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At least 703 records · Page 39

Effect of ion sputtering on interface chemistry and electrical properties of Au GaAs(100) Schottky contacts

The effects of sputtering n-type (100)GaAs with 1 to 5 keV argon ions have been studied in ultrahigh vacuum. Auger electron and X-ray photoelectron spectroscopies have been used to characterize the surface before and after sputtering. Gold Schottky contacts were prepared in situ to avoid contamination at the metal/semiconductor interface. The data show that sputtering depletes the surface in As, and the extent of depletion increased as the ion energy was increased. However, angular-resolved photoelectron data showed As was enriched on the outer atom layer by 5 keV but depleted by 1 keV Ar(+) sputtering. Current and capacitance versus voltage data showed that sputtering always lowered the Schottky barrier height and generally increased the ideality factor. However, the barrier height after 3 keV sputtering was higher than after 1 keV sputtering. Those effects are explained based on a combined effective work function model and creation of a donorlike surface damage layer. The donor layer was correlated with As depletion by sputtering. Deep level trap formation and annealing of sputtering effects were studied.

Wang, Y.-X.↗

Laboratory studies of fast oxygen atom interactions with materials

A pulsed 8 km/s oxygen atom source was used to perform a number of measurements of material interactions of interest to low Earth orbit applications. A system to measure the scattering distribution resulting from 8 km/s oxygen atoms impinging on selected spacecraft materials was developed. Data for scattering from glass and black and clear anodized aluminum are presented. Results on the fast atom oxidation mechanism for thin silver films, the O-atom velocity dependent erosion rates for selected materials, and the oxidation dependence on material temperature are presented.

Caledonia, George E.↗

High-Resolution N-Band Observations of the Nova RS Ophiuchi with the Keck Interferometer Nuller

We report new observations of the nova RS Ophiuchi (RS Oph) using the Keck Interferometer Nulling Instrument, approximately 3.8 days following the most recent outburst that occurred on 2006 February 12. The Keck Interferometer Nuller (KIN) operates in K-band from 8 to 12.5 pm in a nulling mode, which means that the central broad-band interference fringe is a dark fringe - with an angular width of 25 mas at mid band - rather than the bright fringe used ill a conventional optical interferometer. In this mode the stellar light itself is suppressed by the destructive fringe, effectively enhancing the contrast of the circumstellar material located near the star. By subsequently shifting the neighboring bright fringe onto the center of the source brightness distribution and integrating, a second spatial regime dominated by light from the central portion of the source is almost simultaneously sampled. The nulling technique is the sparse aperture equivalent of the conventional corongraphic technique used in filled aperture telescopes. By fitting the unique KIK inner and outer spatial regime data, we have obtained an angular size of the mid-infrared continuum of 6.2, 4.0. or 5.4 mas for a disk profile, gaussian profile (fwhm), and shell profile respectively. The data show evidence of enhanced neutral atomic hydrogen emission located in the inner spatial regime relative to the outer regime. There is also evidence of a 9.7 micron silicate feature seen outside of this region. Importantly, we see spectral lines excited by the nova flash in the outer region before the blast wave reaches these regions. These lines are from neutral, weakly excited atoms which support the following interpretation. We discuss the present results in terms of a unifying model of the system that includes an increase in density in the plane of the orbit of the two stars created by a spiral shock wave caused by the motion of the stars through the cool wind of the red giant star. These data show the power and potential of the nulling technique which has been developed for the detection of Earth-like planets around nearby stars for the Terrestrial Planet Finder Mission and Darwin missions.

Barry, R. K.↗

Universally Accessible Structural Data on Macromolecular Conformation, Assembly, and Dynamics by Small Angle X-Ray Scattering for DNA Repair Insights.

Structures provide a critical breakthrough step for biological analyses, and small angle X-ray scattering (SAXS) is a powerful structural technique to study dynamic DNA repair proteins. As toxic and mutagenic repair intermediates need to be prevented from inadvertently harming the cell, DNA repair proteins often chaperone these intermediates through dynamic conformations, coordinated assemblies, and allosteric regulation. By measuring structural conformations in solution for both proteins, DNA, RNA, and their complexes, SAXS provides insight into initial DNA damage recognition, mechanisms for validation of their substrate, and pathway regulation. Here, we describe exemplary SAXS analyses of a DNA damage response protein spanning from what can be derived directly from the data to obtaining super resolution through the use of SAXS selection of atomic models. We outline strategies and tactics for practical SAXS data collection and analysis. Making these structural experiments in reach of any basic and clinical researchers who have protein, SAXS data can readily be collected at government-funded synchrotrons, typically at no cost for academic researchers. In addition to discussing how SAXS complements and enhances cryo-electron microscopy, X-ray crystallography, NMR, and computational modeling, we furthermore discuss taking advantage of recent advances in protein structure prediction in combination with SAXS analysis.

