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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Molecular evidence of toxic effect on the biofilm and its matrix

The biofilm and its extracellular polymeric substance (EPS) are known to respond to toxic chemicals. Shewanella oneidensis MR-1 wild-type (WT) and a hyper-adhesive mutant CP2-1-S1 (CP) are used as model organisms and Cr(VI) is selected as a toxic chemical in this study. We investigate the following the science questions: 1) what are the chemical differences revealed in molecular mapping between WT and CP; and 2) how WT and CP biofilms respond to a toxic chemical. The System for Analysis at the Liquid Vacuum Interface (SALVI) is employed for in situ chemical imaging of live biofilms using time-of-flight secondary ion mass spectrometry (ToF-SIMS). The SIMS spectra and principal component analysis (PCA) are used to study the biofilm spatial and chemical heterogeneity. In situ measurement of biofilm metabolic responses to toxic chemicals has been given for the first time. The method presented here is expected to be viable to study responses to other chemicals including antimicrobials in the context of antimicrobial resistance to biofilms with diverse applications.

biofilm, Shewanella oneidensis, CP2-1-S1, SALVI, T↗
DOE OSTI2018

The activation of carbon dioxide by first row transition metals (Sc – Zn)

The activation of CO2 by chloride-tagged first-row transition metal anions [ClM]- (M=Sc–Zn), was examined by mass spectrometry, quantum chemical calculations, and statistical analysis. The direct formation of [ClM(CO2)]- complexes was demonstrated in the reaction between [ClM] - and neutral CO2. In addition, the reverse reaction was investigated by energy-variable collisionally induced dissociation (CID) of the corresponding [ClM(CO2)]- anions generated in-source. Five different mono- and bi-dentate binding motifs present in the ion/CO2 complexes were identified by quantum chemical calculations and the relative stability of the each of these isomers was established and analyzed for all first-row transition metals based on the experimental and theoretical ion/molecule binding energies. It was found that the early first row transition metals form strong covalent bonds with the neutral CO2 molecule, while the late in particular copper and zinc are weakly bonded. Using simple valence bond Lewis diagrams, the binding motifs and their relative stabilities across the first row were described in a quantitative manner based on the electronic structure of the individual metals. This analysis provides an explanation for the change of most favorite bonding motif of the transition metals with CO2 along the 1st transition metal row. The nature of the activated CO2 complex and the relationship between its stability and other structural and spectral properties was also analyzed by Principal Component Analysis (PCA) and Artificial Neural Networks.

Blaziak, Kacper↗
DOE OSTI2021

Molecular imaging of plant-microbe interactions on the Brachypodium seed surface

Plant growth-promoting rhizobacteria (PGPR) play a crucial role in biological control and pathogenic defense on and with-in plant tissues, however the mechanism(s) by which plants associate with PGPR to elicit such beneficial effects needs further study. Here, we present high mass resolution time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging of Brachypodium distachyon (Brachypodium) seeds with and without exposure to two model PGPR, i.e., Gram-negative Pseudomonas fluorescens SBW25::GFP (P.) and Gram-positive Arthrobacter chlorophenolicus A6::GFP (A.). Delayed image extraction was used to image PGPB-treated seed sections to reveal morphological changes. ToF-SIMS spectral compari-son, principal component analysis (PCA), and two-dimensional (2D) imaging show that the selected PGPR have different effects on the host seed surface, resulting in changes in chemical composition and morphology. Metabolite prod-ucts and biomarkers, such as flavonoids, phenolic com-pounds, fatty acids, and indole-3-acetic acid (IAA), were ob-served on the PGPR-treated seed surfaces. These compounds had different distributions on the Brachypodium seed surface for the two PGPR, indicating that the different bacteria elicited distinct responses from the host. Our results illustrate that ToF-SIMS is an effective tool to study plant-microbe interac-tions and to provide insightful information with submicrome-ter lateral resolution of the chemical distributions associated with morphological features, potentially offering a new way to study the mechanisms underlying beneficial roles of PGPR.

