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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

High‐Throughput Study of Amorphous Stability and Optical Properties of Superlattice‐Like Ge–Sb–Te Thin Films

A high‐throughput ion beam sputtering system is used to synthesize compositional gradient superlattice‐like (SLL) thin film libraries of Ge–Sb–Te alloys over the entire phase diagram. Here, the optical properties and structural evolution of the Ge–Sb–Te combinatorial SLL thin film are investigated. A systematic screening over the annealing temperature, annealing time, and modulation period has elucidated the critical factors that affect the stability of the metastable phase and optical properties. It is found that amorphous stability and optical constant are highly dependent on the modulation period and chemical composition of the thin film. This data‐driven approach offers new perspectives for accelerating the development of new materials with excellent optical and amorphous stability and for exploring their mechanisms, by greatly expanding the dataset of Ge–Sb–Te alloys with SLL structures through high‐throughput experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Sampling Density in Regional Exploration and Environmental Geochemical Studies: A Review

A variety of factors contribute to the proper and efficient evaluation of geochemical programs including sampling medium, sample size and sample fraction, sampling density, digestion procedure, and analytical techniques. Among the aforementioned factors, sampling density is of great importance, affecting project ability to detect anomalous sites, which are either economically viable or environmentally hazardous. It is quite critical to have a sufficient number of samples to delineate geochemical anomalies or baselines and to reveal the relative variations in elemental concentrations in a study area. The resolution of the subsequent maps obtained by sampling greatly depends on sampling density. While a large number of samples may generate redundant data, a small number of samples smooth out the patterns and may completely miss anomalies. This review provides a platform for applied geochemists who desire to design a sampling scheme for a regional geochemical program and do not have the financial resources to perform an orientation survey, which will give them the necessary information for designing, according to project objectives, a cost-effective regional geochemical survey for their study area. It is advisable to integrate during the desktop study all available information, such as geological, structural, geophysical, remote sensing data and topographical data by using different data fusion algorithms to arrive at a sampling density fit-for-purpose of the target area. This in turn facilitates an effective spatial positioning of sample locations. Quantitative analyses of the efficiency of different sampling densities for delineating geochemical patterns have not been well documented, warranting more attention and research.

58 GEOSCIENCES↗
DOE OSTI2021

Decoupling of particles and dissolved iron downstream of Greenlandic glacier outflows

Glaciers can be a significant and locally dominant source of iron (Fe), a biologically essential micronutrient, in high latitude coastal seas. The vast majority of this glacial Fe delivery is associated with particles, yet the speciation of the solid-phase Fe and specifically the relationships that govern exchange between particulate and dissolved Fe phases in these environments are poorly described. Here, in this work, we performed measurements of in situ dissolved Fe (dFe) along meltwater and particle plumes in three transects around Disko Bay and Ameralik Fjord (West Greenland). Measurements of dFe were combined with Fe K-edge X-ray absorption spectroscopy analysis of ~40 suspended sediment samples obtained from the same transects and from select depth profiles down to 300 m. We observed relatively constant dFe levels (4 to 10 nM for nearly all dFe measurements) across fjords with widely varying particulate Fe(II) contents (from 20 to 90% Fe(II)), indicating that dFe concentrations had little dependence on the oxidation state of Fe in the suspended sediment. Particulate Fe data were grouped by underlying bedrock geology, with suspended sediment consisting of 80-90% biotite-like Fe(II) in fjords with Precambrian shield geology and poorly-ordered Fe(III) particles (<20-30% Fe(II)) in one fjord with suspended sediments derived from tertiary basalts. Our characterization data indicated no significant change in the average Fe oxidation state and bonding environment of particles along the fjord transects, implying that Fe(II) in biotite-like coordination is not a readily labile Fe form on this spatial scale. Finally, our results suggest that dFe in these glacially-modified coastal waters is buffered at a relatively constant low nM concentration due to factors other than particle Fe mineralogy and that glacier-derived Fe phases are relatively inert on this spatial scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Multi-site assessment of the potential of fine resolution red-edge vegetation indices for estimating gross primary production

