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At least 469 records · Page 26

Probing the solidification of quasicrystals via joint experiment and simulation (Final Report)

Quasicrystals (QCs) possess long-range positional order but non-crystallographic orientational order. Their classically ‘forbidden’ symmetry has long attracted the interest of scientists worldwide. Despite their frequent observation in both metal alloys and soft matter structures in the 35 years since their discovery, little is known about how QCs evolve from a liquid, amorphous, or crystalline precursor. In this project, we sought to resolve the enigma of QC self-assembly through a combined experimental and computational program. The Shahani group employed in situ electron and synchrotron X ray imaging to peer into the growth dynamics of QCs in a liquid, covering a broad range of length scales and solidification pathways. Glotzer's team developed new simulation models incorporating phasonic defects — which are unique to quasicrystals — and used this model to investigate two grains growing together, closely mimicking the experimental conditions. While QCs remain exceptional structures, most compounds in the realm of intermetallics adopt non-trivial geometries. In fact, only around 6% of phases are comprised of the simplest sphere packings that researchers so readily associate with metals. State-of-the-art knowledge of phase transformations at the outset of this collaborative project did not encompass the remaining 94% of intermetallic compounds that possess complex and aperiodic structure types. Therefore, we expect that outcomes from this project will have immediate and profound impact on synthesis and processing science: our efforts will be used to not only explain the growth dynamics of QCs but also complex intermetallics more broadly.

36 MATERIALS SCIENCE↗

Semi-inclusive wino and higgsino annihilation to LL'

Here, we systematically compute the annihilation rate for winos and higgsinos into the final state relevant for indirect detection experiments, γ + X. The radiative corrections to this process receive enhancement from the large Bloch-Nordsieck-Violating Sudakov logarithm, log(2M${\chi }$/M W ). We resum the double logs and include single logs to fixed order using a formalism that combines nonrelativistic and soft-collinear effective field theories. For the wino case, we update an earlier exclusion adapting results of the HESS experiment. At the thermal relic mass of 3 TeV, LL' corrections result in a ~30% reduction in rate relative to LL. But, single logs do not save the wino, and it is still excluded by an order of magnitude. Finally, experimental cuts produce an endpoint region which, our results show, significantly effects the higgsino rate at its thermal-relic mass near 1 TeV and is deserving of further study.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Two-Particle Correlation Function for Systems with Long-Range Interactions

In this paper, we study the truncated two-particle correlation function in particle systems with long range interactions. For Coulombian and soft potentials, we define and give well-posedness results for the equilibrium correlations. In the Coulombian case, we prove the onset of the Debye screening length in the equilibrium correlations, for suitable velocity distributions. Additionally, we give precise estimates on the effective range of interaction between particles. In the case of soft potential interaction the equilibrium correlations and their fluxes in the space of velocities are shown to be linearly stable.

97 MATHEMATICS AND COMPUTING↗

Self-organizing sensing and actuation for automatic control

A Self-Organizing Process Control Architecture is introduced with a Sensing Layer, Control Layer, Actuation Layer, Process Layer, as well as Self-Organizing Sensors (SOS) and Self-Organizing Actuators (SOA). A Self-Organizing Sensor for a process variable with one or multiple input variables is disclosed. An artificial neural network (ANN) based dynamic modeling mechanism as part of the Self-Organizing Sensor is described. As a case example, a Self-Organizing Soft-Sensor for CFB Boiler Bed Height is presented. Also provided is a method to develop a Self-Organizing Sensor.

