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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Nanoscale modulation of flat bands via controllable charge density wave defects in 4⁢𝐻⁡𝑏−Ta⁢S 2

Electron correlation is a main driver of exotic quantum phases and their interplay. The 4H b-TaS 2 system, possessing an intrinsic heterostructure of 1T- and 1H -TaS 2 monolayers, offers a unique opportunity to control electron correlation by distorting the atomic lattice or tuning interlayer coupling. Here, we investigated intrinsically deformed charge-density waves (CDWs) in the 1T layer of 4H b-TaS 2 to elucidate and control their effects on flat bands using scanning tunneling microscopy and spectroscopy (STM/S) combined with first-principles calculations. We identified two types of CDW defects: Type 1 has structural distortion and locally suppressed flat bands, while Type 2 features an increased flat band filling factor of intact CDW structure. Density functional theory calculations indicate that a sulfur vacancy in the 1T layer distorts the CDW structure and gives rise to a Type 1, whereas a sulfur vacancy in the 1H layer reduces the interlayer charge transfer and leads to a Type 2. Furthermore, we demonstrated creating and erasing individual CDW defects via STM manipulation. Here, our findings provide a pathway to not only tune flat bands but also selectively manipulate the interaction between CDW, the atomic lattice, and interlayer coupling in strongly correlated systems with atomic precision.

Charge density waves↗
DOE OSTI2019

Mott gapping in 3 d A B O 3 perovskites without Mott-Hubbard interelectronic repulsion energy U

The existence of band gaps in Mott insulators such as perovskite oxides with partially filled 3d shells has been traditionally explained in terms of strong, dynamic interelectronic repulsion codified by the on-site repulsion energy U in the Hubbard Hamiltonian. The success of the “DFT+U approach” where an empirical on-site potential term U is added to the exchange- and correlation density functional theory (DFT) raised questions on whether U in DFT+U represents interelectronic correlation in the same way as it does in the Hubbard Hamiltonian, and if empiricism in selecting U can be avoided. Here we illustrate that ab initio DFT without any U is able to predict gapping trends and structural symmetry breaking (octahedra rotations, Jahn-Teller modes, bond disproportionation) for all 3dABO 3 perovskites from titanates to nickelates in both spin-ordered and spin-disordered paramagnetic phases. Thus, the mechanism of gap formation due to the Hubbard Hamiltonian dynamic interelectronic correlation is not a requirement in these 3d electron compounds. Here, we describe the paramagnetic phases as a supercell where individual sites can have different local environments thereby allowing DFT to develop finite moments on different sites as long as the total cell has zero moment. We use the recently developed strongly constrained appropriately normed exchange and correlation functional (SCAN) that is sanctioned by the usual single-determinant, mean-field DFT paradigm with static correlations, but has a more precise rendering of self-interaction cancelation. Our results suggest that strong dynamic electronic correlations are not playing a universal role in gapping of 3dABO 3 Mott insulators, and opens the way for future applications of DFT for studying a plethora of complexity effects that depend on the existence of gaps, such as doping, defects, and band alignment in ABO 3 oxides.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Causal correlation of foliar biochemical concentrations with AVIRIS spectra using forced entry linear regression