Gross primary production (GPP) models driven by fine resolution remote sensing data characterize the spatial and temporal heterogeneities in plant photosynthesis, which is largely dependent on biome-specific maximum photosynthetic capacity. The red-edge reflectance, sensitive to leaf chlorophyll content, is a good proxy of maximum photosynthetic capacity. More importantly, studies show that the red-edge reflectance-related chlorophyll content index (CIr) multiplied by the incident photosynthetic active radiation (PAR in ) strongly correlates to GPP estimated at carbon flux towers (GPP flux ). Yet, to the best of our knowledge, there is no systematic study investigating the general relationship between fine spatial resolution CIr and GPP among biomes and the relationship between CIr and maximum photosynthetic capacity in GPP models. To provide an overview on incorporating space-borne CIr into a GPP model, we applied fine resolution Sentinel-2-derived CIr and GPP flux over 57 flux sites representative of 10 biomes. We investigated the relationship between CIr and GPP flux , and the spatio-temporal relationship between CIr and ecosystem maximum photosynthetic capacity indicated by the potential ecosystem light use efficiency (LUE pot ). We also evaluated the relationship between other five vegetation indices (VIs) and GPP flux . Results showed that the CIr multiplied by PARin has a higher agreement (R 2 > 0.5) with GPP than other VIs. A universal relationship exists between the CIr multiplied by PARin and GPP, except for forest biomes. The CIr also strongly (R 2 > 0.5) relates to the LUE pot during the peak of the growing season. The CIr has a low spatial variance (CV = 0.25) among biomes, highlighting that CIr can be a proxy of maximum photosynthetic capacity in GPP models that do not require biome-dependent coefficients. This study provides insight for incorporating CIr into GPP models and better quantifying global terrestrial photosynthesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Improving the prediction of daily reservoir releases over the CONUS using conditioned LSTM

Reservoirs play a vital role in regulating streamflow timing and variability for hydroelectricity, flood control, water supply, irrigation, and recreation. Despite their importance, many reservoirs lack comprehensive operational guidelines, making their management complex due to conflicting operational objectives. Hence traditional policy-based reservoir models often fail to capture real-world conditions accurately and they depend on perfect streamflow predictions, which are not always available. In contrast, data-driven models like Long Short-Term Memory (LSTM) networks offer a robust alternative. This study introduces an approach that integrates reservoir characteristics—such as main use, climate, and maximum capacity—into the LSTM model to enhance reservoir release predictions. Using data from nearly 200 reservoirs in the contiguous United States (CONUS), our conditioned LSTM model (LSTM_cond) was compared with both the vanila LSTM and a traditional policy-based approach. Furthermore, our results show that while both LSTM_cond and LSTM perfoms better than the policy-based approach, LSTM_cond consistently outperforms LSTM for hydroelectric, water supply, irrigation, and recreation reservoirs. The KGE median values for LSTM_cond for out-sample reservoirs are 0.764, 0.565, 0.821, and 0.779, respectively, for the aforementioned reservoir types, which are consistently higher that the corresponding KGE values of 0.737, 0.413, 0.775, and 0.713 of LSTM, demonstrating its advantages in improving generalizability.

CONUS↗
DOE OSTI2021

Acoustic velocities, elasticity, and pressure-induced elastic softening in compressed neodymium

For the first time, the acoustic velocities and elasticity of double hexagonal close-packed neodymium (Nd) were measured at high pressure using ultrasonic interferometry in conjunction with synchrotron X-ray techniques. Here, both the compressional and shear wave velocities increased with an increase in pressure of up to ~5.4 GPa before they exhibited almost constant values upon further compression. This pressure-induced elastic wave velocity softening can be attributed to the structural instability in dhcp-Nd. From the current sound velocities and density data, we obtained new bulk and shear moduli as well as their pressure dependence for polycrystalline dhcp-Nd, yielding $B_0$=33.2(9) GPa, $G_0$=14.1(5) GPa, $\partial$$B/$$\partial$$P$ = 3.6 (4) and $\partial$$=G/$$\partial$$P$ = 1.3 (2) while other elasticity-related/mechanical properties, including Young's modulus, Debye temperature, Poisson's ratio, and Grüneisen parameter, which are important parameters for the application of Nd in extreme environments, were also derived.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Characterization of lift force and torque in prolate ellipsoid suspensions