97 MATHEMATICS AND COMPUTING↗

Validation for 2D/3D registration I: A new gold standard data set

Purpose: In this article, the authors propose a new gold standard data set for the validation of two-dimensional/three-dimensional (2D/3D) and 3D/3D image registration algorithms. Methods: A gold standard data set was produced using a fresh cadaver pig head with attached fiducial markers. The authors used several imaging modalities common in diagnostic imaging or radiotherapy, which include 64-slice computed tomography (CT), magnetic resonance imaging using Tl, T2, and proton density sequences, and cone beam CT imaging data. Radiographic data were acquired using kilovoltage and megavoltage imaging techniques. The image information reflects both anatomy and reliable fiducial marker information and improves over existing data sets by the level of anatomical detail, image data quality, and soft-tissue content. The markers on the 3D and 2D image data were segmented using ANALYZE 10.0 (AnalyzeDirect, Inc., Kansas City, KN) and an in-house software. Results: The projection distance errors and the expected target registration errors over all the image data sets were found to be less than 2.71 and 1.88 mm, respectively. Conclusions: The gold standard data set, obtained with state-of-the-art imaging technology, has the potential to improve the validation of 2D/3D and 3D/3D registration algorithms for image guided therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Compact 'diode-based' multi-energy soft x-ray diagnostic for NSTX

A novel and compact, diode-based, multi-energy soft x-ray (ME-SXR) diagnostic has been developed for the National Spherical Tokamak Experiment. The new edge ME-SXR system tested on NSTX consists of a set of vertically stacked diode arrays, each viewing the plasma tangentially through independent pinholes and filters providing an overlapping view of the plasma midplane which allows simultaneous SXR measurements with coarse sub-sampling of the x-ray spectrum. Using computed x-ray spectral emission data, combinations of filters can provide fast (>10 kHz) measurements of changes in the electron temperature and density profiles providing a method to 'fill-in' the gaps of the multi-point Thomson scattering system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Probing phonon softening in ferroelectrics by scanning probe microwave spectroscopy

Microwave measurements have recently been successfully applied to measure ferroelectric materials on the nanoscale, including detection of polarization switching and ferroelectric domain walls. In this study we discuss the question of whether scanning probe microscopy operating at microwave frequency can identify the changes associated with the soft phonon dynamics in a ferroic. The analytical expressions for the electric potential, complex impedance, and dielectric losses are derived and analyzed, since these physical quantities are linked to experimentally measurable properties of the ferroic. As a ferroic we consider virtual or proper ferroelectric with an optic phonon mode that softens at a Curie point. We also consider a decay mechanism linked to the conductance of the ferroic, thus manifesting itself as the dielectric loss in the material. Our key finding is that the influence of the soft phonon dispersion on the surface potential distribution, complex impedance, and dielectric losses are evidently strong in the vicinity (~10–30 K) of the Curie temperature. Additionally, we quantified how the spatial distribution and frequency spectra of the complex impedance and the dielectric losses react on the dynamics of the soft phonons near the Curie point. These results set the stage for characterization of polar phase transitions with nanoscale microwave measurements, providing a complementary approach to well established electromechanical measurements for fundamental understanding of ferroelectric properties as well as their applications in telecommunication and computing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Advanced Computational Framework for Environmental Management ZEM, Version 1.x

Typically environmental management problems require analysis of large and complex data sets originating from concurrent data streams with different data collection frequencies and pedigree. These big data sets require on-the-fly integration into a series of models with different complexity for various types of model analyses where the data are applied as soft and hard model constraints. This is needed to provide fast iterative model analyses based on the latest available data to guide decision-making. Furthermore, the data and model are associated with uncertainties. The uncertainties are probabilistic (e.g. measurement errors) and non-probabilistic (unknowns, e.g. alternative conceptual models characterizing site conditions). To address all of these issues, we have developed an integrated framework for real-time data and model analyses for environmental decision-making called ZEM. The framework allows for seamless and on-the-fly integration of data and modeling results for robust and scientifically-defensible decision-making applying advanced decision analyses tools such as Bayesian- Information-Gap Decision Theory (BIG-DT). The framework also includes advanced methods for optimization that are capable of dealing with a large number of unknown model parameters, and surrogate (reduced order) modeling capabilities based on support vector regression techniques. The framework is coded in Julia, a state-of-the-art high-performance programing language (http://julialang.org). The ZEM framework is open-source and can be applied to any environmental management site. The framework will be open-source and released under GPL V3 license.

