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FIB-ToF-SIMS characterization of irradiated U-10Zr

Post-irradiation examination (PIE) is critical for the performance assessment and qualification of nuclear fuels. Secondary ion mass spectrometry (SIMS) is a powerful materials characterization technique that allows for elemental and isotopic mapping with a depth resolution greater than EDS and EPMA. However, it has not yet been applied to PIE of metallic nuclear fuel. Here, in this work, we characterize an fast neutron spectrum irradiated U-10Zr fuel sample using a time-of-flight SIMS (ToF-SIMS) system connected to a FIB/SEM system, which allows for flexible sample analysis compared to a dedicated ToF-SIMS instrument. Analysis of the resulting hyperspectral micrograph data was aided by the development of an unsupervised machine learning (ML) algorithm that iterates on existing methods to segment the 3D micrographic datasets based on the similarity of mass spectra. The results showed that the FIB-ToF-SIMS instrument was potentially capable of spatially resolving closed fission gas bubbles in 3D by continued ion sputtering of the analyzed volume. Additionally, the ML algorithm proved useful in revealing the chemical segregation of light fission products (those with an atomic mass between approximately 85–105 amu, such as ruthenium and rhodium) plus matrix zirconium, heavy fission products (those with an atomic mass between approximately 135–150 amu, such as the lanthanides) and uranium. Future studies are planned to conduct FIB-ToF-SIMS analysis on more irradiated U-Zr samples to study the constituent redistribution.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Phase retrieval for short wavelength orbital angular momentum beams using knife-edge diffraction

Laser beams operating in high order transverse modes, especially orbital angular momentum (OAM) modes, have been used increasingly in many frontier research areas. The characterization of these laser modes and the related component analysis can be carried out using the retrieved optical phase. However, conventional iterative phase retrieval methods, when applied to pure OAM modes, may fail because their convergence depends on the choice of the initial phase. Here, we present an improved phase retrieval method which can incorporate additional phase information obtained using knife-edge diffraction. Using no additional optics or few optics available in a wide spectral range, this method is particularly suitable for short wavelength lasers such as free-electron lasers (FELs) in the VUV, EUV, and X-ray regimes. Finally, this method has been tested using simulated beams, and successfully applied to experimentally generated beams from a HeNe laser and an FEL.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Explicit modeling of pebble temperature in the porous-media model for pebble-bed reactors

In this study, we developed a multiscale model to include an explicit pebble-temperature model nested in the porous-media model for pebble-bed reactor applications. The multiscale solid-phase energy balance model, including the pebble surface energy balance equation and an explicit modeling of pebble temperature, can predict the macroscopic (pebble bed) and microscopic (pebble) temperature distributions under both steady-state and transient conditions. The proposed multiscale model is solved in a fully coupled manner using the Newton- Krylov method, and therefore iterations between the macroscopic (pebble-bed-scale) and microscopic (pebble- scale) model are avoided. Extensive code verifications, validation, and demonstrations have been performed for this newly developed model. By explicitly modeling pebble temperatures, this new model addresses a major deficiency of the basic porous-media model, which assumes homogeneous solid-phase temperature and is not appropriate for pebble-bed reactor design and safety analyses.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Uncertainty Quantification in CO 2 Sequestration Using Surrogate Models from Polynomial Chaos Expansion

In this paper, surrogate models are iteratively built using polynomial chaos expansion (PCE) and detailed numerical simulations of a carbon sequestration system. Output variables from a numerical simulator are approximated as polynomial functions of uncertain parameters. Once generated, PCE representations can be used in place of the numerical simulator and often decrease simulation times by several orders of magnitude. However, PCE models are expensive to derive unless the number of terms in the expansion is moderate, which requires a relatively small number of uncertain variables and a low degree of expansion. To cope with this limitation, instead of using a classical full expansion at each step of an iterative PCE construction method, we introduce a mixed-integer programming (MIP) formulation to identify the best subset of basis terms in the expansion. This approach makes it possible to keep the number of terms small in the expansion. Monte Carlo (MC) simulation is then performed by substituting the values of the uncertain parameters into the closed-form polynomial functions. Based on the results of MC simulation, the uncertainties of injecting CO{sub 2} underground are quantified for a saline aquifer. Moreover, based on the PCE model, we formulate an optimization problem to determine the optimal CO{sub 2} injection rate so as to maximize the gas saturation (residual trapping) during injection, and thereby minimize the chance of leakage.

