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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Thermodynamics of the Metal Carbonates and Bicarbonates of Mn, Co, Ni, Cu, and Zn Relevant to Mineral Energetics

The gas phase heats of formation of ground-state MCO 3 , M(HCO 3 ) 2 , and M(HCO 3 )(OH), where M = Mn, Co, Ni, Cu, and Zn, have been predicted using the correlated molecular orbital theory at the CCSD(T) level extrapolated to the complete basis set limit using the Feller–Peterson–Dixon (FPD) approach. Cohesive energies of the carbonates were predicted based on the calculated gas phase and experimental solid heats of formation. Coulombic dissociation energies (CDEs) between metal cations and anions show a near-linear correlation with Shannon metal cation atomic radii, yet no correlation is found with the hardness of these cations. The total reaction dissociation energies (TRDEs) of transition metals are higher than their CDEs for the di-bicarbonates, in contrast to those for Mg and Ca based on our prior work. In addition to differences in the energies needed to prepare the transition metal dications, electron donation from the ligands to the 3d orbitals of open-shell transition metal dications from lone pairs of adjacent O atoms also plays a role. No electron donation from the ligands to the fully occupied 3d orbitals of Zn and Cd was found. Decomposition energies for generating MO, CO 2 , and/or H 2 O were calculated. Gas phase metal exchange energies only partially correlate with the electrochemical series for M(s) → M 2+( aq). The FPD heats of formation were used to benchmark a range of density functional theory exchange–correlation functionals, including those commonly used in solid-state mineral calculations. None of the functionals provided chemical accuracy agreement (±1 kcal/mol) with the FPD results. So, the best agreement with the FPD results is predicted for the $\tau$-HCTH functional with an average unsigned error of 8.3 kcal/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Evaluating ecosystem water use efficiency under drought stress: a case study of the Helan Mountain region, northwest China

Context Water use efficiency (WUE) is a fundamental ecological indicator links carbon assimilation and water loss in terrestrial ecosystems. Understanding its responses to drought stress is essential for adaptive ecosystem management, particularly in climate-sensitive mountain landscapes. Objectives This study aimed to investigate drought-driven variations in WUE across major vegetation types in the Helan Mountain region of Northwest China. Specifically, we sought to identify dominant ecological drivers of WUE variability and to disentangle their relative importance and causal pathways. Methods We quantified WUE using the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Drought Severity Index (DSI) data from 2001 to 2020. To examine WUE – drought relationships across contrasting vegetation types, we employed a spatially explicit analytical framework integrating Random Forest (RF) modeling, partial correlation analysis, and structural equation modeling (SEM). Results Regional WUE exhibited relatively stable interannual dynamics, yet pronounced spatial heterogeneity that was strongly modulated by drought conditions. Vegetation properties, particularly Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI), emerged as the dominant determinants of WUE, with NDVI alone explaining over 20% of its spatial variance in forest and grassland during non-drought periods. SEM analyses revealed that climate forcing influenced WUE mainly through indirect pathways mediated by soil moisture availability and vegetation structural dynamics, rather than through direct climatic controls. Among all regulating factors, LAI acted as the central control node governing ecosystem carbon–water coupling. In contrast, short-term climatic stress, especially atmospheric demand and drought duration, exerted weak or negative direct effects on WUE. Ecosystem-specific responses were observed, with croplands mainly regulated by soil water availability, whereas forests and grasslands showed more sensitive to atmospheric drought stress. Together, these results reveal a hierarchical control framework where soil–vegetation interactions mediate climate impacts on WUE, driving strong spatial heterogeneity in drought responses across mountain landscapes. Conclusions Our findings highlight the pivotal role of indirect drought effects mediated by vegetation and soil processes in shaping ecosystem WUE. The identified soil–vegetation–climate regulatory hierarchy provides mechanistic insight into landscape–scale drought sensitivity and supports integrated modeling approaches for evaluating ecosystem resilience and sustainable management in arid mountain regions.