A major goal of airborne imaging spectrometry is to estimate the biochemical composition of vegetation canopies from reflectance spectra. Remotely-sensed estimates of foliar biochemical concentrations of forests would provide valuable indicators of ecosystem function at regional and eventually global scales. Empirical research has shown a relationship exists between the amount of radiation reflected from absorption features and the concentration of given biochemicals in leaves and canopies (Matson et al., 1994, Johnson et al., 1994). A technique commonly used to determine which wavelengths have the strongest correlation with the biochemical of interest is unguided (stepwise) multiple regression. Wavelengths are entered into a multivariate regression equation, in their order of importance, each contributing to the reduction of the variance in the measured biochemical concentration. A significant problem with the use of stepwise regression for determining the correlation between biochemical concentration and spectra is that of 'overfitting' as there are significantly more wavebands than biochemical measurements. This could result in the selection of wavebands which may be more accurately attributable to noise or canopy effects. In addition, there is a real problem of collinearity in that the individual biochemical concentrations may covary. A strong correlation between the reflectance at a given wavelength and the concentration of a biochemical of interest, therefore, may be due to the effect of another biochemical which is closely related. Furthermore, it is not always possible to account for potentially suitable waveband omissions in the stepwise selection procedure. This concern about the suitability of stepwise regression has been identified and acknowledged in a number of recent studies (Wessman et al., 1988, Curran, 1989, Curran et al., 1992, Peterson and Hubbard, 1992, Martine and Aber, 1994, Kupiec, 1994). These studies have pointed to the lack of a physical link between wavelengths chosen by stepwise regression and the biochemical of interest, and this in turn has cast doubts on the use of imaging spectrometry for the estimation of foliar biochemical concentrations at sites distant from the training sites. To investigate this problem, an analysis was conducted on the variation in canopy biochemical concentrations and reflectance spectra using forced entry linear regression.

Dawson, Terence P.↗
NASA NTRS1990

Codeless GPS Applications to Multi-Path: CGAMP

Cordless Global Positioning System (GPS) Applications to Multi-Path (CGAMP) is meeting the challenge of exploiting the L-band signals from the Global Positioning System (GPS) satellites for the measurement of the impulse response of radio transmission channels over space-Earth paths. This approach was originally suggested by E. K. Smith and has been pursued by J. Lemmon, without an affordable implementation being identifiable. In addition to the high cost of a suitable P code correlating GPS receiver, there is also the major impediment of the often announced Department of Defense policy of selective availability/anti-spoof (SA/AS) that clouds reliable access to the wideband (20 MHz) P channel of the GPS signals without cryptographic access. A technique proposed by MacDoran utilizes codeless methods for exploiting the P channel signals implemented by the use of a pair of antennas and cross correlation signal detection.

Macdoran, P. F.↗
DOE OSTI2016

A CIRCULAR-CYLINDRICAL FLUX-ROPE ANALYTICAL MODEL FOR MAGNETIC CLOUDS

We present an analytical model to describe magnetic flux-rope topologies. When these structures are observed embedded in Interplanetary Coronal Mass Ejections (ICMEs) with a depressed proton temperature, they are called Magnetic Clouds (MCs). Our model extends the circular-cylindrical concept of Hidalgo et al. by introducing a general form for the radial dependence of the current density. This generalization provides information on the force distribution inside the flux rope in addition to the usual parameters of MC geometrical information and orientation. The generalized model provides flexibility for implementation in 3D MHD simulations. Here, we evaluate its performance in the reconstruction of MCs in in situ observations. Four Earth-directed ICME events, observed by the Wind spacecraft, are used to validate the technique. The events are selected from the ICME Wind list with the magnetic obstacle boundaries chosen consistently with the magnetic field and plasma in situ observations and with a new parameter (EPP, the Electron Pitch angle distribution Parameter) which quantifies the bidirectionally of the plasma electrons. The goodness of the fit is evaluated with a single correlation parameter to enable comparative analysis of the events. In general, at first glance, the model fits the selected events very well. However, a detailed analysis of events with signatures of significant compression indicates the need to explore geometries other than the circular-cylindrical. An extension of our current modeling framework to account for such non-circular CMEs will be presented in a forthcoming publication.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Capabilities of multivariate Bayesian inference toward seismic hazard assessment

