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At least 955 records · Page 53

Tritium aspects of the fusion nuclear science facility

The Fusion Nuclear Science Facility (FNSF) is intended to bridge the technical gaps from ITER to DEMO, and provide a fully nuclear environment for the advancement of materials and blanket science, among other missions. Though smaller (~500 MW fusion power) than the envisioned DEMO, our FNSF design still seeks to test DEMO-relevant components and technologies, and to that end one of its goals is to achieve a tritium breeding ratio near one using a dual-cooled lead lithium (DCLL) blanket. We explore here the migration of bred tritium through in-vessel components and coolant loops, which is exacerbated by the relatively low solubility of tritium in PbLi and the high operating temperatures envisioned in later phases of operation. Some features inherent to the design of the DCLL help limit tritium losses, namely the relatively high PbLi flow rates; coupled with efficient tritium extraction, the DCLL potentially achieves low tritium permeation losses without the use of permeation barriers. We outline here the design of such an extraction system, and some of the materials challenges that must be met in order to realize it. The efficacy of these and other design features, such as coaxial piping, is demonstrated via a series of parameter studies. We also investigate the effect of parameter uncertainties, and find that the imprecise knowledge of the tritium solubility in PbLi in particular leads to very disparate estimates of tritium losses. Depending on the experimental value used, losses range from ~0.05 to over 6 grams of tritium per year. As a result, the former is acceptable based on estimated environmental releases and resultant dose to members of the public; the latter exceeds regulatory limits.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

SU-D-BRA-04: Computerized Framework for Marker-Less Localization of Anatomical Feature Points in Range Images Based On Differential Geometry Features for Image-Guided Radiation Therapy

Purpose: To propose a computerized framework for localization of anatomical feature points on the patient surface in infrared-ray based range images by using differential geometry (curvature) features. Methods: The general concept was to reconstruct the patient surface by using a mathematical modeling technique for the computation of differential geometry features that characterize the local shapes of the patient surfaces. A region of interest (ROI) was firstly extracted based on a template matching technique applied on amplitude (grayscale) images. The extracted ROI was preprocessed for reducing temporal and spatial noises by using Kalman and bilateral filters, respectively. Next, a smooth patient surface was reconstructed by using a non-uniform rational basis spline (NURBS) model. Finally, differential geometry features, i.e. the shape index and curvedness features were computed for localizing the anatomical feature points. The proposed framework was trained for optimizing shape index and curvedness thresholds and tested on range images of an anthropomorphic head phantom. The range images were acquired by an infrared ray-based time-of-flight (TOF) camera. The localization accuracy was evaluated by measuring the mean of minimum Euclidean distances (MMED) between reference (ground truth) points and the feature points localized by the proposed framework. The evaluation was performed for points localized on convex regions (e.g. apex of nose) and concave regions (e.g. nasofacial sulcus). Results: The proposed framework has localized anatomical feature points on convex and concave anatomical landmarks with MMEDs of 1.91±0.50 mm and 3.70±0.92 mm, respectively. A statistically significant difference was obtained between the feature points on the convex and concave regions (P<0.001). Conclusion: Our study has shown the feasibility of differential geometry features for localization of anatomical feature points on the patient surface in range images. The proposed framework might be useful for tasks involving feature-based image registration in range-image guided radiation therapy.

60 APPLIED LIFE SCIENCES↗

Controlling the intermediate structure of an ionic liquid for f-block element separations

Recent research has revealed molecular structure beyond the inner coordination sphere is essential in defining the performance of separations processes, but nevertheless remains largely unexplored. Here we apply small angle neutron scattering (SANS) and x-ray absorption fine structure (XAFS) spectroscopy to investigate the structure of an ionic liquid system studied for f-block element separations. SANS data reveal dramatic changes in the ionic liquid microstructure (~150 Å) which we demonstrate can be controlled by judicious selection of counter ion. Mesoscale structural features (> 500 Å) are also observed as a function of metal concentration. XAFS analysis supports formation of extended aggregate structures, similar to those observed in traditional solvent extraction processes, and suggest additional parallels may be drawn from further study. As a result, achieving precise tunability over the intermediate features is an important development in controlling mesoscale structure and realizing advanced new forms of soft matter.

