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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Solving the excitation and chemical abundances in shocks: The case of HH 1

We present deep spectroscopic (3600–24700 Å ) X-shooter observations of the bright Herbig–Haro object HH 1, one of the best laboratories to study the chemical and physical modifications caused by protostellar shocks on the natal cloud. We observe atomic fine structure lines, H i and He i recombination lines and H{sub 2} ro-vibrational lines (more than 500 detections in total). Line emission was analyzed by means of Non-local Thermal Equilibiurm codes to derive the electron temperature and density, and for the first time we are able to accurately probe different physical regimes behind a dissociative shock. We find a temperature stratification in the range 4000 K ÷ 80,000 K, and a significant correlation between temperature and ionization energy. Two density regimes are identified for the ionized gas, a more tenuous, spatially broad component (density ∼10{sup 3} cm{sup −3}), and a more compact component (density ⩾ 10{sup 5} cm{sup −3}) likely associated with the hottest gas. A further neutral component is also evidenced, having a temperature ≲10,000 K and a density >10{sup 4} cm{sup −3}. The gas fractional ionization was estimated by solving the ionization equilibrium equations of atoms detected in different ionization stages. We find that neutral and fully ionized regions co-exist inside the shock. Also, indications in favor of at least partially dissociative shock as the main mechanism for molecular excitation are derived. Chemical abundances are estimated for the majority of the detected species. On average, abundances of non-refractory/refractory elements are lower than solar of about 0.15/0.5 dex. This indicates the presence of dust inside the medium, with a depletion factor of iron of ∼40%.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Simultaneous 3D MR elastography of the in vivo mouse brain

The feasibility of sample interval modulation (SLIM) magnetic resonance elastography (MRE) for the in vivo mouse brain is assessed, and an alternative SLIM-MRE encoding method is introduced. In SLIMMRE, the phase accumulation for each motion direction is encoded simultaneously by varying either the start time of the motion encoding gradient (MEG), SLIM-phase constant (SLIM-PC), or the initial phase of the MEG, SLIM-phase varying (SLIM-PV). SLIM-PC provides gradient moment nulling, but the mutual gradient shift necessitates increased echo time (TE). SLIM-PV requires no increased TE, but exhibits nonuniform flow compensation. Comparison was to conventional MRE using six C57BL/6 mice. For SLIMPC, the Spearman’s rank correlation to conventional MRE for the shear storage and loss modulus images were 80% and 76%, respectively, and likewise for SLIM-PV, 73% and 69%, respectively. The results of the Wilcoxon rank sum test showed that there were no statistically significant differences between the spatially averaged shear moduli derived from conventional-MRE, SLIM-PC, and SLIM-PV acquisitions. Both SLIM approaches were comparable to conventional MRE scans with Spearman’s rank correlation of 69%-80% and with 3 times reduction in scan time. As a result, the SLIM-PC method had the best correlation, and SLIM-PV may be a useful tool in experimental conditions, where both measurement time and T2 relaxation is critical.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Conformal maps of viscous electron flow in the Gurzhi crossover

Herein we investigate the impact of geometric constriction on the viscous flow of electron liquid through quantum point contacts. We provide analysis on the electric potential distribution given the setup of a slit configuration and use the method of conformal mapping to obtain analytical results. The potential profile can be tested and contrasted experimentally with the scanning tunneling potentiometry technique. We discuss intricate physics that underlies the Gurzhi effect, i.e., the enhancement of conductivity in the viscous flow, and compare results for different boundary conditions. In addition, we calculate the temperature dependence of the momentum relaxation time as a result of impurity assisted quasiballistic interference effects and discuss various correlational corrections that lead to the violation of Matthiessen's rule in the hydrodynamic regime. We caution that spatially inhomogeneous profiles of current in the Gurzhi crossover between Ohmic and Stokes flows might also appear in the nonhydrodynamic limit where nonlocality plays an important role. This conclusion is corroborated by calculation of dispersive conductivity in the weakly impure limit.