54 ENVIRONMENTAL SCIENCES↗

Temperature and density dependent pair potential for deuterium under shock

Large-scale classical molecular dynamics (CMD) simulations naturally include the microscopic physics necessary for atomistic modeling of shock release at the ablator-fuel interface in an inertial confinement fusion (ICF) capsule. Here, the multi-megabar shocks utilized in ICF experiments can drive the deuterium fuel from ambient to electron volt temperatures (T) and multi-fold compression. Modeling interatomic interactions over such an extreme range of conditions is challenging for empirical bond order potentials. We generate a pair potential for deuterium with explicit temperature and mass density dependence from ab initio density functional theory molecular dynamics using the iterative Boltzmann inversion method. This potential accurately reproduces the radial distribution functions and pressures from DFT in CMD equilibrium simulations across a wide range of thermodynamic conditions, yet fails to return the expected Hugoniot relations when used in direct CMD shock simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Rapid 3D nanoscale coherent imaging via physics-aware deep learning

Phase retrieval, the problem of recovering lost phase information from measured intensity alone, is an inverse problem that is widely faced in various imaging modalities ranging from astronomy to nanoscale imaging. The current process of phase recovery is iterative in nature. As a result, the image formation is time consuming and computationally expensive, precluding real-time imaging. Here, we use 3D nanoscale X-ray imaging as a representative example to develop a deep learning model to address this phase retrieval problem. We introduce 3D-CDI-NN, a deep convolutional neural network and differential programing framework trained to predict 3D structure and strain, solely from input 3D X-ray coherent scattering data. Our networks are designed to be “physics-aware” in multiple aspects; in that the physics of the X-ray scattering process is explicitly enforced in the training of the network, and the training data are drawn from atomistic simulations that are representative of the physics of the material. We further refine the neural network prediction through a physics-based optimization procedure to enable maximum accuracy at lowest computational cost. 3D-CDI-NN can invert a 3D coherent diffraction pattern to real-space structure and strain hundreds of times faster than traditional iterative phase retrieval methods. Our integrated machine learning and differential programing solution to the phase retrieval problem is broadly applicable across inverse problems in other application areas.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Subspace recursive Fermi-operator expansion strategies for large-scale DFT eigenvalue problems on HPC architectures

Quantum mechanical calculations for material modeling using Kohn–Sham density functional theory (DFT) involve the solution of a nonlinear eigenvalue problem for N smallest eigenvector-eigenvalue pairs, with N proportional to the number of electrons in the material system. Here, these calculations are computationally demanding and have asymptotic cubic scaling complexity with the number of electrons. Large-scale matrix eigenvalue problems arising from the discretization of the Kohn–Sham DFT equations employing a systematically convergent basis traditionally rely on iterative orthogonal projection methods, which are shown to be computationally efficient and scalable on massively parallel computing architectures. However, as the size of the material system increases, these methods are known to incur dominant computational costs through the Rayleigh–Ritz projection step of the discretized Kohn–Sham Hamiltonian matrix and the subsequent subspace diagonalization of the projected matrix. This work explores the potential of polynomial expansion approaches based on recursive Fermi-operator expansion as an alternative to the subspace diagonalization of the projected Hamiltonian matrix to reduce the computational cost. Subsequently, we perform a detailed comparison of various recursive polynomial expansion approaches to the traditional approach of explicit diagonalization on both multi-node central processing unit and graphics processing unit architectures and assess their relative performance in terms of accuracy, computational efficiency, scaling behavior, and energy efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Inexact iterative numerical linear algebra for neural network-based spectral estimation and rare-event prediction

Understanding dynamics in complex systems is challenging because there are many degrees of freedom, and those that are most important for describing events of interest are often not obvious. The leading eigenfunctions of the transition operator are useful for visualization, and they can provide an efficient basis for computing statistics, such as the likelihood and average time of events (predictions). Here, we develop inexact iterative linear algebra methods for computing these eigenfunctions (spectral estimation) and making predictions from a dataset of short trajectories sampled at finite intervals. We demonstrate the methods on a low-dimensional model that facilitates visualization and a high-dimensional model of a biomolecular system. Implications for the prediction problem in reinforcement learning are discussed.