Multivariate Bayesian analysis can bring significant benefits to seismic hazard analysis: Its multivariate feature enables computing scalar and vector hazard without making any approximations; Correlations between intensity measures are implicitly modeled, permitting direct simulation of ground motion selection tools such as the conditional mean spectrum and the generalized conditioning intensity measure; and Its updating feature enables a seamless integration of new ground motion data into the hazard results. Here, we first develop a multivariate Bayesian ground motion model through the NGA-West2 database. The model functional form considers fault-type, magnitude, and distance dependencies, and also the linear and the rock intensity dependent site response. We use a hybrid Markov Chain Monte Carlo sampling to perform Bayesian inference consisting of Gibbs step and a multilevel Metropolis-Hastings step. We then perform several checks on the model and note that its performance is satisfactory. Finally, we illustrate the merits of this multivariate Bayesian analysis, which include: ground motion model updating with ground motion data recorded in the last four years not part of the NGA-West2 database; computation of scalar and vector seismic hazard using the un-updated and updated ground motion models for Los Angeles, CA; and simulation of the conditional mean spectrum under scalar and vector IM conditioning while accounting for different sources of aleatoric and epistemic uncertainties.

58 GEOSCIENCES↗
DOE OSTI2024

A methodology for selection of solid desiccants in energy recovery ventilators

Controlling indoor humidity levels is essential for maintaining acceptable indoor air quality in buildings. The use of energy recovery ventilators (ERVs) is an energy-efficient way to regulate indoor air humidity. Fixed-bed regenerators and rotary wheels are widely used ERVs because of their high sensible and latent effectiveness. These ERVs are made of desiccant-coated substrates, which enable them to transfer moisture between the supply and exhaust air streams. However, the moisture transfer ability of ERVs depends on the physiochemical and sorption properties of desiccants. Extensive, full-scale experiments are required to determine the best desiccant material for these systems. This paper presents a simplified method of selecting suitable desiccant materials for ERVs. The methodology involves important characterization methods, literature correlations for performance prediction, and cost-effective testing methods prior to full-scale testing, and full-scale test methods are discussed in detail. Furthermore, the performance of a few newly derived materials is evaluated and compared with that of conventional desiccants such as silica gel and molecular sieves. The highest latent effectiveness was obtained for composite of super absorbent polymer (SAP) with potassium formate (SAP-HCO2K-50 %), all-polymer porous solid desiccant (APPSD) and metal organic framework (MOF)–MIL–101 (Cr), followed by activated carbon fibre felt (ACFF) Silica sol-LiCl30, SAP, silica gel, MOF–303, and molecular sieve. Researchers and manufacturers would benefit from the proposed methodology and presented data in developing new desiccant materials for ERV applications.

Energy recovery↗
DOE OSTI2026

Tailored Solvent Treatment for Optimized Production of Upcycled Anodes from End-Of-Life Li-Ion Batteries

Recycling processes for lithium-ion batteries typically overlook graphite because of its lower market value relative to that of transition-metal-containing cathode materials. However, graphite recovered from cycled lithium-ion batteries holds additional engineered value associated with the solid-electrolyte interphase (SEI). The SEI contributes critical electronic passivation of the graphite surface but becomes highly resistive with extended cycling, yielding poor cell performance. In this work, we apply tailored solvent treatment to end-of-life (EOL) graphite anodes to selectively remove adverse SEI components while retaining beneficially passivating species. We evaluate a series of polar protic solvents to achieve targeted removal of SEI components and control selectivity through rational variation in solvent properties. The physiochemical properties of treatment solvents correlate with both the retained SEI composition and the corresponding electrochemical performance of solvent-treated “upcycled” graphite anodes. Within the initial set of solvents evaluated, top-performing candidates show capacity and Coulombic efficiency nearly equivalent to those of an analogous pristine anode, as well as promising electrochemical performance enhancement with regard to irreversible capacity-loss metrics. This study establishes critical design principles for an optimized anode upcycling method that enhances the value of recycled graphite by retaining and upgrading the SEI.