36 MATERIALS SCIENCE↗

Off-equilibrium sphaleron transitions in the Glasma

We perform the first, to our knowledge, classical-statistical real time lattice simulations of topological transitions in the nonequilibrium glasma of weakly coupled but highly occupied gauge fields created immediately after the collision of ultrarelativistic nuclei. Simplifying our description by employing SU(2) gauge fields, and neglecting their longitudinal expansion, we find that the rate of topological transitions is initially strongly enhanced relative to the thermal sphaleron transition rate and decays with time during the thermalization process. Qualitative features of the time dependence of this nonequilibrium transition rate can be understood when expressed in terms of the magnetic screening length, which we also extract nonperturbatively. Furthermore, a detailed investigation of auto-correlation functions of the Chern-Simons number (N CS ) reveals non-Markovian features of the evolution distinct from previous simulations of non-Abelian plasmas in thermal equilibrium.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Data for FUN-PROSE: A Deep Learning Approach to Predict Condition-Specific Gene Expression in Fungi

mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE—a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.

Genomics↗

Extending a Tandem Mass Spectral Library to Include MS{sup 2} Spectra of Fragment Ions Produced In-Source and MS{sup n} Spectra

Tandem mass spectral library searching is finding increased use as an effective means of determining chemical identity in mass spectrometry-based omics studies. We previously reported on constructing a tandem mass spectral library that includes spectra for multiple precursor ions for each analyte. Here we report our method for expanding this library to include MS{sup 2} spectra of fragment ions generated during the ionization process (in-source fragment ions) as well as MS{sup 3} and MS{sup 4} spectra. These can assist the chemical identification process. A simple density-based clustering algorithm was used to cluster all significant precursor ions from MS{sup 1} scans for an analyte acquired during an infusion experiment. The MS{sup 2} spectra associated with these precursor ions were grouped into the same precursor clusters. Subsequently, a new top-down hierarchical divisive clustering algorithm was developed for clustering the spectra from fragmentation of ions in each precursor cluster, including the MS{sup 2} spectra of the original precursors and of the in-source fragments as well as the MS{sup n} spectra. This algorithm starts with all the spectra of one precursor in one cluster and then separates them into sub-clusters of similar spectra based on the fragment patterns. Herein, we describe the algorithms and spectral evaluation methods for extending the library. The new library features were demonstrated by searching the high resolution spectra of E. coli extracts against the extended library, allowing identification of compounds and their in-source fragment ions in a manner that was not possible before. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Transverse momentum structure of proton within the basis light-front quantization framework

We obtain the leading-twist valence quark transverse-momentum-dependent parton distribution functions (TMD PDFs) for the proton within the basis light-front quantization (BLFQ) framework. Our results are consistent with lattice QCD calculations and our previous results for the collinear limit. We also obtain consistency with the Soffer-type bounds. Within our approach, we find that six T-even TMDs in the leading twist are all independent of each other, and previously found model-dependent relations do not hold. This is a promising sign that our results are representative of future, more extensive treatments of QCD. Furthermore, we obtain a non-trivial x-dependence of the <(p ⊥ ) 2 > and some consistency with the Gaussian ansatz but only in the small <(p ⊥ ) 2 > region. Those features suggest our results may be a useful alternative in future experimental extractions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Ion Pairing and Molecular Orientation at Liquid/Liquid Interfaces: Self-Assembly and Function

We report that molecular orientation plays a pivotal role in defining the functionality and chemistry of interfaces, yet accurate measurements probing this important feature are few, due, in part, to technical and analytical limitations in extracting information from molecular monolayers. For example, buried liquid/liquid interfaces, where a complex and poorly understood balance of inter- and intramolecular interactions impart structural constraints that facilitate the formation of supramolecular assemblies capable of new functions, are difficult to probe experimentally. Here, we use vibrational sum-frequency generation spectroscopy, numerical polarization analysis, and atomistic molecular dynamics simulations to probe molecular orientations at buried oil/aqueous interfaces decorated with amphiphilic oligomers. We show that the orientation of self-assembled oligomers changes upon the addition of salts in the aqueous phase. The evolution of these structures can be described by competitive ion effects in the aqueous phase altering the orientations of the tails extending into the oil phase. These specific anionic effects occur via interfacial ion pairing and associated changes in interfacial solvation and hydrogen-bonding networks. These findings provide more quantitative insight into orientational changes encountered during self-assembly and pave the way for the design of functional interfaces for chemical separations, neuromorphic computing applications, and related biomimetic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Forecasting Battery Electrode Performance via Electrochemical Fluorescence Microscopy and Machine-Learning