PGPR, Brachypodium distachyon, ToF-SIMS, metabolit↗
DOE OSTI2021

Unsupervised machine learning for unbiased chemical classification in X-ray absorption spectroscopy and X-ray emission spectroscopy

Here we report a comprehensive computational study of unsupervised machine learning for extraction of chemically relevant information in X-ray absorption near edge structure (XANES) and in valence-to-core X-ray emission spectra (VtC-XES) for classification of a broad ensemble of sulphorganic molecules. By progressively decreasing the constraining assumptions of the unsupervised machine learning algorithm, moving from principal component analysis (PCA) to a variational autoencoder (VAE) to t-distributed stochastic neighbour embedding (t-SNE), we find improved sensitivity to steadily more refined chemical information. Surprisingly, when embedding the ensemble of spectra in merely two dimensions, t-SNE distinguishes not just oxidation state and general sulphur bonding environment but also the aromaticity of the bonding radical group with 87% accuracy as well as identifying even finer details in electronic structure within aromatic or aliphatic sub-classes. We find that the chemical information in XANES and VtC-XES is very similar in character and content, although they unexpectedly have different sensitivity within a given molecular class. We also discuss likely benefits from further effort with unsupervised machine learning and from the interplay between supervised and unsupervised machine learning for X-ray spectroscopies. Our overall results, i.e., the ability to reliably classify without user bias and to discover unexpected chemical signatures for XANES and VtC-XES, likely generalize to other systems as well as to other one-dimensional chemical spectroscopies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

TOFHunter—unlocking rapid untargeted screening of inductively coupled plasma–time-of-flight–mass spectrometry data

This study provides an overview of a newly developed open source program written in Python, TOFHunter, which permits the rapid and untargeted screening of inductively coupled plasma (ICP)-time-of-flight (TOF)-mass spectrometry (MS) datasets. ICP-TOF-MS is an analytical tool capable of providing quasi simultaneous detection of all nuclides from Li to Pu. This capability has triggered an increase in studies investigating single-particle analysis in which the TOF-MS provides correlated elemental/isotopic signatures on a particle basis in time. Similarly, laser ablation mapping has seen rapid growth owing to ICP-TOF-MS's capacity to handle fast washout times (<10 ms) while providing a broad nuclide coverage. The caveat to this broad mass coverage and high time resolution comes in the form of large, overwhelming datasets. With datasets typically on the scale of gigabytes, it is easy for a user to only focus on very targeted analytes; however, this focus diminishes the opportunity offered by the TOF-MS detector. TOFHunter applies chemometric methods, principal component analysis (PCA), and interesting features finder (IFF) on ICP-TOF-MS data, allowing for investigation of correlations, major and minor variance sources, and sample screening. The unique spectra identified by the (IFF) are used to generate a list of mass peaks, which are then matched with both nuclides and potential interferences before being exported for the user to investigate. Several case studies are discussed herein, demonstrating TOFHunter's ability to screen aqueous injections, single-particle/single-cell analysis, and probe laser ablation mapping files for unique regions of interest.

47 OTHER INSTRUMENTATION↗
DOE OSTI2012

Constraints on cosmic-ray efficiency in the supernova remnant RCW 86 using multi-wavelength observations

Several young supernova remnants (SNRs) have recently been detected in the high-energy (HE; 0.1 < E < 100 GeV) and very-high-energy (VHE; E > 100 GeV) gamma-ray domains. As exemplified by RX J1713.7-3946, the nature of this emission has been hotly debated, and direct evidence for the efficient acceleration of cosmic-ray protons at the SNR shocks still remains elusive. Here, we study the broadband gamma-ray emission from one of these young SNRs, namely RCW 86, for which several observational lines of evidence indirectly point towards the presence of accelerated hadrons. We then attempt to detect any putative hadronic signal from this SNR in the available gamma-ray data, in order to assess the level of acceleration efficiency. We also analyzed more than 40 months of data acquired by the Large Area Telescope (LAT) on-board the Fermi Gamma-Ray Space Telescope in the HE domain, and gathered all of the relevant multi-wavelength (from radio to VHE gamma-rays) information about the broadband nonthermal emission from RCW 86. For this purpose, we re-analyzed the archival X-ray data from the ASCA/Gas Imaging Spectrometer (GIS), the XMM-Newton/EPIC-MOS, and the RXTE/Proportional Counter Array (PCA). Beyond the expected Galactic diffuse background, no significant gamma-ray emission in the direction of RCW 86 is detected in any of the 0.1–1, 1–10 and 10–100 GeV Fermi-LAT maps. The derived HE upper limits, together with the H.E.S.S. measurements in the VHE domain, are incompatible with a standard D$-2\atop{p}$ hadronic emission arising from proton-proton interactions, and can only be accommodated by a spectral index Γ ≤ 1.8, i.e. a value in-between the standard (test-particle) index and the asymptotic limit of theoretical particle spectra in the case of strongly modified shocks. In such a hadronic scenario, the total energy in accelerated particles is at the level of ηCR = ECR/ESN ~0.07 d$2\atop{2.5}$kpc/$\tilde{n}$ (with the distance d 2.5 kpc ≡ d/2.5 kpc and the effective density $\tilde{n}$ ≡ $\tilde{n}$ /1 cm -3 ), and the average magnetic field must be stronger than 50 μG in order to significantly suppress any leptonic contribution. On the other hand, the interpretation of the gamma-ray emission by inverse Compton scattering of high energy electrons reproduces the multi-wavelength data using a reasonable value for the average magnetic field of 15–25 μG. In this leptonic scenario, we derive a conservative upper limit to ηCR of 0.04 d $2\atop{2.5}$ kpc/$\tilde{n}$. Furthermore, we discuss these results in the light of existing estimates of the magnetic field strength, the effective density and the acceleration efficiency in RCW 86.