25 ENERGY STORAGE↗
DOE OSTI2025

Breakdown of the Static Dielectric Screening Approximation of Coulomb Interactions in Atomically Thin Semiconductors

Coulomb interactions in atomically thin materials are remarkably sensitive to variations in the dielectric screening of the environment, which can be used to control exotic quantum many-body phases and engineer exciton potential landscapes. For decades, static or frequency-independent approximations of the dielectric response, where increased dielectric screening is predicted to cause an energy redshift of the exciton resonance, have been sufficient. These approximations were first applied to quantum wells and were more recently extended with initial success to layered transition metal dichalcogenides (TMDs). Here, we use charge-tunable exciton resonances to investigate screening effects in TMD monolayers embedded in materials with low-frequency dielectric constants ranging from 4 to more than 1000, a range of 2 orders of magnitude larger than in previous studies. In contrast to the redshift predicted by static models, we observe a blueshift of the exciton resonance exceeding 30 meV in higher dielectric constant environments. We explain our observations by introducing a dynamical screening model based on a solution to the Bethe-Salpeter equation (BSE). When dynamical effects are strong, we find that the exciton binding energy remains mostly controlled by the low-frequency dielectric response, while the exciton self-energy is dominated by the high-frequency one. Our results supplant the understanding of screening in layered materials and their heterostructures, introduce a knob to tune selected many-body effects, and reshape the framework for detecting and controlling correlated quantum many-body states and designing optoelectronic and quantum devices.

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

Operando high-pressure investigation of size-controlled CuZn catalysts for the methanol synthesis reaction

Although Cu/ZnO-based catalysts have been long used for the hydrogenation of CO 2 to methanol, open questions still remain regarding the role and the dynamic nature of the active sites formed at the metal-oxide interface. Here, we apply high-pressure operando spectroscopy methods to well-defined Cu and Cu 0.7 Zn 0.3 nanoparticles supported on ZnO/Al2O 3 , γ-Al 2 O 3 and SiO 2 to correlate their structure, composition and catalytic performance. We obtain similar activity and methanol selectivity for Cu/ZnO/Al 2 O 3 and CuZn/SiO 2 , but the methanol yield decreases with time on stream for the latter sample. Operando X-ray absorption spectroscopy data reveal the formation of reduced Zn species coexisting with ZnO on CuZn/SiO 2 . Near-ambient pressure X-ray photoelectron spectroscopy shows Zn surface segregation and the formation of a ZnO-rich shell on CuZn/SiO 2 . In this work we demonstrate the beneficial effect of Zn, even in diluted form, and highlight the influence of the oxide support and the Cu-Zn interface in the reactivity.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Clustering analysis of medium-band selected high-redshift galaxies

Next-generation large-scale structure spectroscopic surveys will probe cosmology at high redshifts (2.3 < z < 3.5), relying on abundant galaxy tracers such as Lyα emitters (LAEs) and Lyman break galaxies (LBGs). Medium-band photometry has emerged as a potential technique for efficiently selecting these high-redshift galaxies. In this work, we present clustering analysis of medium-band selected galaxies at high redshift, utilizing photometric data from the Intermediate Band Imaging Survey (IBIS) and spectroscopic data from the Dark Energy Spectroscopic Instrument (DESI). We interpret the clustering of such samples using both Halo Occupation Distribution (HOD) modeling and a perturbation theory description of large-scale structure. Our modeling indicates that the current target sample is composed from an overlapping mixture of LAEs and LBGs with emission lines. Despite differences in target selection, we find that the clustering properties are consistent with previous studies, with correlation lengths r 0 ≃ 3-4 h -1 Mpc and a linear bias of b ∼ 1.8-2.5. Finally, we discuss the simulation requirements implied by these measurements and demonstrate that the properties of the samples would make them excellent targets to enhance our understanding of the high-z universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Data-driven Feature Analysis in Control Design for Series-Compensated Transmission Systems

One challenge in power-system control designs is the gap between numerical model-based analysis and complex real-world power systems. With increased data and measurements being collected from power systems, data-driven analysis (e.g., machine learning) may provide an alternative approach to reveal hidden information through learning from the real system data, and provide insights for better control scheme design during the utility planning process. Data-driven feature analysis was performed to evaluate the relationships between series compensation, power generation, and path flows in a real transmission system, as well as temporal patterns. The main data-driven analysis methods, including statistical cross-correlation, multinomial logistical regression, and classification and regression trees, were integrated for feature selection and developing predictive models of series compensation. Analysis results demonstrated the effectiveness of the proposed methodology in feature analysis and the potential to help improve power-system control scheme design.