2-dimensional systems↗
DOE OSTI2021

Simultaneous velocity and density measurements of fully developed Rayleigh-Taylor mixing

Here, the dynamics of molecular mixing and the energy transfer process in the Rayleigh-Taylor instability (RTI) are studied through the collection of simultaneous density-velocity measurements. These experiments provide simultaneous density-velocity field measurements, in contrast to previous point measurements. Statistically stationary experiments are performed in a “convective-type” gas tunnel facility, with density contrast achieved through the injection of helium into the bottom stream. Three experiments at Atwood number ≈ 0.1 are captured at three outer scale Reynolds numbers Re = 520, 2260, and 4050. Particle image velocimetry and laser induced fluorescence are employed simultaneously. Statistics of the density and velocity show self-similar collapse of RTI profiles at large Reynolds number Re >2000. Flat velocity profiles indicate homogeneous turbulence characteristics in the core of the mixing region. Significant anisotropy develops in the flow, with horizontal velocity fluctuations being only 60% of the vertical velocity fluctuations. The turbulent mass flux is found to be asymmetric about the centerline, with increased peak towards the spike. Measurements of the molecular mixing show that mixing is maximized at the core of the flow and increases with increased Reynolds number. The transport equation of density-specific-volume correlation b shows that it is mostly produced in the core of the mixing region, and that the spatial evolution of its profile is the result of transport by bulk motion of the bubble and spike. Energy transfer from gravitational potential energy to turbulent kinetic energy and viscous dissipation is observed to occur in the experiment with a ratio of dissipated energy to potential energy released of 38%. The analysis of the turbulent kinetic energy transport equation budget reveals that production is the primary mechanism towards the growth of turbulent kinetic energy in the core of the flow, and is asymmetrically slightly skewed towards the spike. However, it is through the transport that the strong advection at the edges of the mixing region is maintained.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Plating and Stripping of Lithium Metal Stabilized by a Block Copolymer Electrolyte: Local Current Density Measurement and Modeling

Here, plating and stripping of lithium protrusions in lithium metal symmetric cells containing a solid block copolymer electrolyte was studied as a function of time in 3D using time-resolved X-ray tomography. These measurements enabled determination of the spatial variation in current densities at the plating and stripping electrodes. The initial interelectrode distance was 27 μm. Correlation functions were calculated to reveal the relationships between current densities at the two electrodes and local electrolyte thickness. Current densities at opposing electrode locations during protrusion growth is uncorrelated until the local interelectrode distance decreases to less than 6 μm, just before the cell shorts. Mass balance was used to determine the area from which lithium ions that form a protrusion were stripped. Computational modeling of the plating and stripping process reveals the interplay between electrochemical and mechanical driving forces and their effect on nonuniform current distribution. Model predictions were compared with experiments without resorting to any adjustable parameters. The computed correlation functions were in qualitative agreement with experiments. Finally, the model was used to calculate contour plots of electrochemical potential within the electrolyte, shedding light on how geometry, salt concentration, interelectrode distance, and mechanical stress influence local rates of electrochemical reaction.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quantitative phenotyping of crop roots with spectral electrical impedance tomography: a rhizotron study with optimized measurement design

Background: Root systems are key contributors to plant health, resilience, and, ultimately, yield of agricultural crops. To optimize plant performance, phenotyping trials are conducted to breed plants with diverse root traits. However, traditional analysis methods are often labour-intensive and invasive to the root system, therefore limiting high-throughput phenotyping. Spectral electrical impedance tomography (sEIT) could help as a non-invasive and cost-efficient alternative to optical root analysis, potentially providing 2D or 3D spatio-temporal information on root development and activity. Although impedance measurements have been shown to be sensitive to root biomass, nutrient status, and diurnal activity, only few attempts have been made to employ tomographic algorithms to recover spatially resolved information on root systems. In this study, we aim to establish relationships between tomographic electrical polarization signatures and root traits of different fine root systems (maize, pinto bean, black bean, and soy bean) under hydroponic conditions. Results: Our results show that, with the use of an optimized data acquisition scheme, sEIT is capable of providing spatially resolved information on root biomass and root surface area for all investigated root systems. We found strong correlations between the total polarization strength and the root biomass (R 2 = 0.82) and root surface area (R 2 = 0.8). Our findings suggest that the captured polarization signature is dominated by cell-scale polarization processes. Additionally, we demonstrate that the resolution characteristics of the measurement scheme can have a significant impact on the tomographic reconstruction of root traits. Conclusion: Our findings showcase that sEIT is a promising tool for the tomographic reconstruction of root traits in high-throughput root phenotyping trials and should be evaluated as a substitute for traditional, often time-consuming, root characterization methods.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Machine-Learning-Based Mapping and Modeling of Solar Energy with Ultra-High Spatiotemporal Granularity

Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).

14 SOLAR ENERGY↗
DOE OSTI2025

Electron Energy-Loss Spectroscopy and Differential Phase Contrast Imaging with Active Decision in Multimodal Electron Microscopy: Isotopic detection at the atomic scale

Isotopic engineering provides a powerful route to control phonon behavior in crystalline solids, enabling fundamental studies of lattice dynamics and heat transport at the atomic scale. Here, we directly visualize isotope-dependent phonon propagation in epitaxial Cr 2 O 3 using aberration-corrected scanning transmission electron microscopy (STEM) combined with monochromated, high-energy-resolution electron energy-loss spectroscopy (EELS). Guided by ab initio phonon calculations, we demonstrate that optical phonon modes above 70 meV are predominantly oxygen-derived and exhibit measurable redshifts upon substitution of natural 16 O by enriched 18 O. Spatially resolved vibrational spectrum imaging reveals isotope-enriched tracer layers within Cr 2 O 3 thin films, correlating isotope concentration with phonon intensity variations and vibrational energy shifts. At the nanometer and atomic scales, vibrational EELS mapping uncovers coherent phonon propagation across isotopic interfaces, consistent with theoretical phonon density of states and dispersion relations. These results establish vibrational EELS as a quantitative probe for isotope-dependent phonon transport in materials, opening new possibilities for studying energy dissipation and lattice dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Extended X-Ray Monitoring of Gravitational Lenses with Chandra and Joint Constraints on X-Ray Emission Regions

We present an X-ray photometric analysis of six gravitationally lensed quasars, with observation campaigns spanning from 5 to 14 years, measuring the total (0.83–21.8 keV restframe), soft- (0.83–3.6 keV), and hard- (3.6–21.8 keV) band image flux ratios for each epoch. Using the ratios of the model-predicted macro-magnifications as baselines, we build differential microlensing light curves and obtain joint likelihood functions for the average X-ray emission region sizes. Our analysis yields a probability distribution function for the average half-light radius of the X-ray emission region in the sample that peaks slightly above 1 gravitational radius and with nearly indistinguishable 68% confidence (one-sided) upper limits of 17.8 and 18.9 gravitational radii for the soft and hard X-ray emitting regions, assuming a mean stellar mass of 0.3 M {sub ⊙}. We see hints of energy dependent microlensing between the soft and hard bands in two of the objects. In a separate analysis on the root-mean-square (rms) of the microlensing variability, we find significant differences between the soft and hard bands, but the sign of the difference is not consistent across the sample. This suggests the existence of some kind of spatial structure to the X-ray emission in an otherwise extremely compact source. We also discover a correlation between the rms microlensing variability and the average microlensing amplitude.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Downscaling Solar Power Output to 4-Seconds for Use in Integration Studies (Presentation)

