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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 sources NASA NTRS DOE OSTI

DOE OSTI2016

Dissociation of doubly charged clusters of lithium acetate: Asymmetric fission and breakdown of the liquid drop model: Dissociation of doubly charged clusters of lithium acetate

Unimolecular and collision-induced dissociation of doubly charged lithium acetate clusters, (CH3COOLi)nLi22+, demonstrated that Coulomb fission via charge separation is the dominant dissociation process with no contribution from the neutral evaporation processes for all such ions from the critical limit to larger cluster ions, although latter process have normally been observed in all earlier studies. These results are clearly in disagreement with the Rayleigh’s liquid drop model that has been used successfully to predict the critical size and explain the fragmentation behavior of multiply charged clusters.

Cluster Ions↗

DOE OSTI2017

Cold dark energy constraints from the abundance of galaxy clusters

We constrain cold dark energy of negligible sound speed using galaxy cluster abundance observations. In contrast to standard quasi-homogeneous dark energy, negligible sound speed implies clustering of the dark energy fluid at all scales, allowing us to measure the effects of dark energy perturbations at cluster scales. We compare those models and set the stage for using non-linear information from semi-analytical modelling in cluster growth data analyses. For this, we recalibrate the halo mass function with non-linear characteristic quantities, the spherical collapse threshold and virial overdensity, that account for model and redshift-dependent behaviours, as well as an additional mass contribution for cold dark energy. Here in this paper, we present the first constraints from this cold dark matter plus cold dark energy mass function using our cluster abundance likelihood, which self-consistently accounts for selection effects, covariances and systematic uncertainties. We combine cluster growth data with cosmic microwave background, supernovae Ia and baryon acoustic oscillation data, and find a shift between cold versus quasi-homogeneous dark energy of up to 1σ. We make a Fisher matrix forecast of constraints attainable with cluster growth data from the ongoing Dark Energy Survey (DES). For DES, we predict ~ 50 percent tighter constraints on (Ωm, w) for cold dark energy versus wCDM models, with the same free parameters. Overall, we show that cluster abundance analyses are sensitive to cold dark energy, an alternative, viable model that should be routinely investigated alongside the standard dark energy scenario.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Multivariate regression modelling for gender prediction using volatile organic compounds from hand odor profiles via HS-SPME-GC-MS

The efficacy of using human volatile organic compounds (VOCs) as a form of forensic evidence has been well demonstrated with canines for crime scene response, suspect identification, and location checking. Although the use of human scent evidence in the field is well established, the laboratory evaluation of human VOC profiles has been limited. This study used Headspace-Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS) to analyze human hand odor samples collected from 60 individuals (30 Females and 30 Males). The human volatiles collected from the palm surfaces of each subject were interpreted for classification and prediction of gender. The volatile organic compound (VOC) signatures from subjects’ hand odor profiles were evaluated with supervised dimensional reduction techniques: Partial Least Squares-Discriminant Analysis (PLS-DA), Orthogonal-Projections to Latent Structures Discriminant Analysis (OPLS-DA), and Linear Discriminant Analysis (LDA). The PLS-DA 2D model demonstrated clustering amongst male and female subjects. The addition of a third component to the PLS-DA model revealed clustering and minimal separation of male and female subjects in the 3D PLS-DA model. The OPLS-DA model displayed discrimination and clustering amongst gender groups with leave one out cross validation (LOOCV) and 95% confidence regions surrounding clustered groups without overlap. The LDA had a 96.67% accuracy rate for female and male subjects. The culminating knowledge establishes a working model for the prediction of donor class characteristics using human scent hand odor profiles.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

Ab-initio coupled-cluster effective interactions for the shell model: Application to neutron-rich oxygen and carbon isotopes

We derive and compute effective valence-space shell-model interactions from ab initio coupled-cluster theory and apply them to open-shell and neutron-rich oxygen and carbon isotopes. Our shell-model interactions are based on nucleon-nucleon and three-nucleon forces from chiral effective-field theory. We compute the energies of ground and low-lying states, and find good agreement with experiment. In particular, our computed 2 + states are consistent with N=14,16 shell closures in 22,24 O, and a weaker N=14 shell closure in 20 C. We find good agreement between our coupled-cluster effective-interaction results with those obtained from standard single-reference coupled-cluster calculations for up to eight valence neutrons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

Numerical modeling of solid-cluster evolution applied to the nanosecond solidification of water near the metastable limit