China↗
DOE OSTI2024

Macroscopic Traffic Modeling Using Probe Vehicle Data: A Machine Learning Approach

Abstract The macroscopic fundamental diagram (MFD) captures an orderly relationship among traffic flow, density, and speed at the network level. It is a simple yet powerful tool for modeling traffic dynamics in large urban networks with broad application in traffic control and management. However, empirically derived MFDs in urban regions require high-resolution traffic data from the network. Having the network flow and vehicular density estimated at the (granular) census tract level using vehicle probe data, we apply machine learning methods to predict the MFDs across U.S. urban areas and capture the impacts of location-specific input features on the network flow–density relationships at a large scale. The results show that, among the four tested machine learning approaches (Random Forest, XGBoost, Support Vector Machine, and Neural Network), XGBoost delivers the best performance in predicting network traffic flow based on vehicular density and location attributes. Using interaction Shapley Additive explanation (SHAP) values and partial correlation analysis, we examine the factors influencing MFD shapes across different locations. Our empirical findings reveal that across U.S. urban areas, network topology, transportation infrastructure, and land use are primary factors shaping MFD curves, while demand and trip-related factors play a lesser role. Specifically, higher ranking roads, centrality, and development levels correlate positively with network capacity and critical density, whereas negative associations are observed for network connectivity, mixed-use development, and road roughness levels.

Jin, Ling↗
DOE OSTI2021

Relative effect of anthropogenic warming and natural climate variability to changes in Compound drought and heatwaves

Compound drought and heatwave (CDHW) events can be influenced by large scale teleconnections and anthropogenic warming, leading to severe socio-economic impacts across various climate regions. Here, the relative influence of six different teleconnection patterns and anthropogenic global warming on the global CDHW occurrences is quantified systematically using the instrumental data period, 1982–2016. The results from the study suggest a substantial increase in the CDHW events (1–5 events per year) across various parts of the globe at the beginning of 21st century (2000–2016). A Bayesian approach is implemented to identify the most vulnerable climate regions based on the degree of susceptibility of heatwaves (DSHW) towards drought. As such, top ten most vulnerable regions are selected based on the DSHW magnitude, and a partial correlation analysis is performed to select the natural and anthropogenic drivers of CDHW in those regions, separately. A logistic regression model is then used to determine significant changes in the odds of CDHW due to changes in the selected drivers that suggest a significantly positive, and multiplicative effect of anthropogenic global warming in the top ten most vulnerable climate regions. Finally, the same logistic regression model, integrated with an analytical framework, is applied to determine the relative influence of anthropogenic global warming on the changes in odds of CDHW for the future, 1.5 °C and 2 °C warming limits. Finally, the results suggest that relative to the 2 °C global warming, constraining to the 1.5 °C global warming limit may conduce about 17-fold reduction in the odds of CDHW in the most vulnerable climate region, East Asia, 5–8-fold reduction in Western North America, Northern Australia, Central North America, Central Europe, South Asia, and the Mediterranean region, and 3–4-fold reduction in Northeastern Brazil, Eastern North America, and West Asia.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Zinc speciation and desorption kinetics in a mining waste impacted tropical soil amended with phosphate