The paper derives correlations for lift force and fluid torques acting on stationary prolate ellipsoid suspensions of aspect ratio (AR) 2.5, 5, and 10 subjected to uniform flow. Here, Particle Resolved Simulations (PRS) are conducted on a suspension of infinite extent in two directions for Reynolds number 10≤Re≤200 and solid fractions (φ) between 0.1≤φ≤0.3.The suspension-mean lift-to-drag ratio varies between 7% to 14% at Re=10 which increases to 14%~22% at Re=200. The torque-induced tip rotational acceleration can reach 38%~85% of drag-induced translational acceleration at Re=200. Single particle lift force and torque correlations of (Fröhlich et al., 2020) are modified and adapted to predict current angular-mean lift and torque data. The resulting lift correlation captures the PRS data within an average deviation below 7%. Torque exhibits a somewhat more complex dependency at AR=10 than the assumed sinθ ∙ cosθ variation but nevertheless the correlations predict angular-mean values with mean relative deviations of 16.6% at AR=10.

42 ENGINEERING↗
DOE OSTI2022

Microbe-iron interactions control lignin decomposition in soil

Lignin decomposition is critically linked to terrestrial carbon (C) cycle due to the enormous C mass of lignin and its importance in controlling overall rates of litter decomposition. Interactions between lignin and iron (Fe) minerals have been increasingly recognized as key mediators of lignin decomposition in experimental studies. However, we still lack a quantitative understanding of how Fe minerals interact with microbes to control lignin decomposition. Here, we leveraged experimental results from an incubation of Fe-rich soil, in which lignin decomposition rates were measured at aerobic conditions after four levels of pre-treated O2 availability, to examine microbe-Fe (MiFe) interactions in lignin decomposition with a MiFe model. We quantified how Fe redox cycling interacted with microbial activities to control lignin decomposition via data-model integration. Our results showed that the MiFe model with time-dependent growth and mortality functions better represented CO2 release from lignin decomposition (R2 ranging from 0.96 to 0.97) than models assuming either first-order or Michaelis-Menten kinetics. Reduction of Fe(III) to Fe(II) after pre-treatments with lower O2 availability stimu-lated the Fenton reaction to break down macro-molecular lignin into small molecules available to microbes. The small molecules of lignin and necromass bounded with oxidized Fe and were protected from decomposition. After 1-year incubation, the model implied that most of C stabilized with Fe minerals was derived from small molecular lignin C. Our quantitative analysis of microbe-Fe interactions sheds new light on lignin decomposition and preservation and helps improve model prediction of soil C persistence under global change.

Liao, Cuijuan↗
DOE OSTI2023

Environmental Co‐Benefits of Maintaining Native Vegetation With Solar Photovoltaic Infrastructure

Abstract Co‐locating solar photovoltaics with vegetation could provide a sustainable solution to meeting growing food and energy demands. However, studies quantifying multiple co‐benefits resulting from maintaining vegetation at utility‐scale solar power plants are limited. We monitored the microclimate, soil moisture, panel temperature, electricity generation and soil properties at a utility‐scale solar facility in a continental climate with different site management practices. The compounding effect of photovoltaic arrays and vegetation may homogenize soil moisture distribution and provide greater soil temperature buffer against extreme temperatures. The vegetated solar areas had significantly higher soil moisture, carbon, and other nutrients compared to bare solar areas. Agrivoltaics in agricultural areas with carbon debt can be an effective climate mitigation strategy along with revitalizing agricultural soils, generating income streams from fallow land, and providing pollinator habitats. However, the benefits of vegetation cooling effects on electricity generation are rather site‐specific and depend on the background climate and soil properties. Overall, our findings provide foundational data for site preservation along with targeting site‐specific co‐benefits, and for developing climate resilient and resource conserving agrivoltaic systems.