High penetration renewable integration studies require solar power data with high spatial and temporal accuracy to quantify the impact of high frequency solar power ramps on the operation of the system. Our previous work concentrated on downscaling solar power from one hour to one minute by simulation. This method used clearness classifications to categorize temporal and spatial variability, and iterative methods to simulate intra-hour clearness variability. We determined that solar power ramp correlations between sites decrease with distance and the duration of the ramp, starting at around 0.6 for 30-minute ramps between sites that are less than 20 km apart. The sub-hour irradiance algorithm we developed has a noise floor that causes the correlations to approach ~0.005. Below one minute, the majority of the correlations of solar power ramps between sites less than 20 km apart are zero, and thus a new method to simulate intra-minute variability is needed. These intra-minute solar power ramps can be simulated using several methods, three of which we evaluate: a cubic spline fit to the one-minute solar power data; projection of the power spectral density toward the higher frequency domain; and average high frequency power spectral density from measured data. Each of these methods either under- or over-estimates the variability of intra-minute solar power ramps. We show that an optimized weighted linear sum of methods, dependent on the classification of temporal variability of the segment of one-minute solar power data, yields time series and ramp distributions similar to measured high-resolution solar irradiance data.

14 SOLAR ENERGY↗
DOE OSTI2013

Downscaling Solar Power Output to 4-Seconds for Use in Integration Studies: Preprint

High penetration renewable integration studies require solar power data with high spatial and temporal accuracy to quantify the impact of high frequency solar power ramps on the operation of the system. Our previous work concentrated on downscaling solar power from one hour to one minute by simulation. This method used clearness classifications to categorize temporal and spatial variability, and iterative methods to simulate intra-hour clearness variability. We determined that solar power ramp correlations between sites decrease with distance and the duration of the ramp, starting at around 0.6 for 30-minute ramps between sites that are less than 20 km apart. The sub-hour irradiance algorithm we developed has a noise floor that causes the correlations to approach ~0.005. Below one minute, the majority of the correlations of solar power ramps between sites less than 20 km apart are zero, and thus a new method to simulate intra-minute variability is needed. These intra-minute solar power ramps can be simulated using several methods, three of which we evaluate: a cubic spline fit to the one-minute solar power data; projection of the power spectral density toward the higher frequency domain; and average high frequency power spectral density from measured data. Each of these methods either under- or over-estimates the variability of intra-minute solar power ramps. We show that an optimized weighted linear sum of methods, dependent on the classification of temporal variability of the segment of one-minute solar power data, yields time series and ramp distributions similar to measured high-resolution solar irradiance data.

14 SOLAR ENERGY↗
DOE OSTI2018

A Big Data Analytics Framework for HPC Log Data: Three Case Studies Using the Titan Supercomputer Log

Reliability, availability and serviceability (RAS) logs of high performance computing (HPC) resources, when closely investigated in spatial and temporal dimensions, can provide invaluable information regarding system status, performance, and resource utilization. These data are often generated from multiple logging systems and sensors that cover many components of the system. The analysis of these data for finding persistent temporal and spatial insights faces two main difficulties: the volume of RAS logs makes manual inspection difficult and the unstructured nature and unique properties of log data produced by each subsystem adds another dimension of difficulty in identifying implicit correlation among recorded events. To address these issues, we recently developed a multi-user Big Data analytics framework for HPC log data at Oak Ridge National Laboratory (ORNL). This paper introduces three in-progress data analytics projects that leverage this framework to assess system status, mine event patterns, and study correlations between user applications and system events. We describe the motivation of each project and detail their workflows using three years of log data collected from ORNL's Titan supercomputer.

Park, Byung↗
DOE OSTI2024

Building spatial symmetries into parameterized quantum circuits for faster training

Abstract Practical success of quantum learning models hinges on having a suitable structure for the parameterized quantum circuit. Such structure is defined both by the types of gates employed and by the correlations of their parameters. While much research has been devoted to devising adequate gate-sets, typically respecting some symmetries of the problem, very little is known about how their parameters should be structured. In this work, we show that an ideal parameter structure naturally emerges when carefully considering spatial symmetries (i.e. the symmetries that are permutations of parts of the system under study). Namely, we consider the automorphism group of the problem Hamiltonian, leading us to develop a circuit construction that is equivariant under this symmetry group. The benefits of our novel circuitstructure, called ORB, are numerically probed in several ground-state problems. We find a consistent improvement (in terms of circuit depth, number of parameters required, and gradient magnitudes) compared to literature circuit constructions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