Chinnam, Naga Babu↗

Solar wind and micrometeorite alteration of the lunar regolith

Developments in the understanding of reduction processes which occur in the lunar regolith as a result of solar-wind bombardment and micrometeorite impacts are discussed. The mechanism is described by which water released during reduction is removed from the lunar surface, and the possible contribution of solar-wind sputtering to the reduction process is considered. It is shown that the overall reduction efficiency of incoming hydrogen ions may reach several per cent, which is sufficient to produce all the metallic iron observed in the regolith. Mossbauer spectroscopic data on the amount of metallic iron present as isolated atoms or small clusters in reduced grain surfaces are presented together with data on the metallic iron content of fines samples obtained by Mossbauer spectroscopy, ferromagnetic resonance, and scanning as well as transmission electron microscopy. A portable magnetic probe is described which has been designed for determining surface-exposure age profiles in intact lunar core and drive-tube samples.

Housley, R. M.↗

Search for topological defect dark matter with a global network of optical magnetometers

Ultralight bosons such as axion-like particles are viable candidates for dark matter. They can form stable, macroscopic field configurations in the form of topological defects that could concentrate the dark matter density into many distinct, compact spatial regions that are small compared with the Galaxy but much larger than the Earth. Here we report the results of the search for transient signals from the domain walls of axion-like particles by using the global network of optical magnetometers for exotic (GNOME) physics searches. We search the data, consisting of correlated measurements from optical atomic magnetometers located in laboratories all over the world, for patterns of signals propagating through the network consistent with domain walls. The analysis of these data from a continuous month-long operation of GNOME finds no statistically significant signals, thus placing experimental constraints on such dark matter scenarios.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Heterogeneity and Chemical Reactivity of the Remote Troposphere Defined By Aircraft Measurements - Corrected

The NASA Atmospheric Tomography (ATom) mission built a photochemical climatology of air parcels based on in situ measurements with the NASA DC-8 aircraft along objectively planned profiling transects through the middle of the Pacific and Atlantic oceans. In this paper we present and analyze a data set of 10 s (2 km) merged and gap-filled observations of the key reactive species driving the chemical budgets of O3 and CH4 (O3, CH4, CO, H2O, HCHO, H2O2, CH3OOH, C2H6, higher alkanes, alkenes, aromatics, NOx, HNO3, HNO4, peroxyacetyl nitrate, and other organic nitrates), consisting of 146 494 distinct air parcels from ATom deployments 1 through 4. Six models calculated the O3 and CH4 photochemical tendencies from this modeling data stream for ATom 1. We find that 80 %–90 % of the total reactivity lies in the top 50 % of the parcels and 25 %–35 % in the top 10 %, supporting previous model-only studies that tropospheric chemistry is driven by a fraction of all the air. Surprisingly, the probability densities of species and reactivities averaged on a model scale (100 km) differ only slightly from the 2 km ATom 10 s data, indicating that much of the heterogeneity in tropospheric chemistry can be captured with current global chemistry models. Comparing the ATom reactivities over the tropical oceans with climatological statistics from six global chemistry models, we find generally good agreement with the reactivity rates for O3 and CH4. Models distinctly underestimate O3 production below 2 km relative to the mid-troposphere, and this can be traced to lower NOx levels than observed. Attaching photochemical reactivities to measurements of chemical species allows for a richer, yet more constrained-to-what-matters, set of metrics for model evaluation.

Tropospheric Chemistry↗

Characterization of the atomic-level structure of γ-alumina and (111) Pt/γ-alumina interfaces

The atomic-level structure of platinum/γ-alumina interfaces is characterized in a model system of dense γ-alumina embedded with faceted Pt NPs produced by implantation of platinum ions into sapphire followed by thermal annealing in air at 800 °C. Aberration-corrected scanning transmission electron microscopy (STEM) was used to collect atomic-resolution images, which are compared to STEM image simulations of two experimentally-based bulk models of γ-alumina by Smrčok et al. and Zhou and Snyder. A density functional theory (DFT) based model of (111) interfaces with different chemical terminations (O, Al 1 , Al 2 ) of the γ-alumina developed by Oware Sarfo et al. is also compared to experimental STEM data from Pt/γ-alumina interfaces. Further, the Smrčok γ-alumina model provides a better fit than the Zhou structure to the bulk of the γ-alumina. The oxygen-terminated Oware Sarfo model best fits the experimental data and is a very good model close to the interface. However, the fit of the interface model to the experimental data is poorer beyond the third atomic layer in the γ-alumina. This is attributed to compromises required in the design of the model to limit the cell size and computational time for DFT calculations. Understanding the accuracy and limits of the structural models of γ-alumina and Pt/γ-alumina interfaces is important to further the understanding of the structure/property relationships in this system.