Vesselinov, VelimirV.↗

Dosimetric Impact of Online Correction via Cone-Beam CT-Based Image Guidance for Stereotactic Lung Radiotherapy

Purpose: To evaluate the dosimetric impact of online cone-beam computed tomography (CBCT) guided correction in lung stereotactic body radiation therapy (SBRT). Methods and Materials: Twenty planning and 162 CBCT images from 20 patients undergoing lung SBRT were analyzed. The precorrection CBCT (CBCT after patient setup, no couch correction) was registered to planning CT using soft tissue; couch shift was applied, with a second CBCT for verification (postcorrection CBCT). Targets and normal structures were delineated on CBCTs: gross tumor volume (GTV), clinical target volume (CTV), cord, esophagus, lung, proximal bronchial tree, and aorta. Dose distributions on all organs manifested on each CBCT were compared with those planned on the CT. Results: Without CBCT guided target position correction, target dose reduced with respect to treatment plan. Mean and standard deviation of treatment dose discrepancy from the plan were -3.2% (4.9%), -2.1% (4.4%), -6.1% (10.7%), and -3.5% (7%) for GTV D{sub 99%}, GTV D{sub 95%}, CTV D{sub 99%}, and CTV D{sub 95%}, respectively. With CBCT correction, the results were -0.4% (2.6%), 0.1% (1.7%), -0.3% (4.2%), and 0.5% (3%). Mean and standard deviation of the difference in normal organ maximum dose were 2.2% (6.5%) before correction and 2.4% (5.9%) after correction for esophagus; 6.1% (14.1%) and 3.8% (8.1%) for cord; 3.1% (17.5%) and 6.2% (9.8%) for proximal bronchial tree; and 17.7% (19.5%) and 14.1% (17%) for aorta. Conclusion: Online CBCT guidance improves the accuracy of target dose delivery for lung SBRT. However, treatment dose to normal tissue can vary regardless of the correction. Normal tissues should be considered during target registration, according to target proximity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

MO-FG-CAMPUS-TeP2-01: A Graph Form ADMM Algorithm for Constrained Quadratic Radiation Treatment Planning

Purpose: In radiation therapy optimization the constraints can be either hard constraints which must be satisfied or soft constraints which are included but do not need to be satisfied exactly. Currently the voxel dose constraints are viewed as soft constraints and included as a part of the objective function and approximated as an unconstrained problem. However in some treatment planning cases the constraints should be specified as hard constraints and solved by constrained optimization. The goal of this work is to present a computation efficiency graph form alternating direction method of multipliers (ADMM) algorithm for constrained quadratic treatment planning optimization and compare it with several commonly used algorithms/toolbox. Method: ADMM can be viewed as an attempt to blend the benefits of dual decomposition and augmented Lagrangian methods for constrained optimization. Various proximal operators were first constructed as applicable to quadratic IMRT constrained optimization and the problem was formulated in a graph form of ADMM. A pre-iteration operation for the projection of a point to a graph was also proposed to further accelerate the computation. Result: The graph form ADMM algorithm was tested by the Common Optimization for Radiation Therapy (CORT) dataset including TG119, prostate, liver, and head & neck cases. Both unconstrained and constrained optimization problems were formulated for comparison purposes. All optimizations were solved by LBFGS, IPOPT, Matlab built-in toolbox, CVX (implementing SeDuMi) and Mosek solvers. For unconstrained optimization, it was found that LBFGS performs the best, and it was 3–5 times faster than graph form ADMM. However, for constrained optimization, graph form ADMM was 8 – 100 times faster than the other solvers. Conclusion: A graph form ADMM can be applied to constrained quadratic IMRT optimization. It is more computationally efficient than several other commercial and noncommercial optimizers and it also used significantly less computer memory.