Predicting lithium-ion battery performance is hindered by microscale electrode heterogeneities invisible to conventional diagnostics. Here, we combine electrochemical fluorescence microscopy (EFM), which maps electronic connectivity by visualizing an electrofluorophore reaction distribution, with a multitask ElasticNet regression to forecast discharge capacity from spatial heterogeneity. Analyzing 196 images from six pilot-scale LiNi 0.5 Mn 0.3 Co 0.2 O 2 cathodes with varying carbon loadings, we extract 62 descriptors that capture morphology and texture. A compact five-feature model predicts capacity across eight discharge rates, achieving a per-target R 2 of up to 0.63 and an overall R 2 of 0.92, with a mean absolute percentage error of less than 2%. This performance rivals impedance-based approaches while avoiding their reliance on postformation data and incomplete electronic network information. Our facile and rapid, image-driven method may enable electrode quality control upstream of costly cell assembly to offer a transformative tool for data-driven battery research and manufacturing.

battery electrodes↗

Investigation of Liquid Cloud Microphysical Properties of Deep Convective Systems: 2. Parameterization of Raindrop Size Distribution and its Application for Convective Rain Estimation

The liquid cloud microphysical properties for stratiform rain (SR) have been investigated in Part 1 of this series. Since convective rain (CR) has characteristics in raindrop size distribution (DSD) and precipitation that are distinct from SR, we investigate the CR properties in this study by using 20 hr of CR samples collected by 17 Automatic Parsivel Units disdrometers during the Midlatitude Continental Convective Clouds Experiment over the Atmospheric Radiation Measurement Southern Great Plains site. A full spectrum of DSD is constructed based on a total of 23 size channels (0.321 to 9.785 mm), and both Gamma and Exponential fitted functions are applied to extract the DSD shape parameters. Compared to SR properties, CR has distinct features including broader size range and narrower exponential slope parameter (λ E ). These results indicate that the assumption of constant exponential intercept parameter ( N 0E ) is inappropriate for CR rain rate estimates. Additionally, the subsetting scheme of the CR DSD spectra also has a strong impact on the Gamma/Exponential functions. Therefore, a new CR DSD parameterization scheme is developed by choosing the appropriate spectra subset with the constraint of rain rate and using the constant λ E instead of constant N 0E . With the input of the radar reflectivity at the lowest observed height, the newly calculated CR rain rates match well with the collocated surface rain gauge measurements (127 Mesonet stations and 17 Automatic Parsivel Units), while the rain rates calculated using traditional Z-R relationship are 3–4 times larger, indicating that constant λ E is a better assumption for CR DSD.

58 GEOSCIENCES↗

Synthesis and characterization of low viscosity hexafluoroacetylacetonate-based hydrophobic magnetic ionic liquids

Magnetic ionic liquids (MILs) are distinguished from traditional ionic liquids (ILs) by the incorporation of a paramagnetic component within their chemical structure. Hydrophobic MILs are novel solvents that can be used in many applications, including liquid–liquid extraction (LLE) and catalysis. Low viscosity and low water solubility are essential features that determine their feasibility in LLE. Here, we synthesized extremely hydrophobic MILs by using transition and rare earth metal hexafluoroacetylacetonate chelated anions paired with the trihexyl(tetradecyl)phosphonium ([P 66614 + ]) cation. Hydrophobic MILs exhibiting water solubilities less than 0.01% (v/v) were synthesized in a rapid two-step procedure. Furthermore, the viscosities of the MILs are among some of the lowest ever reported for hydrophobic MILs (276.5–927.9 centipoise (cP) at 23.7 °C) dramatically improving the ease of handling these liquids. For the first time, the magnetic properties of MILs possessing hexafluoroacetylacetonate chelated metal anions synthesized in this study are reported using a superconducting quantum interference device (SQUID) magnetometer. We also achieved an effective magnetic moments (μ eff ) as high as 9.7 and 7.7 Bohr magnetons (μ B ) by incorporating high spin dysprosium and gadolinium ions, respectively, into the anion component of the MIL. The low viscosity, high hydrophobicity, and large magnetic susceptibility of these MILs make them highly attractive and promising solvents for separations and purification, liquid electrochromic materials, catalytic studies, as well as microfluidic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The strain capacitor: A novel energy storage device