Classical nucleation theory (CNT) is a promising way to predictively model the submicrosecond kinetics of phase transitions that occur under dynamic compression, such as the suite of experiments performed over the past two decades on the solidification of liquid water to the high-pressure ice VII phase. Myint et al. [Phys. Rev. Lett. 121, 155701 (2018)] presented the first CNT-based model for these types of rapid phase transitions, but relied on an empirical scaling parameter in their transient induction model to simulate the lag time that occurs prior to the onset of significant formation of ice VII clusters in the system. To build on that study, we model the liquid water–ice VII phase transformation using a numerical discretization scheme to solve the Zel’dovich–Frenkel partial differential equation, which is a fundamental CNT-based kinetic equation that describes the statistical time-dependent behavior of solid cluster formation. The Zel’dovich–Frenkel equation inherently accounts for transience in the nucleation kinetics and eliminates the need for the empirical scaling factor used by Myint et al. One major result of this research is that transience is found to play a relatively small role in the nucleation process for the dynamic-compression time scales of the liquid water–ice VII experiments being simulated. Instead, we show that it is possible to properly model the lag time using steady-state CNT by making small refinements to the interfacial free energy value. In conclusion, we have also developed a new dimensionless parameter that may be applied a priori to predict whether or not transient nucleation will be important in a given dynamic-compression experiment.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2016

Description of alpha decay and cluster radioactivity in the dinuclear system model

A unified description of cluster radioactivity and α-decay of cold nuclei in the dinuclear system model is proposed. Quantum dynamical fluctuations along the charge (mass) asymmetry coordinate determine the spectroscopic factor, and tunneling along the relative distance coordinate determines the penetrability of the barrier of the nucleus–nucleus interaction potential. A new method for calculating the spectroscopic factor is proposed. The hindrance factors for the orbital angular momentum transfer are studied. A potential reason for the half-life to deviate from the Geiger–Nuttall law in α-decays of neutron-deficient nuclei {sup 194,} {sup 196}Rn is found. The fine structure of α-decays of U and Th isotopes is predicted and characterized. The model is used to describe α-decays from the rotational band of even–even nuclei. The known half-lives in the regions of “lead” and “tin” radioactivities are reproduced well, and the most probable cluster yields are predicted. The cluster decay of excited nuclei is discussed. The relation of cluster radioactivity to spontaneous fission and highly deformed nuclear states is analyzed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Cluster cosmology with anisotropic boosts: validation of a novel forward modelling analysis and application on SDSS redMaPPer clusters

We present a novel analysis for cluster cosmology that fully forward models the abundances, weak lensing, and the clustering of galaxy clusters. Our analysis notably includes an empirical model for the anisotropic boosts impacting the lensing and clustering signals of optical clusters. These boosts arise from a preferential selection of clusters surrounded by anisotropic large-scale structure, a consequence of the limited discrimination between line-of-sight interlopers and true cluster members offered by photometric surveys. We validate our analysis via a blind cosmology challenge on mocks, and find that we can obtain tight and unbiased cosmological constraints without informative priors or external calibrations on any of our model parameters. We then apply our analysis on the SDSS redMaPPer clusters, and find results favoring low Ωm and high σ8, combining to yield the lensing strength constraint $S_8 = 0.715_{-0.021}^{+0.024}$. We investigate potential drivers behind these results through a series of post-unblinding tests, noting that our results are consistent with existing cluster cosmology constraints but clearly inconsistent with other CMB/LSS based cosmology results. From these tests, we find hints that a suppression in the cluster lensing signal may be driving our results.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Clusters of Regional Precipitation Seasonality Change in the Community Earth System Model, Version 2

Abstract The likely changes to precipitation seasonality with warming are both impactful and not well understood. This work aims to describe areas that experience similar changes to seasonal precipitation irrespective of the original underlying precipitation seasonality. We train a self-organizing map on the difference between the seasonal cycle of precipitation in the past and in a high-warming future climate as represented by the Community Earth System Model, version 2, to create regions with similar changes in precipitation seasonality. This method is applied separately over land and ocean surfaces because of the differing processes leading to precipitation over each. This method indicates that future changes in seasonal precipitation are most varied in the tropics because of a southward shift in the intertropical convergence zone. The seasonal shifts found over midlatitude oceans indicate a poleward shift in atmospheric river activity. We find a correspondence between certain land-based precipitation changes and Köppen climate classification. The seasonality of large-scale and convective precipitation is examined for each region. The relationship between the seasonal changes to precipitation and associated atmospheric processes is discussed. These processes include atmospheric rivers, the intertropical convergence zone, tropical cyclones, and monsoons.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Integrating land surface phenology with cluster density and size improves spatially explicit models of animal density