42 ENGINEERING↗
DOE OSTI2019

Ultrasonic Characterization of Spatially Varying Material Properties in Metal Components Fabricated by Additive Manufacturing

We investigated the sensitivity of ultrasonic measurements to changes in the operating conditions during additive fabrication for 316L stainless steel samples by selective laser melting. We found that the velocity of the ultrasound propagation positively correlates with the energy density used to melt layers of metal powder during the fabrication. In the range of the investigated conditions, the faster ultrasonic propagation, observed with the increase in the energy density, was shown to correspond to the improved hardness and the modulus of 316L stainless steel. Overall, our results indicate the feasibility of ultrasonic characterization of heterogeneities in the material properties of metal components produced by additive manufacturing.

Walton, Kenneth↗
DOE OSTI2016

SU-G-BRA-02: Development of a Learning Based Block Matching Algorithm for Ultrasound Tracking in Radiotherapy

Purpose: To develop an ultrasound learning-based tracking algorithm with the potential to provide real-time motion traces of anatomy-based fiducials that may aid in the effective delivery of external beam radiation. Methods: The algorithm was developed in Matlab R2015a and consists of two main stages: reference frame selection, and localized block matching. Immediately following frame acquisition, a normalized cross-correlation (NCC) similarity metric is used to determine a reference frame most similar to the current frame from a series of training set images that were acquired during a pretreatment scan. Segmented features in the reference frame provide the basis for the localized block matching to determine the feature locations in the current frame. The boundary points of the reference frame segmentation are used as the initial locations for the block matching and NCC is used to find the most similar block in the current frame. The best matched block locations in the current frame comprise the updated feature boundary. The algorithm was tested using five features from two sets of ultrasound patient data obtained from MICCAI 2014 CLUST. Due to the lack of a training set associated with the image sequences, the first 200 frames of the image sets were considered a valid training set for preliminary testing, and tracking was performed over the remaining frames. Results: Tracking of the five vessel features resulted in an average tracking error of 1.21 mm relative to predefined annotations. The average analysis rate was 15.7 FPS with analysis for one of the two patients reaching real-time speeds. Computations were performed on an i5-3230M at 2.60 GHz. Conclusion: Preliminary tests show tracking errors comparable with similar algorithms at close to real-time speeds. Extension of the work onto a GPU platform has the potential to achieve real-time performance, making tracking for therapy applications a feasible option. This work is partially funded by NIH grant R01CA190298.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

ACCRUE—An Integral Index for Measuring Experimental Relevance in Support of Neutronic Model Validation

A key challenge for the introduction of any design changes, e.g., advanced fuel concepts, first-of-a-kind nuclear reactor designs, etc., is the cost of the associated experiments, which are required by law to validate the use of computer models for the various stages, starting from conceptual design, to deployment, licensing, operation, and safety. To achieve that, a criterion is needed to decide on whether a given experiment, past or planned, is relevant to the application of interest. This allows the analyst to select the best experiments for the given application leading to the highest measures of confidence for the computer model predictions. The state-of-the-art methods rely on the concept of similarity or representativity, which is a linear Gaussian-based inner-product metric measuring the angle—as weighted by a prior model parameters covariance matrix—between two gradients, one representing the application and the other a single validation experiment. This manuscript emphasizes the concept of experimental relevance which extends the basic similarity index to account for the value accrued from past experiments and the associated experimental uncertainties, both currently missing from the extant similarity methods. Accounting for multiple experiments is key to the overall experimental cost reduction by prescreening for redundant information from multiple equally-relevant experiments as measured by the basic similarity index. Accounting for experimental uncertainties is also important as it allows one to select between two different experimental setups, thus providing for a quantitative basis for sensor selection and optimization. The proposed metric is denoted by ACCRUE, short for Accumulative Correlation Coefficient for Relevance of Uncertainties in Experimental validation. Using a number of criticality experiments for highly enriched fast metal systems and low enriched thermal compound systems with accident tolerant fuel concept, the manuscript will compare the performance of the ACCRUE and basic similarity indices for prioritizing the relevance of a group of experiments to the given application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Genome-Wide Association Study Reveals Complex Genetic Architecture of Cadmium and Mercury Accumulation and Tolerance Traits in Medicago truncatula