Mining is an important component of the Brazilian economy. However, it may also contribute to environmental problems such as the pollution of soils with zinc and other potentially toxic metals. Our objective was to evaluate changes in the chemical speciation and mobility of Zn in a soil amended with phosphate. Soil samples were collected from a deactivated mining area in the state of Minas Gerais, Brazil, and amended with NH 4 H 2 PO 4 saturated with deionized water to 70 % of maximum water retention and incubated at 25 ± 2 °C in open containers for 60 days. The soil was chemically and mineralogically characterized, and sequential extraction, desorption kinetics, and speciation were carried out using synchrotron bulk-sample and micro–X-ray Absorption Near-Edge Structure (XANES/μ-XANES) spectroscopy at the Zn K-edge, and X-ray fluorescence microprobe analysis (μ-XRF). The combination of μ-XRF and μ-XANES techniques made it possible to identify Zn hotspots in the main species formed after phosphate remediation. The best fit combination for bulk XANES and μ-XANES was observed in Zn-montmorillonite, Zn-kerolite, Zn-ferrihydrite, and gahnite. In the course of phosphate treatment, gahnite, Zn layered double hydroxides (Zn-LDH), Zn3(PO4), and ZnO were identified by bulk XANES, while Zn-ferrihydrite, Zn-montmorillonite, and scholzite were identified by μ-XANES. Zinc in the phosphate-amended soil had the strongest partial correlations (r' > 0.05) with Ni, Co, Fe, Cr, Mn, Si, P, Cd, Pb, and Cd, while the unamended soil showed the strongest correlation with Cu, Pb, Fe, and Si. The application of NH 4 H 2 PO 4 altered Zn speciation and favored an increase in Zn desorption. Here, the most available Zn contents after phosphate amendment were correlated with the release of exchangeable Zn fractions, associated with carbonate and organic matter.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Deconstructing criterion a of the alternative model for personality disorders.

Here, the construct composition of the Level of Personality Functioning Scale (LPFS; Criterion A) of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition alternative model for personality disorders (American Psychiatric Association, 2013) was examined in a clinical vignette rating study. Multiple indices of level of personality functioning, psychiatric and psychosocial impairment, Criterion B maladaptive personality traits, and conceptually divergent variables (intellectual level, socioeconomic status, and likability) were used to deconstruct the LPFS. Most variables were highly intercorrelated, but partial correlational analyses showed the LPFS possesses meaningful personality construct variance not fully explained by severity of pathological traits, psychiatric and psychosocial impairment, or the conceptually divergent variables. This exploratory study offers initial evidence that the LPFS contains substantive LPF variance beyond PD severity. Results are framed and discussed in terms of the known conceptual and empirical overlap between Criterion A and Criterion B as well as the differing ways a dimension of personality disorder (PD) severity may be interpreted. Finally, we propose the LPFS is more than statistical artifact created by empirical covariation but less than a true latent dimension of PD severity. The LPFS may be understood as a methodologically pragmatic but theoretically substantive dimension of PD severity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Homologous mutations in human β, embryonic, and perinatal muscle myosins have divergent effects on molecular power generation

Mutations at a highly conserved homologous residue in three closely related muscle myosins cause three distinct diseases involving muscle defects: R671C in β-cardiac myosin causes hypertrophic cardiomyopathy, R672C and R672H in embryonic skeletal myosin cause Freeman–Sheldon syndrome, and R674Q in perinatal skeletal myosin causes trismus-pseudocamptodactyly syndrome. It is not known whether their effects at the molecular level are similar to one another or correlate with disease phenotype and severity. To this end, we investigated the effects of the homologous mutations on key factors of molecular power production using recombinantly expressed human β, embryonic, and perinatal myosin subfragment-1. We found large effects in the developmental myosins but minimal effects in β myosin, and magnitude of changes correlated partially with clinical severity. The mutations in the developmental myosins dramatically decreased the step size and load-sensitive actin-detachment rate of single molecules measured by optical tweezers, in addition to decreasing overall enzymatic (ATPase) cycle rate. In contrast, the only measured effect of R671C in β myosin was a larger step size. Our measurements of step size and bound times predicted velocities consistent with those measured in an in vitro motility assay. Finally, molecular dynamics simulations predicted that the arginine to cysteine mutation in embryonic, but not β, myosin may reduce pre-powerstroke lever arm priming and ADP pocket opening, providing a possible structural mechanism consistent with the experimental observations. This paper presents direct comparisons of homologous mutations in several different myosin isoforms, whose divergent functional effects are a testament to myosin’s highly allosteric nature.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A physiological signal derived from sun-induced chlorophyll fluorescence quantifies crop physiological response to environmental stresses in the U.S. Corn Belt