14 SOLAR ENERGY↗
DOE OSTI2024

Establishing coherent momentum-space electronic states in locally ordered materials

Rich momentum-dependent electronic structure naturally arises in solids with long-range crystalline symmetry. Reliable and scalable quantum technologies rely on materials that are either not perfect crystals or non-crystalline, breaking translational symmetry. This poses the fundamental questions of whether coherent momentum-dependent electronic states can arise without long-range order, and how they can be characterized. Here we investigate Bi 2 Se 3 , which exists in crystalline, nanocrystalline, and amorphous forms, allowing direct comparisons between varying degrees of spatial ordering. Through angle-resolved photoemission spectroscopy, we show for the first time momentum-dependent band structure with Fermi surface repetitions in an amorphous solid. The experimental data is complemented by a model that accurately reproduces the vertical, dispersive features as well as the replication at higher momenta in the amorphous form. These results reveal that well-defined real-space length scales are sufficient to produce dispersive band structures, and that photoemission can expose the imprint of these length scales on the electronic structure.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Ab initio quantum scattering calculations and a new potential energy surface for the HCl( X 1Σ+)–O2(X3Σg−) system: Collision-induced line shape parameters for O2-perturbed R(0) 0–0 line in H35Cl

The remote sensing of abundance and properties of HCl—the main atmospheric reservoir of Cl atoms that directly participate in ozone depletion—is important for monitoring the partitioning of chlorine between “ozone-depleting” and “reservoir” species. Such remote studies require knowledge of the shapes of molecular resonances of HCl, which are perturbed by collisions with the molecules of the surrounding air. In this work, we report the first fully quantum calculations of collisional perturbations of the shape of a pure rotational line in H35Cl perturbed by an air-relevant molecule [as the first model system we choose the R(0) line in HCl perturbed by O2]. The calculations are performed on our new highly accurate HCl(X1Σ+)–O2(X3Σg−) potential energy surface. In addition to pressure broadening and shift, we also determine their speed dependencies and the complex Dicke parameter. This gives important input to the community discussion on the physical meaning of the complex Dicke parameter and its relevance for atmospheric spectra (previously, the complex Dicke parameter for such systems was mainly determined from phenomenological fits to experimental spectra and the physical meaning of its value in that context is questionable). We also calculate the temperature dependence of the line shape parameters and obtain agreement with the available experimental data. We estimate the total combined uncertainties of our calculations at 2% relative root-mean-square error in the simulated line shape at 296 K. This result constitutes an important step toward computational population of spectroscopic databases with accurate ab initio line shape parameters for molecular systems of terrestrial atmospheric importance.

Chemistry↗
DOE OSTI2023

Relating galaxies across different redshift to study galaxy evolution

We propose a general framework leveraging the galaxy–halo connection to link galaxies observed at different redshift in a statistical way, and use the link to infer the redshift evolution of the galaxy population. Our tests based on hydrodynamic simulations show that our method can accurately recover the stellar mass assembly histories up to z ∼ 3 for present star-forming and quiescent galaxies down to 10 10 h −1 M ⊙ . Applying the method to observational data shows that the stellar mass evolution of the main progenitors of galaxies depends strongly on the properties of descendants, such as stellar mass, halo mass, and star formation states. Galaxies hosted by low-mass groups/haloes at the present time have since z ∼ 1.8 grown their stellar mass ∼2.5 times as fast as those hosted by massive clusters. This dependence on host halo mass becomes much weaker for descendant galaxies with similar star formation states. Star-forming galaxies grow about 2–4 times faster than their quiescent counterparts since z ∼ 1.8. Both TNG and EAGLE simulations overpredict the progenitor stellar mass at z > 1, particularly for low-mass descendants.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Determining the Hubble constant through cross-correlation of galaxies and gravitational waves

Gravitational-wave (GW) standard sirens have the potential to measure the Hubble constant 𝐻 0 in the local Universe independent of the distance ladder and thus offer unique insights into the Hubble tension. A key challenge with standard sirens is detecting their electromagnetic counterparts and therefore assigning redshifts to the measured distances. One promising way to proceed is to utilize GW dark sirens—events without an identified electromagnetic counterpart—and cross-correlate their angular distribution with that of galaxies. We present a quantitative study of how precisely the Hubble constant can be measured using tomographic cross-correlation between galaxies and GW sources. Altogether, we find that the constraints on 𝐻 0 will be limited by the quality and quantity of GW data. We find that percent-level constraints on 𝐻 0 will primarily depend on achieving small distance uncertainties (𝜎 𝑑𝐿 = 0.1⁢𝑑 𝐿 ), obtaining a large number of GW dark sirens (≳ 5⁢000) and accurate sky localization in the tomographic analysis.