Heavy metals are an increasing problem due to contamination from human sources that and can enter the food chain by being taken up by plants. Understanding the genetic basis of accumulation and tolerance in plants is important for reducing the uptake of toxic metals in crops and crop relatives, as well as for removing heavy metals from soils by means of phytoremediation. Following exposure of Medicago truncatula seedlings to cadmium (Cd) and mercury (Hg), we conducted a genome-wide association study using relative root growth (RRG) and leaf accumulation measurements. Cd and Hg accumulation and RRG had heritability ranging 0.44 – 0.72 indicating high genetic diversity for these traits. The Cd and Hg trait associations were broadly distributed throughout the genome, indicated the traits are polygenic and involve several quantitative loci. For all traits, candidate genes included several membrane associated ATP-binding cassette transporters, P-type ATPase transporters, oxidative stress response genes, and stress related UDP-glycosyltransferases. The P-type ATPase transporters and ATP-binding cassette protein-families have roles in vacuole transport of heavy metals, and our findings support their wide use in physiological plant responses to heavy metals and abiotic stresses. We also found associations between Cd RRG with the genes CAX3 and PDR3, two linked adjacent genes, and leaf accumulation of Hg associated with the genes NRAMP6 and CAX9. When plant genotypes with the most extreme phenotypes were compared, we found significant divergence in genomic regions using population genomics methods that contained metal transport and stress response gene ontologies. Several of these genomic regions show high linkage disequilibrium (LD) among candidate genes suggesting they have evolved together. Minor allele frequency (MAF) and effect size of the most significant SNPs was negatively correlated with large effect alleles being most rare. This is consistent with purifying selection against alleles that increase toxicity and abiotic stress. Conversely, the alleles with large affect that had higher frequencies that were associated with the exclusion of Cd and Hg. Overall, macroevolutionary conservation of heavy metal and stress response genes is important for improvement of forage crops by harnessing wild genetic variants in gene banks such as the Medicago HapMap collection.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1975

Dynamic sampling of laser-induced vapor plumes by mass spectrometry

Mass spectrometric techniques and instrumentation for the dynamic sampling of laser-induced vapor clouds during their submillisecond expansion periods are discussed. Illustrations are drawn primarily from the results of pulsed-laser heating of some oxides and graphites; these include comparisons of incident laser beam pulses with the resultant pulses of positive ions and selected neutral species. Observed characteristics of vapor pulses from graphite are shown to correlate with calculated surface temperature response. Dynamic velocity measurements of individual vapor species are described and, from these velocities, vaporization temperatures are derived and compared using four gas dynamic models for vapor expansion into vacuum. Additional measurements indicate that the laser beam may interact directly with the neutral vapors to produce ions.

Lincoln, K. A.↗
NASA NTRS1980

Io control of Jovian radio emission

The possibility of Io controlling Jovian decametric radio emission, particularly in the region below 22 MHz, is discussed. Results of a two-year survey at 26.3 at 26.3 MHz are presented which demonstrate the control of Io over a high-intensity storm component of the radio emission and the independence of a weak radio component from the phase of Io, as was observed at lower frequencies. It is thus hypothesized that Io control is a flux-dependent rather than a frequency-dependent phenomenon, and results of analyses at 18 and 10 MHz which support this hypothesis are presented. The apparent correlation between frequency and Io control is thus shown to result from a selection effect due to the increase of non-Io emission with decreasing frequency and relative antenna detection threshold. This result implies a contiguous Io-controlled source region extending out several Jovian radii along the Io flux tube.

Desch, M. D.↗