2.3↗
DOE OSTI2012

Spatial distribution of elements in the spheroids by prostate tumor cells using synchrotron radiation x-ray fluorescence

The formation of three-dimensional cell microspheres such as spheroids has attracted attention as a useful culture technique. In this study, we investigated the trace elemental distribution (mapping) in spheroids derived from tissue prostate cancer (PCa). The measurements were performed in standard geometry of 45 deg. incidence, exciting with a white beam and using an optical capillary with 20 {mu}m diameter collimation in the XRF beam line at the Synchrotron Light National Laboratory (Campinas, Brazil). The results showed that most elements analyzed presented non-uniform distribution. P, S and Cl showed similar elemental distribution in all the samples analyzed. K, Ca, Fe, and Cu showed different elemental distribution for the spheroids analyzed. Zinc presented more intense distributions in the spheroid central region for all spheroids analyzed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Development of taste sensor system for differentiation of Indonesian herbal medicines

In Indonesia, herbal medicines are usually produced by small and medium enterprises which are relatively low in quality control. The purpose of this paper is to report that we have developed a taste sensor system with global selectivity, i.e., electronic tongue (e-tongue) for differentiation of Indonesian herbal medicines. The e-tongue was composed of five kinds of ion selective electrodes as working electrodes, data acquisition system, and pattern recognition system. Each ion selective electrode (ISE) was built by attaching lipid/polymer membrane. For this purpose, the five kinds of membranes were built by mixing lipid, plasticizer (nitrophenyl octyl ether/NPOE), polyvinyl chloride (PVC), and tetrahydrofuran (THF). In this study, we employed five kinds of lipid, namely oleic acid (OA), dioctyl phosphate (DOP), decyl alcohol (DA), dodecylamine (DDC), and trioctyl methyl ammonium chloride (TOMA). In this case, the membranes transform information of taste substances into electric signal. The five kinds of Indonesian herbal medicine were purchased from local supermarket in Yogyakarta, i.e., kunyit asam (made from turmeric and tamarind), beras kencur (made from rice and kencur), jahe wangi (made from ginger and fragrance), sirih wangi (made from betel leaf), and temulawak (made from Javanese ginger). Prior to detecting the taste from the Indonesian herbal medicine samples, each ion selective electrode was tested with five basic taste samples, i.e., for saltiness, sweetness, umami, bitterness, and sourness. All ISEs showed global selectivity to all samples. Furthermore, the array of ISEs showed specific response pattern to each Indonesian herbal medicine. For pattern recognition system, we employed principle component analysis (PCA). As a result, the e-tongue was able to differentiate five kinds of Indonesian herbal medicines, proven by the total variance of first and second principle components is about 93%. For the future, the e-tongue may be developed for quality control application in herbal medicine industries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Big Data in Reciprocal Space: Sliding Fast Fourier Transforms for Determining Periodicity