60 APPLIED LIFE SCIENCES↗

Experimental Phase Functions of Millimeter-sized Cosmic Dust Grains

We present the experimental phase functions of three types of millimeter-sized dust grains consisting of enstatite, quartz, and volcanic material from Mount Etna, respectively. The three grains present similar sizes but different absorbing properties. The measurements are performed at 527 nm covering the scattering angle range from 3° to 170°. The measured phase functions show two well-defined regions: (i) soft forward peaks and (ii) a continuous increase with the scattering angle at side- and back-scattering regions. This behavior at side- and back-scattering regions is in agreement with the observed phase functions of the Fomalhaut and HR 4796A dust rings. Further computations and measurements (including polarization) for millimeter-sized grains are needed to draw some conclusions about the fluffy or compact structure of the dust grains.

79 ASTRONOMY AND ASTROPHYSICS↗

Electronic and Structural Properties of the Polymer-Electrolyte Interphase in Electrochemically Doped Polymers

The advance of soft, polymer-based (photo)electrochemical energy transformation and storage applications requires a framework for polymer and electrolyte design that includes a deep understanding of the polymer–electrolyte interphase. Here, we report on the investigations of two napthalenediimide (NDI)–bithiophene (T2)-based semiconducting copolymers using computational modeling and in situ, ex situ, and operando techniques to reveal how changes in electrolyte and polymer chemistry modulate the electronic and structural properties of polymer electrodes during electrochemical (de)doping. These systems are shown to host an ensemble of polarons, in contrast with the single polaron-like character often reported, whose properties vary with the nature of the local environment. Importantly, these polarons serve as reporters of the nanoscale environments in which they reside. We demonstrate that controlling the polymer and electrolyte chemistry regulates the nature of the charge carriers generated upon electrochemical doping and/or exciton dissociation in a photoelectrochemical solar cell: For instance, divalent counterions enable polaron and bipolaron formation at lower reducing potentials, while supporting more bipolaron formation than monovalent counterions. A novel application of NEXAFS reveals insights into charge (de)localization, providing a pathway for future investigation of electron transport mechanisms. Finally, simulations of polymer swelling of an amorphous interphase show that charge formation has a large impact on polymer swelling and ion penetration. These studies deliver insights to enable the control of charge-carrier and ion transport, the rates of electron transfer and catalytic efficiency, device stability, and overall device performance.

14 SOLAR ENERGY↗

Using Machine Learning and Data Analysis to Improve Customer Acquisition and Marketing in Residential Solar

High customer acquisition costs remain a persistent challenge in the U.S. residential solar industry. Effective customer acquisition in the residential solar market is increasingly achieved with the help of data analysis and machine learning, whether that means more targeted advertising, understanding customer motivations, or responding to competitors. New research by the National Renewable Energy Laboratory, Sandia National Laboratories, Vanderbilt University, University of Pennsylvania, and the California Center for Sustainable Energy and funded through the U.S. Department of Energy's Solar Energy Evolution and Diffusion (SEEDS) program demonstrates novel computational methods that can help drive down costs in the residential solar industry.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Non-cardiac uptake of technetium-99m pyrophosphate in transthyretin cardiac amyloidosis

Background: Technetium-based bone scintigraphy is rapidly becoming the most common non-invasive imaging tool in the diagnosis of Transthyretin cardiac amyloidosis (ATTR). Skeletal muscle uptake has been described with technetium-99m-3,3-diphosphono-1,2-propanodicarboxylic acid (TcDPD), and may account for masking of bony uptake. We sought to investigate skeletal muscle uptake of technetium-99m-pyrophosphate (TcPYP) in patients with ATTR. Methods and Results: This was a retrospective analysis of 57 patients diagnosed with ATTR who underwent TcPYP scintigraphy. Cardiac uptake was assessed on whole-body planar imaging using a semiquantitative scale (grades 0 to 3) and on single-photon emission computed tomography (SPECT) with CT attenuation correction using total myocardial counts per voxel after a 3-hour incubation. Skeletal muscle (psoas and biceps), vertebral body, LV myocardium, and blood pool mean counts were calculated. In the cohort (age 78 ± 9 years, 77% male, and 30% hereditary ATTR), there was no visualized tracer uptake in skeletal muscle or soft tissue on qualitative SPECT assessment. Total and blood pool-corrected uptake in the muscle groups were significantly less than myocardium and bone (P < 0.001). Blood pool-corrected muscle uptake was not associated with semiquantitative grade 3 vs 2 uptake (psoas P = 0.66, biceps P = 0.13) or presence of hereditary ATTR (psoas P = 0.43, biceps P = 0.69). As bony uptake decreased, there was no corresponding increase in skeletal muscle uptake. Conclusions: In patients with ATTR cardiac amyloidosis, skeletal muscle uptake of TcPYP is minimal when assessed by qualitative and quantitative metrics, and is not significantly different in patients with grade 2 vs 3 semiquantitative uptake. The properties of this tracer may be different than TcDPD with respect to non-cardiac uptake.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Intermolecular Network Theory:A General Approach for Understanding the Structural and Dynamic Properties of Liquids and Solutions

