree of uptake control” parameter is defined that helps to identify the step(s) that are uptake controlling. The model helps to interpret the data features and is used to identify operating conditions to meet application-relevant performance metrics, including NO trapping efficiency and NO release temperature. Furthermore, the model demonstrates higher NO uptake on Pd/SSZ-13 compared to Pd/ZSM-5.

42 ENGINEERING↗