Cosmological parameters↗
DOE OSTI2025

Semi-inclusive direct photon + jet and 𝜋 0 + jet correlations measured in 𝑝 + 𝑝 and central Au + Au collisions at $\sqrt{s_{NN}}$ = 200GeV

The STAR experiment at RHIC reports new measurements of jet quenching based on the semi- inclusive distribution of charged-particle jets recoiling from direct photon (γ dir ) and neutral pion (π 0 ) triggers in pp and central Au + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV, for triggers in the range 9 < $E$$^{trig}_{T}$ < 20 GeV. The datasets have integrated luminosities of 3.9nb −1 for Au + Au and 23pb −1 for 𝑝𝑝 collisions. Jets are reconstructed using the anti-𝑘 𝑇 algorithm with resolution parameters 𝑅 = 0.2 and 0.5. The large uncorrelated jet background in central Au + Au collisions is corrected using a mixed-event approach, which enables precise charged-particle jet measurements at low transverse momentum 𝑝$^{ch}_{𝑇,jet}$ and large 𝑅. Recoil-jet distributions are reported in the range 𝑝$^{ch}_{𝑇,jet}$ < 25 GeV/𝑐. Comparison of the distributions measured in 𝑝𝑝 and Au + Au collisions reveals strong medium-induced jet yield suppression for 𝑅 = 0.2 with markedly less suppression for 𝑅 = 0.5. Comparison is also made to theoretical models incorporating jet quenching. Furthermore, these data provide new insight into the mechanisms underlying jet quenching and the angular dependence of medium-induced jet-energy transport and provide new constraints on modeling such effects.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Er Al :Al 2 ⁢O 3 for telecom-band photonics: Electronic structure and optical properties

Er-doped Al 2 ⁢O 3 is a promising host for telecom-band integrated photonics. Here, in this study, we combine ab initio calculations with a symmetry-resolved analysis to elucidate substitutional Er on the Al site (Er Al ) in 𝛼−Al 2 ⁢O 3 . First-principles relaxations confirm the structural stability of Er Al . We then use the local trigonal crystal-field symmetry to classify the Er-derived impurity levels by irreducible representations and to derive polarization-resolved electric-dipole selection rules, explicitly identifying the symmetry-allowed 𝑓−𝑑 hybridization channels. Kubo-Greenwood absorption spectra computed from Kohn-Sham states quantitatively corroborate these symmetry predictions. Furthermore, we connect the calculated intra-4⁢𝑓 line strengths to Judd-Ofelt theory, clarifying the role of 4⁢𝑓−5⁢𝑑 admixture in enabling optical activity. Notably, we predict a characteristic absorption near 1.47 µ⁢m (telecom band), relevant for on-chip amplification and emission. To our knowledge, a symmetry-resolved first-principles treatment of Er:Al 2 ⁢O 3 with an explicit Judd-Ofelt interpretation has not been reported, providing a transferable framework for tailoring rare-earth dopants in wide-band-gap oxides for integrated photonics. Our results for the optical spectra are in good agreement with experimental data. The resulting symmetry-based selection rules translate directly to polarization-dependent coupling in Al 2 ⁢O 3 integrated photonic waveguides and resonators, enabling device-level design of TE/TM-mode interaction with Er emitters in the 1.5-µ⁢m telecom band.