Significant advances in atomically resolved imaging of crystals and surfaces have occurred in the last decade allowing unprecedented insight into local crystal structures and periodicity. Yet, the analysis of the long-range periodicity from the local imaging data, critical to correlation of functional properties and chemistry to the local crystallography, remains a challenge. Here, we introduce a Sliding Fast Fourier Transform (FFT) filter to analyze atomically resolved images of in-situ grown La5/8Ca3/8MnO3 films. We demonstrate the ability of sliding FFT algorithm to differentiate two sub-lattices, resulting from a mixed-terminated surface. Principal Component Analysis (PCA) and Independent Component Analysis (ICA) of the Sliding FFT dataset reveal the distinct changes in crystallography, step edges and boundaries between the multiple sub-lattices. The method is universal for images with any periodicity, and is especially amenable to atomically resolved probe and electron-microscopy data for rapid identification of the sub-lattices present.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Probing biolabels for high throughput biosensing via synchrotron radiation SEIRA technique

Bio-diagnostic assays of high complexity rely on nanoscaled assay recognition elements that can provide unique selectivity and design-enhanced sensitivity features. High throughput performance requires the simultaneous detection of various analytes combined with appropriate bioassay components. Nanoparticle induced sensitivity enhancement, and subsequent multiplexed capability Surface-Enhanced InfraRed Absorption (SEIRA) assay formats are fitting well these purposes. SEIRA constitutes an ideal platform to isolate the vibrational signatures of targeted bioassay and active molecules. The potential of several targeted biolabels, here fluorophore-labeled antibody conjugates, chemisorbed onto low-cost biocompatible gold nano-aggregates substrates have been explored for their use in assay platforms. Dried films were analyzed by synchrotron radiation based FTIR/SEIRA spectro-microscopy and the resulting complex hyperspectral datasets were submitted to automated statistical analysis, namely Principal Components Analysis (PCA). The relationships between molecular fingerprints were put in evidence to highlight their spectral discrimination capabilities. We demonstrate that robust spectral encoding via SEIRA fingerprints opens up new opportunities for fast, reliable and multiplexed high-end screening not only in biodiagnostics but also in vitro biochemical imaging.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2019

A data-driven approach to construct a quantitative relationship between microstructural features of fatigue cracks and contact acoustic nonlinearity

This study demonstrates the feasibility of a data-driven approach to construct a quantitative relationship between nonlinear acoustic parameters and microstructural features of contact interfaces. The near-surface nonlinearity is measured using dynamic acousto-elastic testing (DAET) with a surface wave probe, while the microstructural features are extracted from scanning electron microscopy (SEM) images of fatigue cracks. Four aluminum alloy samples, each having a fatigue crack are prepared. Six local nonlinearity parameters are measured at different locations along the crack propagation direction. A total of 40 local measurements are acquired. A principal component analysis (PCA) reveals that all six nonlinearity parameters are correlated and hence can be replaced by one principal component (PC). Fifteen crack micro-geometrical features at each measurement point were extracted from the SEM images. Regression analysis is used to relate the PC of the nonlinearity parameters to the microstructural features at the crack interface. We compare three regression models that take variable selection into account: stepwise multiple linear regression (MLR), stepwise principal component regression (PCR), and least absolute shrinkage and selection operator (LASSO). Despite having different principles, the three predictive models identify two features as the most significant in predicting the interface nonlinearity: the crack aperture (opening) distribution and the distance to the crack tip. The differences between the three models and the physical interpretation of the data-driven predictions are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Manifold projection image segmentation for nano-XANES imaging

As spectral imaging techniques are becoming more prominent in science, advanced image segmentation algorithms are required to identify appropriate domains in these images. We present a version of image segmentation called manifold projection image segmentation (MPIS) that is generally applicable to a broad range of systems without the need for training because MPIS uses unsupervised machine learning with a few physically motivated hyperparameters. We apply MPIS to nanoscale x-ray absorption near edge structure (XANES) imaging, where XANES spectra are collected with nanometer spatial resolution. We show the superiority of manifold projection over linear transformations, such as the commonly used principal component analysis (PCA). Moreover, MPIS maintains accuracy while reducing computation time and sensitivity to noise compared to the standard nano-XANES imaging analysis procedure. Finally, we demonstrate how multimodal information, such as x-ray fluorescence data and spatial location of pixels, can be incorporated into the MPIS framework. We propose that MPIS is adaptable for any spectral imaging technique, including scanning transmission x-ray microscopy, where the length scale of domains is larger than the resolution of the experiment.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Descriptors of water aggregation