A novel electromechanical energy storage device is reported that has the potential to have high energy densities. It can efficiently store both mechanical strain energy and electrical energy in the form of an electric field between the electrodes of a strain-mismatched bilayer capacitor. When the charged device is discharged, both the electrical and mechanical energy are extracted in an electrical form. The charge-voltage profile of the device is suitable for energy storage applications since a larger portion of the stored energy can be extracted at higher voltage levels compared to a normal capacitor. Its unique features include the potential for long lifetime, safety, portability, wide operating temperature range, and environment friendliness. The device can be designed to operate over varied operating voltage ranges by selecting appropriate materials and by changing the dimensions of the device. In this paper a finite element model of the device is developed to verify and demonstrate the potential of the device as an energy storage element. This device has the potential to replace conventional energy storage devices.

36 MATERIALS SCIENCE↗

Evidence for thermal x-ray line emission from the synchrotron-dominated supernova remnant RX J1713.7-3946

We report the first detection of thermal X-ray line emission from the supernova remnant (SNR) RX J1713.7-3946, the prototype of the small class of synchrotron-dominated SNRs. A softness-ratio map generated using XMM-Newton data shows that faint interior regions are softer than bright shell regions. Using Suzaku and deep XMM-Newton observations, we have extracted X-ray spectra from the softest area, finding clear line features at E{sub ph}∼ 1 and ∼1.35 keV. These lines can be best explained as Ne Lyα and Mg Heα from a thermal emission component. Since the abundance ratios of metals to Fe are much higher than solar values in the thermal component, we attribute the thermal emission to reverse-shocked SN ejecta. The measured Mg/Ne, Si/Ne, and Fe/Ne ratios of 2.0–2.6, 1.5–2.0, and <0.05 solar suggest that the progenitor star of RX J1713.7-3946 was a relatively low-mass star (≲20 M{sub ⊙}), consistent with a previous inference based on the effect of stellar winds of the progenitor star on the surrounding medium. Since the mean blastwave speed of ∼6000 km s{sup −1} (the radius of 9.6 pc divided by the age of 1600 years) is relatively fast compared with other core-collapse SNRs, we propose that RX J1713.7-3946 is a result of an SN Ib/c whose progenitor was a member of an interacting binary. While our analysis provides strong evidence for X-ray line emission, our interpretation of its nature as thermal emission from SN ejecta requires further confirmation especially through future precision spectroscopic measurements using ASTRO-H.

79 ASTRONOMY AND ASTROPHYSICS↗

Geometric and dynamic distortions in anisotropic galaxy clustering

We examine the signature of dynamic (redshift-space) distortions and geometric distortions (including the Alcock-Paczynski effect) in the context of the galaxy power spectrum measured in upcoming galaxy redshift surveys. Information comes from both the baryon acoustic oscillation (BAO) feature and the broadband power spectrum shape. Accurate modeling is required to extract this information without systematically biasing the result. We consider an analytic model for the power spectrum of dark matter halos in redshift space, based on the distribution function expansion, and compare with halo clustering measured in N-body simulations. We forecast that the distribution function model is sufficiently accurate to allow the inclusion of broadband information on scales down to k ∼ 0.2h Mpc{sup −1}, with somewhat better accuracy for higher bias halos. Compared with a BAO-only analysis with reconstruction, including broadband shape information can improve unbiased constraints on distance measures H(z) and D{sub A}(z) by ∼ 30% and 20%, respectively, for a galaxy sample similar to the DESI luminous red galaxies. The gains in precision are larger in the absence of BAO reconstruction. Furthermore, including broadband shape information allows the measurement of structure growth, through redshift-space distortions. For the same galaxy sample, the distribution function model is able to constrain fσ{sub 8} to ∼ 2%, when simultaneously fitting for H(z) and D{sub A}(z). We discuss techniques to optimize the analysis of the power spectrum, including removing modes near the line-of-sight that are particularly challenging to model, and whether these approaches can improve parameter constraints. We find that such techniques are unlikely to significantly improve constraints on geometry, although they may allow higher precision measurements of redshift-space distortions.