Not Available

Butler, Matthew J.↗

DOE OSTI2017

Flexible, cluster-based analysis of the electronic medical record of sepsis with composite mixture models

The widespread adoption of electronic medical records (EMRs) in healthcare has provided vast new amounts of data for statistical machine learning researchers in their efforts to model and predict patient health status, potentially enabling novel advances in treatment. In the case of sepsis, a debilitating, dysregulated host response to infection, extracting subtle, uncataloged clinical phenotypes from the EMR with statistical machine learning methods has the potential to impact patient diagnosis and treatment early in the course of their hospitalization. However, there are significant barriers that must be overcome to extract these insights from EMR data. First, EMR datasets consist of both static and dynamic observations of discrete and continuous-valued variables, many of which may be missing, precluding the application of standard multivariate analysis techniques. Second, clinical populations observed via EMRs and relevant to the study and management of conditions like sepsis are often heterogeneous; properly accounting for this heterogeneity is critical. Here, we describe an unsupervised, probabilistic framework called a composite mixture model that can simultaneously accommodate the wide variety of observations frequently observed in EMR datasets, characterize heterogeneous clinical populations, and handle missing observations. In conclusion, we demonstrate the efficacy of our approach on a large-scale sepsis cohort, developing novel techniques built on our model-based clusters to track patient mortality risk over time and identify physiological trends and distinct subgroups of the dataset associated with elevated risk of mortality during hospitalization.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

RELICS: Strong Lens Models for Five Galaxy Clusters from the Reionization Lensing Cluster Survey

Strong gravitational lensing by galaxy clusters magnifies background galaxies, enhancing our ability to discover statistically significant samples of galaxies at ${\boldsymbol{z}}\gt 6$, in order to constrain the high-redshift galaxy luminosity functions. In this study, we present the first five lens models out of the Reionization Lensing Cluster Survey (RELICS) Hubble Treasury Program, based on new HST WFC3/IR and ACS imaging of the clusters RXC J0142.9+4438, Abell 2537, Abell 2163, RXC J2211.7–0349, and ACT-CLJ0102–49151. The derived lensing magnification is essential for estimating the intrinsic properties of high-redshift galaxy candidates, and properly accounting for the survey volume. We report on new spectroscopic redshifts of multiply imaged lensed galaxies behind these clusters, which are used as constraints, and detail our strategy to reduce systematic uncertainties due to lack of spectroscopic information. In addition, we quantify the uncertainty on the lensing magnification due to statistical and systematic errors related to the lens modeling process, and find that in all but one cluster, the magnification is constrained to better than 20% in at least 80% of the field of view, including statistical and systematic uncertainties. The five clusters presented in this paper span the range of masses and redshifts of the clusters in the RELICS program. We find that they exhibit similar strong lensing efficiencies to the clusters targeted by the Hubble Frontier Fields within the WFC3/IR field of view. Outputs of the lens models are made available to the community through the Mikulski Archive for Space Telescopes.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Study of clusters and hypernuclei production with the NICA/MPD experiment

Heavy-ion collisions provide the unique possibility to create and investigate hot and dense matter in the laboratory. At the initial stage of the reaction a QGP is formed, while the final stage is driven by the hadronization process and the formation of clusters. The capture of the produced hyperons by clusters of nucleons leads to the hypernuclei formation which is a very rare process at strangeness threshold energies. We report on the first results on the dynamical modeling of cluster formation with the combined PHSD + SACA (Parton–Hadron–Strings dynamics + Simulated Annealing Clusterization Algorithm) model at Nuclotron and NICA energies. The clusters selection in SACA is realized by a simulated annealing procedure to obtain the most bound configuration of fragments and nucleons. Based on present predictions of the combined model we study the possibility to detect such clusters and hypernuclei in the NICA/MPD detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Detecting low-mass perturbers in cluster lenses using curved arc bases