Sun-induced chlorophyll fluorescence (SIF) measurements have shown unique potential for quantifying plant physiological stress. However, recent investigations found canopy structure and radiation largely control SIF, and physiological relevance of SIF remains yet to be fully understood. This study aims to evaluate whether the SIF-derived physiological signal improves quantification of crop responses to environmental stresses, by analyzing data at three different spatial scales within the U.S. Corn Belt, i.e. experiment plot, field, and regional scales, where ground-based portable, stationary and space-borne hyperspectral sensing systems are used, respectively. We found that, when controlling for variations in incoming radiation and canopy structure, crop SIF signals can be decomposed into non-physiological (i.e. canopy structure and radiation, 60% ~ 82%) and physiological information (i.e. physiological SIF yield, Φ F , 17% ~ 31%), which confirms the contribution of physiological variation to SIF. We further evaluated whether Φ F indicated plant responses under high-temperature and high vapor pressure deficit (VPD) stresses. The plot-scale data showed that Φ F responded to the proxy for physiological stress (partial correlation coefficient, r p = 0.40, p < 0.001) while non-physiological signals of SIF did not respond ( p > 0.1). The field-scale Φ F data showed water deficit stress from the comparison between irrigated and rainfed fields, and Φ F was positively correlated with canopy-scale stomatal conductance, a reliable indicator of plant physiological condition (correlation coefficient r = 0.60 and 0.56 for an irrigated and rainfed sites, respectively). The regional-scale data showed Φ F was more strongly correlated spatially with air temperature and VPD ( r = 0.23 and 0.39) than SIF ( r = 0.11 and 0.34) for the U.S. Corn Belt. The lines of evidence suggested that Φ F reflects crop physiological responses to environmental stresses with greater sensitivity to stress factors than SIF, and the stress quantification capability of Φ F is spatially scalable. Utilizing Φ F for physiological investigations will contribute to improve our understanding of vegetation responses to high-temperature and high-VPD stresses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The ALMaQUEST survey IX: the nature of the resolved star forming main sequence

ABSTRACT We investigate the nature of the scaling relations between the surface density of star formation rate (ΣSFR), stellar mass (Σ*), and molecular gas mass ($\Sigma _{\rm H_2}$), aiming at distinguishing between the relations that are primary, i.e. more fundamental, and those which are instead an indirect by-product of the other relations. We use the ALMA-MaNGA QUEnching and STar formation survey and analyse the data by using both partial correlations and random forest regression techniques. We unambiguously find that the strongest intrinsic correlation is between ΣSFR and $\Sigma _{\rm H_2}$ (i.e. the resolved Schmidt–Kennicutt relation), followed by the correlation between $\Sigma _{\rm H_2}$ and Σ* (resolved molecular gas main sequence, rMGMS). Once these two correlations are taken into account, we find that there is no evidence for any intrinsic correlation between ΣSFR and Σ*, implying that star formation rate (SFR) is entirely driven by the amount of molecular gas, while its dependence on stellar mass (i.e. the resolved star forming main sequence, rSFMS) simply emerges as a consequence of the relationship between molecular gas and stellar mass.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

On the quenching of star formation in observed and simulated central galaxies: evidence for the role of integrated AGN feedback

ABSTRACT In this paper, we investigate how massive central galaxies cease their star formation by comparing theoretical predictions from cosmological simulations: EAGLE, Illustris, and IllustrisTNG with observations of the local Universe from the Sloan Digital Sky Survey (SDSS). Our machine learning (ML) classification reveals supermassive black hole mass (MBH) as the most predictive parameter in determining whether a galaxy is star forming or quenched at redshift z = 0 in all three simulations. This predicted consequence of active galactic nucleus (AGN) quenching is reflected in the observations, where it is true for a range of indirect estimates of MBH via proxies as well as its dynamical measurements. Our partial correlation analysis shows that other galactic parameters lose their strong association with quiescence, once their correlations with MBH are accounted for. In simulations, we demonstrate that it is the integrated power output of the AGN, rather than its instantaneous activity, which causes galaxies to quench. Finally, we analyse the change in molecular gas content of galaxies from star-forming to passive populations. We find that both gas fractions (fgas) and star formation efficiencies (SFEs) decrease upon transition to quiescence in the observations but SFE is more predictive than fgas in the ML passive/star-forming classification. These trends in the SDSS are most closely recovered in IllustrisTNG and are in direct contrast with the predictions made by Illustris. We conclude that a viable AGN feedback prescription can be achieved by a combination of preventative feedback and turbulence injection which together quench star formation in central galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