XCT analysis of the influence of melt strategies on defect population in Ti–6Al–4V components manufactured by Selective Electron Beam Melting

Selective Electron Beam Melting (SEBM) is a promising powder bed Additive Manufacturing technique for near-net-shape manufacture of high-value titanium components. However without post-manufacture HIPing the fatigue life of SEBM parts is currently dominated by the presence of porosity. In this study, the size, volume fraction, and spatial distribution of the pores in model samples have been characterised in 3D, using X-ray Computed Tomography, and correlated to the process variables. The average volume fraction of the pores (< 0.2%) was measured to be lower than that usually observed in competing processes, such as selective laser melting, but a strong relationship was found with the different beam strategies used to contour, and infill by hatching, a part section. The majority of pores were found to be small spherical gas pores, concentrated in the infill hatched region; this was attributed to the lower energy density and less focused beam used in the infill strategy allowing less opportunity for gas bubbles to escape the melt pool. Overall, increasing the energy density or focus of the beam was found to correlate strongly to a reduction in the level of gas porosity. Rarer irregular shaped pores were mostly located in the contour region and have been attributed to a lack of fusion between powder particles. - Graphical abstract: Display Omitted - Highlights: • Vast majority of defects detected were small spherical gas pores. • Gas bubbles trapped in the powder granules expand and coalesce in the melt pool. • Pores have been shown not to be randomly distributed. • Larger and deeper melt pools give more opportunity for gas to escape. • Minor changes to melt strategy result in significant reductions in pore population.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Spatial Mode Correction of Single Photons Using Machine Learning

Abstract Spatial modes of light constitute valuable resources for a variety of quantum technologies ranging from quantum communication and quantum imaging to remote sensing. Nevertheless, their vulnerabilities to phase distortions, induced by random media, impose significant limitations on the realistic implementation of numerous quantum‐photonic technologies. Unfortunately, this problem is exacerbated at the single‐photon level. Over the last two decades, this challenging problem has been tackled through conventional schemes that utilize optical nonlinearities, quantum correlations, and adaptive optics. In this article, the self‐learning and self‐evolving features of artificial neural networks are exploited to correct the complex spatial profile of distorted Laguerre–Gaussian modes at the single‐photon level. Furthermore, the potential of this technique is used to improve the channel capacity of an optical communication protocol that relies on structured single photons. The results have important implications for real‐time turbulence correction of structured photons and single‐photon images.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Spatially Resolved Photoexcited Charge-Carrier Dynamics in Phase-Engineered Monolayer MoS 2

A fundamental understanding of the intrinsic optoelectronic properties of atomically thin transition metal dichalcogenides (TMDs) is crucial for its integration into high performance semiconductor devices. We investigate the transport properties of chemical vapor deposition (CVD) grown monolayer molybdenum disulfide (MoS 2 ) under photo-excitation using correlated scanning photocurrent microscopy and photoluminescence imaging. We examined the effect of local phase transformation underneath the metal electrodes on the generation of photocurrent across the channel length with diffraction-limited spatial resolution. While maximum photocurrent generation occurs at the Schottky contacts of semiconducting (2H-phase) MoS 2 , after the metallic phase transformation (1T-phase), the photocurrent peak is observed towards the center of the device channel, suggesting a strong reduction of native Schottky barriers. Analysis using the bias and position dependence of the photocurrent indicates that the Schottky barrier heights are few meV for 1T- and ~200 meV for 2H-contacted devices. We also demonstrate that a reduction of native Schottky barriers in a 1T device enhances the photo responsivity by more than one order of magnitude, a crucial parameter in achieving high performance optoelectronic devices. The obtained results pave a pathway for the fundamental understanding of intrinsic optoelectronic properties of atomically thin TMDs where Ohmic contacts are necessary for achieving high efficiency devices with low power consumption.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Relationship between surface μ‐roughness and interface slurry particle spatial distribution during glass polishing