79 ASTRONOMY AND ASTROPHYSICS↗

Dynamics of charge clouds ejected from laser-induced warm dense gold nanofilms

We report the first systematic study of the ejected charge dynamics surrounding laser-produced 30-nm warm dense gold films using single-shot femtosecond electron shadow imaging and deflectometry. The results reveal a two-step dynamical process of the ejected electrons under the high pump fluence conditions: an initial emission and accumulation of a large amount of electrons near the pumped surface region followed by the formation of hemispherical clouds of electrons on both sides of the film, which are escaping into the vacuum at a nearly isotropic and constant velocity with an unusually high kinetic energy of more than 300 eV. We also developed a model of the escaping charge distribution that not only reproduces the main features of the observed charge expansion dynamics but also allows us to extract the number of ejected electrons remaining in the cloud.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Search for new phenomena in a lepton plus high jet multiplicity final state with the ATLAS experiment using s = 13 Tev proton-proton collision data

CERN-LHC. A search for new phenomena in final states characterized by high jet multiplicity, an isolated lepton (electron or muon) and either zero or at least three b-tagged jets is presented. The search uses 36.1 fb-1 of sqrt(s) = 13 TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider in 2015 and 2016. The dominant sources of background are estimated using parameterized extrapolations, based on observables at medium jet multiplicity, to predict the b-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. No significant excess over the Standard Model expectation is observed and 95% confidence-level limits are extracted constraining four simplified models of R-parity-violating supersymmetry that feature either gluino or top-squark pair production. The exclusion limits reach as high as 2.1 TeV in gluino mass and 1.2 TeV in top-squark mass in the models considered. In addition, an upper limit is set on the cross-section for Standard Model tttt production of 60 fb (6.5 times the Standard Model prediction) at 95% confidence level. Finally, model-independent limits are set on the contribution from new phenomena to the signal-region yields.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Design of imaginary transition gamma booster synchrotron for the Jefferson Lab EIC (JLEIC)

Baseline design of the JLEIC booster synchrotron is presented. Its aim is to inject and accumulate heavy ions and protons at 285 MeV, to accelerate them to about 7 GeV, and finally to extract the beam into the ion collider ring. The Figure-8 ring features two 2600 achromatic arcs configured with negative momentum compaction optics, designed to avoid transition crossing for all ion species during the course of acceleration. The lattice also features a specialized high dispersion injection insert optimized to facilitate the transverse phase-space painting in both planes for multi-turn ion injection. Furthermore, the lattice has been optimized to ease chromaticity correction with two families of sextupoles in each plane. The booster ring is configured with super-ferric, 3 Tesla bends. We are presently launching optimization of the booster synchrotron design to operate in the extreme space-charge dominated regime.

Bogacz, Alex↗

RivGraph: Automatic extraction and analysis of river and delta channel network topology

River networks sustain life and landscapes by carrying and distributing water, sediment, and nutrients throughout ecosystems and communities. At the largest scale, river networks drain continents through tree-like tributary networks. At typically smaller scales, river deltas and braided rivers form loopy, complex distributary river networks via avulsions and bifurcations.In order to model flows through these networks or analyze network structure, the topology, or connectivity, of the network must be resolved. Additionally, morphologic properties of each river channel as well as the direction of flow through the channel inform how fluxes travel through the network’s channels. Riv Graphis a Python package that automates the extraction and characterization of river channel networks from a user-provided binary image, or mask, of a channel network (Fig. 1). Masks may be derived from (typically remotely-sensed) imagery, simulations, or even hand-drawn. RivGraph will create explicit representations of the channel network by resolving river centerlines as links, and junctions as nodes. Flow directions are solved for each link of the network without using auxiliary data, e.g., a digital elevation model (DEM). Morphologic properties are computed as well, including link lengths, widths, sinuosities, branching angles,and braiding indices. If provided,RivGraph will preserve georeferencing information of the mask and will export results as ESRI shapefiles, GeoJSONs, and GeoTIFFs for easy import into GIS software.RivGraph can also return extracted networks as networkx objects for convenient interfacing with the full-featured networkx package (Hagberg et al., 2008). Finally, RivGraph offers a suite of topologic metrics that were specifically designed for river channel network analysis (Tejedor et al., 2015b).

54 ENVIRONMENTAL SCIENCES↗