36 MATERIALS SCIENCE↗

Leveraging 13C-Labeling to Assign Molecular Formulas to Unknown Yeast Metabolites

Mass spectrometry analyses have identified tens of thousands of unknown small molecule-associated peaks in different biological specimens. Notably, even the simplest and best studied organisms like Escherichia coli and Saccharomyces cerevisiae yield thousands of unknown peaks. A key question is how many of these reflect actual novel endogenous metabolites. To explore this, Mahieu and Patti used complete 13 C -labeling in E. coli to credential peaks as biological. This reduced the number of unknowns by more than 90%. Here, we carry out similar uniform 13 C-labeling in the Baker’s yeast S. cerevisiae and two less-studied bioenergy-relevant yeasts Rhodotorula toruloides (lipid producer) and Issatchenkia orientalis (organic acid producer). Identification of unknown metabolite peaks and their molecular formulas is facilitated through software tailored for 13 C labeling data and resulting knowledge of carbon atom count. A classification model evaluates the plausibility of each candidate formula, with peaks lacking plausible candidate formulas unlikely to reflect metabolite molecular ions. This approach prioritizes about one hundred candidate abundant unknown metabolites with logical molecular formulas. Most of these are species-specific rather than conserved across yeasts, and more are found in the nonmodel yeasts than S. cerevisiae. Thus, 13 C-labeling data on unknown metabolites highlights the potential for discovering new metabolites and pathways in nonmodel yeasts.

Carbon↗

H2 recombination on interstellar grains

From a consideration of relevant theoretical and experimental data it is concluded that H atoms (but not H2 molecules) will be chemisorbed on interstellar graphite grains, with H2 formation proceeding efficiently for graphite grain temperatures less than 70 K. It is argued that graphite grains will act as the principal sites for H2 formation, with a formation rate of about 4 to the minus 17th cu cm per sec. Heating by H2 molecules formed by surface recombination is analyzed in the context of the available experimental data, and a heating rate is derived and compared with other suggested cloud heating mechanisms. It is concluded that H2 recombination will provide the largest heat source in diffuse clouds if the albedo of interstellar dust in the 912-1200 A region is high (about 0.9), whereas if the albedo in this wavelength region is lower (about 0.5), photoelectron ejection from grains will tend to predominate, and can explain observed cloud temperatures with a carbon depletion factor of approximately 2, a factor attributable to a normal interstellar abundance of graphite grains.

Barlow, M. J.↗

Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules

Abstract Graph Convolutional Neural Network (GCNN) is a popular class of deep learning (DL) models in material science to predict material properties from the graph representation of molecular structures. Training an accurate and comprehensive GCNN surrogate for molecular design requires large-scale graph datasets and is usually a time-consuming process. Recent advances in GPUs and distributed computing open a path to reduce the computational cost for GCNN training effectively. However, efficient utilization of high performance computing (HPC) resources for training requires simultaneously optimizing large-scale data management and scalable stochastic batched optimization techniques. In this work, we focus on building GCNN models on HPC systems to predict material properties of millions of molecules. We use HydraGNN, our in-house library for large-scale GCNN training, leveraging distributed data parallelism in PyTorch. We use ADIOS, a high-performance data management framework for efficient storage and reading of large molecular graph data. We perform parallel training on two open-source large-scale graph datasets to build a GCNN predictor for an important quantum property known as the HOMO-LUMO gap. We measure the scalability, accuracy, and convergence of our approach on two DOE supercomputers: the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF) and the Perlmutter system at the National Energy Research Scientific Computing Center (NERSC). We present our experimental results with HydraGNN showing (i) reduction of data loading time up to 4.2 times compared with a conventional method and (ii) linear scaling performance for training up to 1024 GPUs on both Summit and Perlmutter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Warm neutral halos around molecular clouds. III - Interpretation of H I and CO J = 1-0 data

The physical characteristics of the transition region separating the molecular and the atomic medium in interstellar clouds are studied using H I 21-cm and CO J = 1-0 data. Strong evidence is found for general heating of the surface layers of molecular clouds and for the existence of large heated neutral atomic halos around the molecular clouds. The heating of the molecular cloud surface is manifested through the general existence of limb brightening in the CO emission, with a characteristic depth of 1.7 pc, dependent on the Galactic latitude. The heated H I halos have a characteristic depth of 4.7 pc and a maximal extent of about 10 pc.