Abstract During optical glass polishing, a number of interactions between the workpiece (i.e., glass), polishing slurry, and pad can influence the resulting workpiece roughness at different spatial scale lengths. In our previous studies, the particle size distribution of the slurry, the pad topography, and the amount of material removed by a single particle on the workpiece were shown to strongly correlate with roughness at AFM scale lengths (nm‐μm) and weakly at μ‐roughness scale lengths (μm‐mm). In this study, the polishing slurry pH and the generation of glass removal products are shown to influence the slurry particle spatial and height distribution at the polishing interface and the resulting μ‐roughness of the glass workpiece. A series of fused silica and phosphate glass samples were polished with various ceria and colloidal silica slurries over a range of slurry pH , and the resulting AFM roughness and μ‐roughness were measured. The AFM roughness was largely invariant with pH , suggesting that the removal function of a single particle is unchanged with pH . However, the μ‐roughness changed significantly, increasing linearly with pH for phosphate glass and having a maximum at an intermediate pH for fused silica. In addition, the spatial and height distribution of slurry particles on the pad (as measured by laser confocal microscopy) was determined to be distinctly different at low and high pH during phosphate glass polishing. Also, the zeta potential as a function of pH was measured for the workpiece, slurry, and pad with and without surrogate glass products (K 3 PO 4 for phosphate glass and Si( OH ) 4 for silica) to assess the role of interfacial charge during polishing. The addition of K 3 PO 4 significantly raised the zeta potential, whereas addition of Si( OH ) 4 had little effect on the zeta potential. An electrostatic DLVO three‐body force model, using the measured zeta potentials, was used to calculate the particle–particle, particle–workpiece, and particle–pad attractive and repulsive forces as a function of pH and the incorporation of glass products at the interface. The model predicted an increase in particle–pad attraction with an increase in pH and phosphate glass products consistent with the measured slurry distribution on the pads during phosphate glass polishing. Finally, a slurry “island” distribution gap ( IDG ) model has been formulated which utilizes the measured interface slurry distributions and a load balance to determine the interface gap, the contact area fraction, and the load on each slurry “island”. The IDG model was then used to simulate the workpiece surface topography and μ‐roughness; the results show an increase in roughness with pH similar to that observed experimentally.

Suratwala, Tayyab↗
DOE OSTI2015

GIANT MOLECULAR CLOUDS IN THE EARLY-TYPE GALAXY NGC 4526

We present a high spatial resolution (≈20 pc) of {sup 12}CO(2 −1) observations of the lenticular galaxy NGC 4526. We identify 103 resolved giant molecular clouds (GMCs) and measure their properties: size R, velocity dispersion σ{sub v}, and luminosity L. This is the first GMC catalog of an early-type galaxy. We find that the GMC population in NGC 4526 is gravitationally bound, with a virial parameter α ∼ 1. The mass distribution, dN/dM ∝ M{sup −2.39±0.03}, is steeper than that for GMCs in the inner Milky Way, but comparable to that found in some late-type galaxies. We find no size–line width correlation for the NGC 4526 clouds, in contradiction to the expectation from Larson’s relation. In general, the GMCs in NGC 4526 are more luminous, denser, and have a higher velocity dispersion than equal-size GMCs in the Milky Way and other galaxies in the Local Group. These may be due to higher interstellar radiation field than in the Milky Way disk and weaker external pressure than in the Galactic center. In addition, a kinematic measurement of cloud rotation shows that the rotation is driven by the galactic shear. For the vast majority of the clouds, the rotational energy is less than the turbulent and gravitational energy, while the four innermost clouds are unbound and will likely be torn apart by the strong shear at the galactic center. We combine our data with the archival data of other galaxies to show that the surface density Σ of GMCs is not approximately constant, as previously believed, but varies by ∼3 orders of magnitude. We also show that the size and velocity dispersion of the GMC population across galaxies are related to the surface density, as expected from the gravitational and pressure equilibrium, i.e., σ{sub v} R{sup −1/2} ∝ Σ{sup 1/2}.

79 ASTRONOMY AND ASTROPHYSICS↗