What drives galaxy quenching? A deep connection between galaxy kinematics and quenching in the local Universe

ABSTRACT We develop a 2D inclined rotating disc model, which we apply to the stellar velocity maps of 1862 galaxies taken from the MaNGA survey (SDSS public Data Release 15) . We use a random forest classifier to identify the kinematic parameters that are most connected to galaxy quenching. We find that kinematic parameters that relate predominantly to the disc (such as the mean rotational velocity) and parameters that characterize whether a galaxy is rotation- or dispersion-dominated (such as the ratio of rotational velocity to velocity dispersion) are not fundamentally linked to the quenching of star formation. Instead, we find overwhelmingly that it is the absolute level of velocity dispersion (a property that relates primarily to a galaxy’s bulge/spheroidal component) that is most important for separating star-forming and quenched galaxies. Furthermore, a partial correlation analysis shows that many commonly discussed correlations between galaxy properties and quenching are spurious, and that the fundamental correlation is between quenching and velocity dispersion. In particular, we find that at fixed velocity dispersion, there is only a very weak dependence of quenching on the disc properties, whereby more discy galaxies are slightly more likely to be forming stars. By invoking the tight relationship between black hole mass and velocity dispersion, and noting that black hole mass traces the total energy released by active galactic nuclei (AGNs), we argue that these data support a scenario in which quenching occurs by preventive feedback from AGNs. The kinematic measurements from this work are publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The metallicity’s fundamental dependence on both local and global galactic quantities

ABSTRACT We study the scaling relations between gas-phase metallicity, stellar mass surface density (Σ*), star formation rate surface density (ΣSFR), and molecular gas surface density ($\Sigma _{{\rm H}_2}$) in local star-forming galaxies on scales of a kpc. We employ optical integral field spectroscopy from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, and ALMA data for a subset of MaNGA galaxies. We use partial correlation coefficients and Random Forest regression to determine the relative importance of local and global galactic properties in setting the gas-phase metallicity. We find that the local metallicity depends primarily on Σ* (the resolved mass–metallicity relation, rMZR), and has a secondary anticorrelation with ΣSFR (i.e. a spatially resolved version of the ‘Fundamental Metallicity Relation’, rFMR). We find that $\Sigma _{{\rm H}_2}$ is less important than ΣSFR in determining the local metallicity. This result indicates that gas accretion, resulting in local metallicity dilution and local boosting of star formation, is unlikely to be the primary origin of the rFMR. The local metallicity depends also on the global properties of galaxies. We find a strong dependence on the total stellar mass (M*) and a weaker (inverse) dependence on the total SFR. The global metallicity scaling relations, therefore, do not simply stem out of their resolved counterparts; global properties and processes, such as the global gravitational potential well, galaxy-scale winds and global redistribution/mixing of metals, likely contribute to the local metallicity, in addition to local production and retention.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Stellar mass, not dynamical mass nor gravitational potential, drives the mass–metallicity relationship