For this work, we rely on a total of 23 (cluster size, 8 structural, and 14 connectivity) descriptors to investigate structural patterns and connectivity motifs associated with water cluster aggregation. In addition to the cluster size n (number of molecules), the 8 structural descriptors can be further categorized into (i) one-body (intramolecular): covalent OH bond length (r OH ) and HOH bond angle (θ HOH ), (ii) two-body: OO distance (r OO ), OHO angle (θ OHO ), and HOOX dihedral angle ($\phi$ HOOX ), where X lies on the bisector of the HOH angle, (iii) three-body: OOO angle (θ OOO ), and (iv) many-body: modified tetrahedral order parameter (q) to account for two-, three-, four-, five-coordinated molecules (q m , m = 2, 3, 4, 5) and radius of gyration (R g ). The 14 connectivity descriptors are all many-body in nature and consist of the AD, AAD, ADD, AADD, AAAD, AAADD adjacencies [number of hydrogen bonds accepted (A) and donated (D) by each water molecule], Wiener index, Average Shortest Path Length, hydrogen bond saturation (% HB), and number of non-short-circuited three-membered cycles, four-membered cycles, five-membered cycles, six-membered cycles, and seven-membered cycles. We mined a previously reported database of 4 948 959 water cluster minima for (H 2 O) n , n = 3–25 to analyze the evolution and correlation of these descriptors for the clusters within 5 kcal/mol of the putative minima. It was found that r OH and % HB correlated strongly with cluster size n, which was identified as the strongest predictor of energetic stability. Marked changes in the adjacencies and cycle count were observed, lending insight into changes in the hydrogen bond network upon aggregation. A Principal Component Analysis (PCA) was employed to identify descriptor dependencies and group clusters into specific structural patterns across different cluster sizes. The results of this study inform our understanding of how water clusters evolve in size and what appropriate descriptors of their structural and connectivity patterns are with respect to system size, stability, and similarity. The approach described in this study is general and can be easily extended to other hydrogen-bonded systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Sarcomeric perturbations of myosin motors lead to dilated cardiomyopathy in genetically modified MYL2 mice

Dilated cardiomyopathy (DCM) is a devastating heart disease that affects about 1 million people in the United States, but the underlying mechanisms remain poorly understood. In this study, we aimed to determine the biomechanical and structural causes of DCM in transgenic mice carrying a novel mutation in the MYL2 gene, encoding the cardiac myosin regulatory light chain. Transgenic D94A (aspartic acid-to-alanine) mice were created and investigated by echocardiography and invasive hemodynamic and molecular structural and functional assessments. Consistent with the DCM phenotype, a significant reduction of the ejection fraction (EF) was observed in ~5- and ~12-mo-old male and female D94A lines compared with respective WT controls. Younger male D94A mice showed a more pronounced left ventricular (LV) chamber dilation compared with female counterparts, but both sexes of D94A lines developed DCM by 12 mo of age. The hypocontractile activity of D94A myosin motors resulted in the rightward shift of the force–pCa dependence and decreased actin-activated myosin ATPase activity. Consistent with a decreased Ca 2+ sensitivity of contractile force, a small-angle X-ray diffraction study, performed in D94A fibers at submaximal Ca 2+ concentrations, revealed repositioning of the D94A cross-bridge mass toward the thick-filament backbone supporting the hypocontractile state of D94A myosin motors. Our data suggest that structural perturbations at the level of sarcomeres result in aberrant cardiomyocyte cytoarchitecture and lead to LV chamber dilation and decreased EF, manifesting in systolic dysfunction of D94A hearts. The D94A-induced development of DCM in mice closely follows the clinical phenotype and suggests that MYL2 may serve as a new therapeutic target for dilated cardiomyopathy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Nebulin and titin modulate cross-bridge cycling and length-dependent calcium sensitivity