Chemistry↗

Temperature-dependent phonon lifetimes and thermal conductivity of silicon by inelastic neutron scattering and ab initio calculations

In this paper, inelastic neutron scattering on a single crystal of silicon was performed at temperatures from 100 to 1500 K. These experimental data were reduced to obtain phonon spectral intensity at all wave vectors $\overset{→}{Q}$ and frequencies ω in the first Brillouin zone. Thermal broadenings of the phonon peaks were obtained by fitting and by calculating with an iterative ab initio method that uses thermal atom displacements on an ensemble of superlattices. Agreement between the calculated and experimental broadenings was good, with possible discrepancies at the highest temperatures. Distributions of phonon widths versus phonon energy had similar shapes for computation and experiment. These distributions grew with temperature but maintained similar shapes. Parameters from the ab initio calculations were used to obtain the thermal conductivity from the Boltzmann transport equation, which was in good agreement with experimental data. Despite the high group velocities of longitudinal acoustic phonons, their shorter lifetimes reduced their contribution to the thermal conductivity, which was dominated by transverse acoustic modes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

First Simultaneous Extraction of Spin-Dependent Parton Distributions and Fragmentation Functions from a Global QCD Analysis

In this paper, we perform the first global QCD analysis of polarized inclusive and semi-inclusive deep-inelastic scattering and single-inclusive $e^+e^-$ annihilation data, simultaneously fitting the parton distribution and fragmentation functions using the iterative Monte Carlo method. Without imposing SU(3) symmetry relations, we find the strange polarization to be very small, consistent with zero for both inclusive and semi-inclusive data, which provides a resolution to the strange quark polarization puzzle. Finally, the combined analysis also allows the direct extraction from data of the isovector and octet axial charges, and is consistent with a small SU(2) flavor asymmetry in the polarized sea.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Validation of Power Distribution Models using Load Flow Analysis in an ADMS Environment

Electric utilities are facing the need for better monitoring, analysis, and control of their distribution systems. An accurate mathematical model is a key to both the development of cutting-edge, scalable model-based algorithms and the assessment of emerging technologies such as distributed energy resources (DER) for grid planning and operation. However, the constantly evolving nature of power distribution systems poses challenges to maintaining accurate models. In this paper, we propose a novel load flow based approach to validate power distribution models. Networked equipment models described according to the Common Information Model (CIM) standard and a measurement model are used to formulate the distribution load flow problem. First, a system admittance matrix (Ybus) is derived from device-level CIM parameters. Next, the operational parameters (dynamic Ybus and nodal injections) are extracted from the measurement model using sensor configuration and equipment state. An iterative power flow method is then used to compute nodal voltages and branch flows that are compared against the measurement data to find any inconsistencies in the networked equipment model. This approach is implemented within GridAPPS-D, an open-source standards-based platform for advanced distribution management system (ADMS) application development, and demonstrated on the IEEE 13-bus, 123-bus, and 8500-node test feeders.

Common information model, model validation, power ↗

Quantum noise properties of CT images with anatomical textured backgrounds across reconstruction algorithms: FBP and SAFIRE