The widely known relation between stellar mass and gas metallicity [mass–metallicity relation (MZR)] in galaxies is often ascribed to the higher capability of more massive systems to retain metals against the action of galactic outflows. In this scenario the stellar mass would simply be an indirect proxy of the dynamical mass or of the gravitational potential. We test this scenario by using a sample of more than 1000 star-forming galaxies from the MaNGA (Mapping Nearby Galaxies at Apache Point Observatory) survey for which dynamical masses have been accurately determined. By using three different methods (average dispersion, partial correlation coefficients, and random forest), we unambiguously find that the gas metallicity depends primarily and fundamentally on the stellar mass. Once the dependence on stellar mass is taken into account, there is little or no dependence on either dynamical mass or gravitational potential (and, if anything, the metallicity dependence on the latter quantities is inverted). Our result indicates that the MZR is not caused by the retention of metals in more massive galaxies. The direct, fundamental dependence of metallicity on stellar mass suggests the much simpler scenario in which the MZR is just a consequence of the stellar mass being proportional to the integral of metals production in the galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

SDSS-IV MaNGA: Exploring the Local Scaling Relations for N/O

We present, for the first time, the relationship between local stellar mass surface density, Σ * , and N/O derived from SDSS-IV MaNGA data, using a sample of 792,765 high signal-to-noise ratio star-forming spaxels. Using a combination of phenomenological modeling and partial correlation analysis, we find that Σ * alone is insufficient to predict the N/O in MaNGA spaxels and that there is an additional dependence on the local star formation rate surface density, Σ SFR . This effect is a factor of 3 stronger than the dependence of 12+log(O/H) on Σ SFR . Surprisingly, we find that the local N/O scaling relations also depend on the total galaxy stellar mass at fixed Σ * and the galaxy size at fixed stellar mass. We find that more compact galaxies are more nitrogen rich, even when Σ * and Σ SFR are controlled for. We show that ~50% of the variance of N/O is explained by the total stellar mass and size. Thus, the evolution of nitrogen in galaxies is set by more than just local effects and does not simply track the buildup of oxygen in galaxies. The precise form of the N/O–O/H relation is therefore sensitive to the sample of galaxies from which it is derived. This result casts doubt on the universal applicability of nitrogen-based strong-line metallicity indicators derived in the local universe.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1974

Statistical modeling of scintillation effects

Scintillation produces fluctuation of the complex envelope of a modulated signal. A useful way to characterize scintillation effects is to describe the signal statistics that result when a CW wave is transmitted through a random medium. Many theoretical treatments describe the signal statistics in a manner identical with the noise theory of Rice. These theories, however, predict Rice statistics only at a very great distance from the perturbing medium, and it has been suspected that generalization to permit the quadrature components of the scattered signal to be partially correlated Gaussian variates might better match the observed signal statistics. Recent tests of signals observed through three types of structured plasma have consistently confirmed this speculation and have revealed a surprising consistency in parameters describing the first-order signal statistics.

Fremouw, E. J.↗
NASA NTRS1979

Viking Orbiter imaging observations of dust in the Martian atmosphere

More than 20 local Martian dust clouds and two global dust storms were observed with the Viking Orbiter camera. Sixteen of the local clouds were imaged in two colors or were observed with other instruments confirming their identification as dust clouds. These Viking results are compared with earth-based observations of Martian dust storms and with Mariner 9 data. Most of the dust activity seen by Viking occurred during southern hemisphere spring and early summer, when Mars was near perihelion and insolation was near maximum. About half the local clouds occurred near the edge of the southern polar cap, where winds are presumably enhanced by a strong regional temperature gradient. The other half occurred mainly in the southern hemisphere near regions where circulation models incorporating topography predict positive vertical velocities. Although dust clouds observed from earth show a similar partial correlation with models, some ambiguity exists concerning interpretation of regions near Hellespontus that have spawned the most spectacular Martian dust storms on record.

Briggs, G. A.↗
NASA NTRS1981

Methods for presentation and display of multivariate data

Methods for the presentation and display of multivariate data are discussed with emphasis placed on the multivariate analysis of variance problems and the Hotelling T(2) solution in the two-sample case. The methods utilize the concepts of stepwise discrimination analysis and the computation of partial correlation coefficients.

Myers, R. H.↗