Various mutations in the structural proteins nebulin and titin that are present in human disease are known to affect the contractility of striated muscle. Loss of nebulin is associated with reduced actin filament length and impairment of myosin binding to actin, whereas titin is thought to regulate muscle passive elasticity and is likely involved in length-dependent activation. Here, we sought to assess the modulation of muscle function by these sarcomeric proteins by using the computational platform muscle simulation code (MUSICO) to quantitatively separate the effects of structural changes, kinetics of cross-bridge cycling, and calcium sensitivity of the thin filaments. The simulations show that variation in thin filament length cannot by itself account for experimental observations of the contractility in nebulin-deficient muscle, but instead must be accompanied by a decreased myosin binding rate. Additionally, to match the observed calcium sensitivity, the rate of TnI detachment from actin needed to be increased. Simulations for cardiac muscle provided quantitative estimates of the effects of different titin-based passive elasticities on muscle force and activation in response to changes in sarcomere length and interfilament lattice spacing. Predicted force–pCa relations showed a decrease in both active tension and sensitivity to calcium with a decrease in passive tension and sarcomere length. We conclude that this behavior is caused by partial redistribution of the muscle load between active muscle force and titin-dependent passive force, and also by redistribution of stretch along the thin filament, which together modulate the release of TnI from actin. These data help advance understanding of how nebulin and titin mutations affect muscle function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

COSMIC SHEAR RESULTS FROM THE DEEP LENS SURVEY. I. JOINT CONSTRAINTS ON {Omega} {sub M} AND {sigma}{sub 8} WITH A TWO-DIMENSIONAL ANALYSIS

We present a cosmic shear study from the Deep Lens Survey (DLS), a deep BVRz multi-band imaging survey of five 4 deg{sup 2} fields with two National Optical Astronomy Observatory (NOAO) 4 m telescopes at Kitt Peak and Cerro Tololo. For both telescopes, the change of the point-spread-function (PSF) shape across the focal plane is complicated, and the exposure-to-exposure variation of this position-dependent PSF change is significant. We overcome this challenge by modeling the PSF separately for individual exposures and CCDs with principal component analysis (PCA). We find that stacking these PSFs reproduces the final PSF pattern on the mosaic image with high fidelity, and the method successfully separates PSF-induced systematics from gravitational lensing effects. We calibrate our shears and estimate the errors, utilizing an image simulator, which generates sheared ground-based galaxy images from deep Hubble Space Telescope archival data with a realistic atmospheric turbulence model. For cosmological parameter constraints, we marginalize over shear calibration error, photometric redshift uncertainty, and the Hubble constant. We use cosmology-dependent covariances for the Markov Chain Monte Carlo analysis and find that the role of this varying covariance is critical in our parameter estimation. Our current non-tomographic analysis alone constrains the {Omega} {sub M}-{sigma}{sub 8} likelihood contour tightly, providing a joint constraint of {Omega} {sub M} = 0.262 {+-} 0.051 and {sigma}{sub 8} = 0.868 {+-} 0.071. We expect that a future DLS weak-lensing tomographic study will further tighten these constraints because explicit treatment of the redshift dependence of cosmic shear more efficiently breaks the {Omega} {sub M}-{sigma}{sub 8} degeneracy. Combining the current results with the Wilkinson Microwave Anisotropy Probe 7 year (WMAP7) likelihood data, we obtain {Omega} {sub M} = 0.278 {+-} 0.018 and {sigma}{sub 8} = 0.815 {+-} 0.020.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

MULTIWAVELENGTH OBSERVATIONS AND MODELING OF 1ES 1959+650 IN A LOW FLUX STATE

We report on the VERITAS observations of the high-frequency peaked BL Lac object 1ES 1959+650 in the period 2007-2011. This source is detected at TeV energies by VERITAS at 16.4 standard deviation ({sigma}) significance in 7.6 hr of observation in a low flux state. A multiwavelength spectral energy distribution (SED) is constructed from contemporaneous data from VERITAS, Fermi-LAT, RXTE PCA, and Swift UVOT. Swift XRT data is not included in the SED due to a lack of simultaneous observations with VERITAS. In contrast to the orphan {gamma}-ray flare exhibited by this source in 2002, the X-ray flux of the source is found to vary by an order of magnitude, while other energy regimes exhibit less variable emission. A quasi-equilibrium synchrotron self-Compton model with an additional external radiation field is used to describe three SEDs corresponding to the lowest, highest, and average X-ray states. The variation in the X-ray spectrum is modeled by changing the electron injection spectral index, with minor adjustments of the kinetic luminosity in electrons. This scenario produces small-scale flux variability of the order of {approx}< 2 in the high energy (E > 1 MeV) and very high energy (E > 100 GeV) {gamma}-ray regimes, which is corroborated by the Fermi-LAT, VERITAS, and Whipple 10 m telescope light curves.

79 ASTRONOMY AND ASTROPHYSICS↗