Purpose: Quantum noise properties of CT images are generally assessed using simple geometric phantoms with uniform backgrounds. Such phantoms may be inadequate when assessing nonlinear reconstruction or postprocessing algorithms. The purpose of this study was to design anatomically informed textured phantoms and use the phantoms to assess quantum noise properties across two clinically available reconstruction algorithms, filtered back projection (FBP) and sinogram affirmed iterative reconstruction (SAFIRE). Methods: Two phantoms were designed to represent lung and soft-tissue textures. The lung phantom included intricate vessel-like structures along with embedded nodules (spherical, lobulated, and spiculated). The soft tissue phantom was designed based on a three-dimensional clustered lumpy background with included low-contrast lesions (spherical and anthropomorphic). The phantoms were built using rapid prototyping (3D printing) technology and, along with a uniform phantom of similar size, were imaged on a Siemens SOMATOM Definition Flash CT scanner and reconstructed with FBP and SAFIRE. Fifty repeated acquisitions were acquired for each background type and noise was assessed by estimating pixel-value statistics, such as standard deviation (i.e., noise magnitude), autocorrelation, and noise power spectrum. Noise stationarity was also assessed by examining the spatial distribution of noise magnitude. The noise properties were compared across background types and between the two reconstruction algorithms. Results: In FBP and SAFIRE images, noise was globally nonstationary for all phantoms. In FBP images of all phantoms, and in SAFIRE images of the uniform phantom, noise appeared to be locally stationary (within a reasonably small region of interest). Noise was locally nonstationary in SAFIRE images of the textured phantoms with edge pixels showing higher noise magnitude compared to pixels in more homogenous regions. For pixels in uniform regions, noise magnitude was reduced by an average of 60% in SAFIRE images compared to FBP. However, for edge pixels, noise magnitude ranged from 20% higher to 40% lower in SAFIRE images compared to FBP. SAFIRE images of the lung phantom exhibited distinct regions with varying noise texture (i.e., noise autocorrelation/power spectra). Conclusions: Quantum noise properties observed in uniform phantoms may not be representative of those in actual patients for nonlinear reconstruction algorithms. Anatomical texture should be considered when evaluating the performance of CT systems that use such nonlinear algorithms.

60 APPLIED LIFE SCIENCES↗

WE-H-206-00: Advances in Preclinical Imaging

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffers from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.

60 APPLIED LIFE SCIENCES↗

WE-H-206-01: Photoacoustic Tomography: Multiscale Imaging From Organelles to Patients by Ultrasonically Beating the Optical Diffusion Limit

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffers from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.

60 APPLIED LIFE SCIENCES↗

WE-H-206-02: Recent Advances in Multi-Modality Molecular Imaging of Small Animals

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffers from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.

60 APPLIED LIFE SCIENCES↗

jShyLU Scalable Hybrid Preconditioner and Solver

ShyLU is numerical software to solve sparse linear systems of equations. ShyLU uses a hybrid direct-iterative Schur complement method, and may be used either as a preconditioner or as a solver. ShyLU is parallel and optimized for a single compute Solver node. ShyLU will be a package in the Trilinos software framework.

SciDAC↗

Impact of Glass Irradiation on Laser-Induced Breakdown Spectroscopy Data Analysis

Increased absorption of optical materials arising from exposure to ionizing radiation must be accounted for to accurately analyze laser-induced breakdown spectroscopy (LIBS) data retrieved from high-radiation environments. We evaluate this effect on two examples that mimic the diagnostics placed within novel nuclear reactor designs. The analysis is performed on LIBS data measured with 1% Xe gas in an ambient He environment and 1% Eu in a molten LiCl-KCl matrix, along with the measured optical absorption from the gamma- and neutron-irradiated low-OH fused silica and sapphire glasses. Significant changes in the number of laser shots required to reach a 3σ detection level are observed for the Eu data, increasing by two orders of magnitude after exposure to a 1.7 × 1017 n/cm2 neutron fluence. For all cases examined, the spectral dependence of absorption results in the introduction of systematic errors. Moreover, if lines from different spectral regions are used to create Boltzmann plots, this attenuation leads to statistically significant changes in the temperatures calculated from the Xe II lines and Eu II lines, lowering them from 8000 ± 610 K to 6900 ± 810 K and from 15,800 ± 400 K to 7200 ± 800 K, respectively, for exposure to the 1.7 × 1017 n/cm2 fluence. The temperature range required for a 95% confidence interval for the calculated temperature is also broadened. In the case of measuring the Xe spectrum, these effects may be mitigated using only the longer-wavelength spectral region, where radiation attenuation is relatively small, or through analysis using the iterative Saha–Boltzmann method.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