ABSTRACT Strong gravitationally lensed arcs produced by galaxy clusters have been observationally detected for several decades now. These strong lensing constraints provided high-fidelity mass models for cluster lenses that include substructure down to $10^{9{-}10}\, \mathrm{M}_\odot$. Optimizing lens models, where the cluster mass distribution is modelled by a smooth component and subhaloes associated with the locations of individual cluster galaxies, has enabled deriving the subhalo mass function, providing important constraints on the nature and granularity of dark matter. In this work, we explore and present a novel method to detect and measure individual perturbers (subhaloes, line-of-sight haloes, and wandering supermassive black holes) by exploiting their proximity to highly distorted lensed arcs in galaxy clusters, and by modelling the local lensing distortions with curved arc bases. This method offers the possibility of detecting individual low-mass perturber subhaloes in clusters and haloes along the line of sight down to a mass resolution of $10^8\, \mathrm{M}_\odot$. We quantify our sensitivity to low-mass perturbers ($M\sim 10^{7{-}9}\, \mathrm{M}_\odot$) in clusters (M ∼ 1014–15 M⊙), by creating realistic mock data. Using three lensed images of a background galaxy in the cluster SMACS J0723, taken by JWST, we study the retrieval of the properties of potential perturbers with masses $M=10^{7{-}9}\, \mathrm{M}_\odot$. From the derived posterior probability distributions for the perturber, we constrain its concentration, redshift, and ellipticity. By allowing us to probe lower mass substructures, the use of curved arc bases can lead to powerful constraints on the nature of dark matter as discrimination between dark matter models appears on smaller scales.

Astronomy & Astrophysics↗

DOE OSTI2021

Data–Driven Velocity Model Evaluation Using K–Means Clustering

In this work, we develop a data-driven clustering method to evaluate a velocity model using surface wave velocity dispersion. This is done by first computing theoretical dispersion curves for 1-D velocity profiles of all the grid locations and then splitting the resulting dispersion curves into a certain number of groups via the K-means clustering. The observed dispersion curves are also clustered following the same procedure and the velocity model is assessed by comparing the spatial patterns obtained for the observed and synthetic data sets. The method is applied to evaluate two community velocity models in southern California, CVM-S4.26 and CVM-H15.1, using phase velocity maps derived for 3–16 s Rayleigh waves. We found a good correlation in the spatial distribution of clusters between the result of CVM-S4.26 and that of the observed data, suggesting that the CVM-S4.26 fits the observed dispersion maps better than the CVM-H15.1 in terms of features extracted from the clustering analysis.

58 GEOSCIENCES↗

DOE OSTI2013

Effects of anisotropy on gravitational infall in galaxy clusters using an exact general relativistic model

We study the effects and implications of anisotropies at the scale of galaxy clusters by building an exact general relativistic model of a cluster using the inhomogeneous and anisotropic Szekeres metric. The model is built from a modified Navarro-Frenk-White (NFW) density profile. We compare this to a corresponding spherically symmetric structure in the Lemaȋtre-Tolman (LT) model and quantify the impact of introducing varying levels of anisotropy. We examine two physical measures of gravitational infall — the growth rate of density and the velocity of the source dust in the model. We introduce a generalization of the LT dust velocity profile for the Szekeres metric and demonstrate its consistency with the growth rate of density. We find that the growth rate of density in one substructure increases by 0.5%, 1.5%, and 3.75% for 5%, 10%, and 15% levels of introduced anisotropy, which is measured as the fractional displaced mass relative to the spherically symmetric case. The infall velocity of the dust is found to increase by 2.5, 10, and 20 km s{sup −1} (0.5%, 2%, and 4.5%), respectively, for the same three levels of anisotropy. This response to the anisotropy in a structure is found to be strongly nonlinear with respect to the strength of anisotropy. These relative velocities correspond to an equivalent increase in the total mass of the spherically symmetric structure of 1%, 3.8%, and 8.4%, indicating that not accounting for the presence of anisotropic mass distributions in cluster models can strongly bias the determination of physical properties like the total mass.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Description of alternating-parity bands within the dinuclear-system model

A cluster approach is used to describe ground-state-based alternating-parity bands in even–even nuclei and to study the band-termination mechanism. A method is proposed for testing the cluster nature of alternating-parity bands.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS1985

Spectral constraints on models of gas in clusters of galaxies

The HEAO 1A2 spectra of clusters of galaxies are used to determine the temperature profile which characterizes the X-ray emitting gas. Strong evidence of nonisothermality is found for the Coma, A85, and A1795 clusters. Properties of the cluster potential which binds the gas are calculated for a range of model parameters. The typical binding mass, if the gas is adiabatic, is 2-4E14 solar masses and is quite centrally concentrated. In addition, the Fe abundance in Coma is .26 + or - .06 solar, less than the typical value (.5) found for rich clusters. The results for the gas in Coma may imply a physical description of the cluster which is quite different from what was previously believed.

Henriksen, M. J.↗

NASA NTRS1985

Spectral constraints on models of gas in clusters of galaxies

Henriksen, M. J.↗