Andersson, B.-G.↗

Using Block-local Atomicity to Detect Stale-value Concurrency Errors

Data races do not cover all kinds of concurrency errors. This paper presents a data-flow-based technique to find stale-value errors, which are not found by low-level and high-level data race algorithms. Stale values denote copies of shared data where the copy is no longer synchronized. The algorithm to detect such values works as a consistency check that does not require any assumptions or annotations of the program. It has been implemented as a static analysis in JNuke. The analysis is sound and requires only a single execution trace if implemented as a run-time checking algorithm. Being based on an analysis of Java bytecode, it encompasses the full program semantics, including arbitrarily complex expressions. Related techniques are more complex and more prone to over-reporting.

Artho, Cyrille↗

Compatibility of seasonal variations in mid-latitude thermospheric models at solar maximum and low geomagnetic activity

Satellite drag data, in situ mass spectrometer data, Fabry Perot interferometer data, and incoherent scatter data were used to produce models of the concentration of atomic oxygen and molecular nitrogen in the thermosphere and of the exospheric temperature. Incoherent scatter data from two stations near 45 deg N were used. The three techniques provide similar patterns for the annual variations of the atomic oxygen concentration at 400 km, and the mean annual temperatures are within 20 K of each other for five of the six models involved. Four of the models are in good agreement concerning the annual temperature variation. There is fair agreement between incoherent scatter models and mass spectrometer models for the N2 concentrations at 400 km but disagreement between these models and the satellite drag model. It is shown that most disagreements can be resolved by changing both the vertical temperature profile and the lower-thermosphere oxygen concentration in the direction indicated by previous incoherent scatter measurements.

Alcayde, D.↗

Ionization induced damage in crystalline silicon

Close examination of the interaction of the energetic knock-on atoms with the local lattice environment reveals a damage mechanism which does satisfy the experimental data on proton irradiation of silicon. A proton-atom interaction with high energy transfer is considered where the proton path is delineated by a trail of ionization, and the silicon ion path is characterized by much heavier ionization terminating in a dense displacement cluster. At collision, many of the silicon electrons are stripped off, and the resulting energetic ion subsequently loses energy rapidly by Coulomb interaction with bound electrons. The rate of energy loss depends on the charge state and velocity of the knock-on ion. For ion energies in excess of 1 MeV, the intensity of ionization is sufficient to permit lattice atoms, stripped of their binding electrons, to reorient randomly before having an opportunity to recombine with electrons and re-establish the lattice. The path of a knock-on ion thus becomes a thin cylinder of amorphous material within the crystal. Amorphous silicon has a Fermi level closer to mid-band than does single crystal silicon, and a strong field therefore, results around this damaged region. The field produces a large depletion region, representing a very large capture cross section for minority carriers.

Meulenberg, A., Jr.↗

The reaction of N/2D/ with O2 as a source of O/1D/ atoms in aurorae

The source of O(1D) atoms in the auroral ionosphere is investigated using sounding rocket data. Previously, it has been shown that the conventional sources of O(1D) atoms in the aurora, dissociative recombination of O2(plus) and electron impact excitation of atomic oxygen, fail to explain the measured 6300 A volume emission rate profile. It is suggested that the atom-atom interchange reaction of N(2D) with O2 can be the major source of auroral 6300 A emission if O(1D) is created with high efficiency.

Rusch, D. W.↗

Ca X ML: Chemistry‐informed machine learning explains mutual changes between protein conformations and calcium ions in calcium‐binding proteins using structural and topological features

Proteins' flexibility is a feature in communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression. When binding with the disordered parts of a protein, calcium ions must balance their charge states with the shape of calcium-binding proteins and their versatile pool of partners depending on the circumstances they transmit. Accurately determining the ionic charges of those ions is essential for understanding their role in such processes. However, it is unclear whether the limited experimental data available can be effectively used to train models to accurately predict the charges of calcium-binding protein variants. Here, we developed a chemistry-informed, machine-learning algorithm that implements a game theoretic approach to explain the output of a machine-learning model without the prerequisite of an excessively large database for high-performance prediction of atomic charges. We used the ab initio electronic structure data representing calcium ions and the structures of the disordered segments of calcium-binding peptides with surrounding water molecules to train several explainable models. Network theory was used to extract the topological features of atomic interactions in the structurally complex data dictated by the coordination chemistry of a calcium ion, a potent indicator of its charge state in protein. Our design created a computational tool of Ca X ML, which provided a framework of explainable machine learning model to annotate ionic charges of calcium ions in calcium-binding proteins in response to the chemical changes in an environment. Our framework will provide new insights into protein design for engineering functionality based on the limited size of scientific data in a genome space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