Graph theory applications within the physical sciences have a long history. However, it has never moved to the forefront of analytical techniques employed by the computational chemistry community. Though much of the earliest work leveraged percolation theory as a backdrop for understanding critical phenomena and phase transitions within statistical mechanical simulations, modern data science has much to contribute. Here in this paper, we focus on the realm of intermolecular networks, where vertices represent molecules or particles, and an edge represents an intermolecular or interparticle interaction. These interactions are widely understood to dictate many of the physical properties of soft matter, and for liquids in particular, understanding this network is essential. Consider the sheer volume of ~70 years of literature associated with the hydrogen bond network of water, a topic that remains an active area of research even today. The aim of this work is twofold: first, to put into context prior algorithms and analyses that employed “connectedness theory” or lattice-based models to understand the intermolecular networks of chemical systems; and second to discuss a more general strategy for analyzing the multiscale structural and dynamic properties of chemical systems—intermolecular network theory. This approach encompasses foundational methods such as percolation theory, but also utilizes contemporary graph theoretical analyses that have evolved alongside the development of the World Wide Web, cloud computing, and big data. It is the realm of intermolecular network theory to determine the relationships between the essential physics of a system and the topological properties of the network and to derive new techniques in graph theory that can be related to the underlying physico-chemical or reactive properties of a system. Examples are used throughout this chapter that demonstrate applications to a wide variety of complex chemical systems, including ion association within electrolytes, mass transport and the properties of liquid–liquid phase boundaries, and multicomponent solutions.

Complex networks↗

The first measurements of soft x-ray flux from ignition scale Hohlraums at the National Ignition Facility using DANTE (invited)

The first 96 and 192 beam vacuum Hohlraum target experiments have been fielded at the National Ignition Facility demonstrating radiation temperatures up to 340 eV and fluxes of 20 TW/sr as viewed by DANTE representing an {approx}20 times flux increase over NOVA/Omega scale Hohlraums. The vacuum Hohlraums were irradiated with 2 ns square laser pulses with energies between 150 and 635 kJ. They produced nearly Planckian spectra with about 30{+-}10% more flux than predicted by the preshot radiation hydrodynamic simulations. To validate these results, careful verification of all component calibrations, cable deconvolution, and software analysis routines has been conducted. In addition, a half Hohlraum experiment was conducted using a single 2 ns long axial quad with an irradiance of {approx}2x10{sup 15} W/cm{sup 2} for comparison with NIF Early Light experiments completed in 2004. We have also completed a conversion efficiency test using a 128-beam nearly uniformly illuminated gold sphere with intensities kept low (at 1x10{sup 14} W/cm{sup 2} over 5 ns) to avoid sensitivity to modeling uncertainties for nonlocal heat conduction and nonlinear absorption mechanisms, to compare with similar intensity, 3 ns OMEGA sphere results. The 2004 and 2009 NIF half-Hohlraums agreed to 10% in flux, but more importantly, the 2006 OMEGA Au Sphere, the 2009 NIF Au sphere, and the calculated Au conversion efficiency agree to {+-}5% in flux, which is estimated to be the absolute calibration accuracy of the DANTEs. Hence we conclude that the 30{+-}10% higher than expected radiation fluxes from the 96 and 192 beam vacuum Hohlraums are attributable to differences in physics of the larger Hohlraums.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