Er-doped Al2O3↗
DOE OSTI2021

Discriminating Quantum States with Quantum Machine Learning

Quantum machine learning (QML) algorithms have obtained great relevance in the machine learning (ML) field due to the promise of quantum speedups when performing basic linear algebra subroutines (BLAS), a fundamental element in most ML algorithms. By making use of BLAS operations, we propose, implement and analyze a quantum k-means (qk-means) algorithm with a low time complexity of O(NKlog(D)I/C) to apply it to the fundamental problem of discriminating quantum states at readout. Discriminating quantum states allows the identification of quantum states |0⟩ and |1⟩ from low-level in-phase and quadrature signal (IQ) data, and can be done using custom ML models. In order to reduce dependency on a classical computer, we use the qk-means to perform state discrimination on the IBMQ Bogota device and managed to find assignment fidelities of up to 98.7% that were only marginally lower than that of the k-means algorithm. We also performed a cross-talk benchmark on the quantum device by applying both algorithms to perform state discrimination on a combination of quantum states and using Pearson Correlation coefficients and assignment fidelities of discrimination results to conclude on the presence of cross-talk on qubits. Evidence shows cross-talk in the (1, 2) and (2, 3) neighboring qubit couples for the analyzed device.

Quiroga, David↗
DOE OSTI2024

Rapid Monitoring and Defense Approach for Resilience Improvement of Grid Cyber Security

Cyber-physical systems and electric utilities significantly depend on the reliability and efficiency of information and operational technology. However, false data injection attacks based on synchrophasor measurement data pose a serious threat to the safe and reliable operation of modern power systems. Here, to mitigate this problem, a rapid monitoring and defense approach is proposed to defend against cyber attacks. Initially, the Time and Frequency based Convolutional neural Network (TFCN) is proposed to detect different types of attacks. Within the TFCN, the advances are that both time and frequency domain information can be fused without extra spectrum analysis methods, and can save detection time to speed the calculation efficiency using the developed time-frequency block. Next, a comprehensive defense strategy is developed for multiple cyber attacks to ensure the stability and resilience of the power system according to the feedback detection results. The advances of this strategy are that different control strategies can be automatically selected to recover the stability to the greatest extent according to the detected attacks. To verify the effectiveness of the proposed approach, the high-speed frequency measurements collected from the wide-area monitoring system are used. The results demonstrate that the cyber attack detection performance can reach 95.57% accuracy, outperforming both traditional and some advanced neural networks. Importantly, the defense strategy is conducted and verified in a modified IEEE 39 bus system as well, which illustrates profound performance in faster stability restoration.

Comprehensive defense strategy↗
DOE OSTI2022

CovS inactivation reduces CovR promoter binding at diverse virulence factor encoding genes in group A Streptococcus

The control of virulence gene regulator (CovR), also called caspsule synthesis regulator (CsrR), is critical to how the major human pathogen group A Streptococcus fine-tunes virulence factor production. CovR phosphorylation (CovR~P) levels are determined by its cognate sensor kinase CovS, and functional abrogating mutations in CovS can occur in invasive GAS isolates leading to hypervirulence. Presently, the mechanism of CovR-DNA binding specificity is unclear, and the impact of CovS inactivation on global CovR binding has not been assessed. Thus, we performed CovR chromatin immunoprecipitation sequencing (ChIP-seq) analysis in the emm1 strain MGAS2221 and its CovS kinase deficient derivative strain 2221-CovS-E281A. We identified that CovR bound in the promoter regions of nearly all virulence factor encoding genes in the CovR regulon. Additionally, direct CovR binding was observed for numerous genes encoding proteins involved in amino acid metabolism, but we found limited direct CovR binding to genes encoding other transcriptional regulators. The consensus sequence AATRANAAAARVABTAAA was present in the promoters of genes directly regulated by CovR, and mutations of highly conserved positions within this motif relieved CovR repression of the hasA and MGAS2221_0187 promoters. Analysis of strain 2221-CovS-E281A revealed that binding of CovR at repressed, but not activated, promoters is highly dependent on CovR~P state. CovR repressed virulence factor encoding genes could be grouped dependent on how CovR~P dependent variation in DNA binding correlated with gene transcript levels. Taken together, the data show that CovR repression of virulence factor encoding genes is primarily direct in nature, involves binding to a newly-identified DNA binding motif, and is relieved by CovS inactivation. These data provide new mechanistic insights into one of the most important bacterial virulence regulators and allow for subsequent focused investigations into how CovR-DNA interaction at directly controlled promoters impacts GAS pathogenesis.

59 BASIC BIOLOGICAL SCIENCES↗