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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

FTIR and Raman Spectroscopy of Reduced Graphene Oxide Carbon Nanoribbons and Graphene Oxide on Copper (Cu)

In the past couple of decades, carbon nanomaterials produced from graphene and graphite have emerged as one of the more important recently discovered substances. These carbon nanomaterials have been found to exhibit high levels of mechanical strength, thermal resistance, and electrical conductivity, thus having a multitude of applications. Therefore, it is important to identify and analyze their traits in order to maximize their effectiveness. Two spectroscopic techniques employed for such analyses of these materials are Fourier-Transform Infrared (FTIR) and Raman Spectroscopy. The advantages of FTIR and Raman include nondestructive analysis, relatively quick measurements under normal atmospheric conditions, and enhanced sensitivity with high resolution capacity. FTIR Spectroscopy was used in this research project to determine the effects of thermal exfoliation and photoreduction on the functionality groups of a carbon nanomaterial. Raman Spectroscopy was used in this research project to determine the effects of thermal exfoliation and photoreduction on the intensity of the disorder peak, which is greater in intensity if the carbon nanomaterial exhibits greater amounts of functionalities or defects in the graphitic material. There were two sample types which were analyzed with both FTIR and Raman Spectroscopy for the research project: graphene nanoribbons and graphene oxide. The m-grade graphene nanoribbons (GNRs) were produced from m-grade carbon nanotubes (CNTs) via Tour's method. The graphene oxide (GO) was produced from graphene via Tour's method, sonicated and centrifuged, dip-coated onto Copper (Cu) foil, and then photoreduced under a UV light source. FTIR measurements and analyses were conducted using a Jasco FTIR Spectrometer. Raman measurements and analyses were conducted using a Jasco Laser Raman Spectrometer. Tasks and techniques for this project included photoreduction, dip-coating, corrosion testing, FTIR and Raman data collection and analysis, and improvement of data collection for the Raman Spectrometer. GNRs exfoliated and reduced (deoxygenation) at 270 deg. C in air showed a significant decrease in O functionalities according to FTIR. However, Raman revealed that a large increase in graphene planar and edge defects are present as indicated by the disorder band at 1340 cm-1. Further optimization could be performed by thermal exfoliation at lower temperatures assuming a need for fewer structural defects. Graphene oxide coatings showed clear reduction with an increase with photoreduction time. Raman revealed that the reduced graphene oxide films had less disruption in the planar phonon lattice vibrations which indicates that the structure is returning to sp2 hybridization of pristine graphene without adding structural defects.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Task 2.3: Continuous Counter-Current Chromatography

This task in the Separations Consortium focuses on the development of counter-current chromatography (CCC), which is an advanced liquid-liquid chromatography method. Today, CCC is primarily practiced in batch mode operation, but continuous operation will be required for at-scale deployment in a biorefinery setting. In this task, we are developing a continuous CCC process in collaboration with a company that builds CCC units. This work will be demonstrated on the biorefining challenge of lignin valorization. Specifically, we demonstrate use of continuous CCC for both monomer-monomer and monomer-oligomer separations in multiple lignin streams of relevance to the biorefining industry. Breakthroughs in this area would be useful for BETO goals in both sustainable aviation fuel and biochemicals production, including directly contributing to BETO's 2030 lignin valorization goal. Our approach includes developing new computational modeling approaches to optimize both batch and continuous CCC processes, experimental work to determine optimal solvent systems for multiple lignin streams sourced from BETO-funded projects and industrial collaborators, and techno-economic analysis and life cycle assessment to identify the most impactful areas to ultimately enable this approach in the biorefinery. This task overall will enable high-resolution, multi-component, continuous separations at scale, demonstrated on a grand challenge biorefining problem.

BIOMASS FUELS↗
DOE OSTI2020

Automatic log analysis with NLP for the CMS workflow handling

The central Monte-Carlo production of the CMS experiment utilizes the WLCG infrastructure and manages daily thousands of tasks, each up to thousands of jobs. The distributed computing system is bound to sustain a certain rate of failures of various types, which are currently handled by computing operators a posteriori. Within the context of computing operations, and operation intelligence, we propose a Machine Learning technique to learn from the operators with a view to reduce the operational workload and delays. This work is in continuation of CMS work on operation intelligence to try and reach accurate predictions with Machine Learning. We present an approach to consider the log files of the workflows as regular text to leverage modern techniques from Natural Language Processing (NLP). In general, log files contain a substantial amount of text that is not human language. Therefore, different log parsing approaches are studied in order to map the log files’ words to high dimensional vectors. These vectors are then exploited as feature space to train a model that predicts the action that the operator has to take. This approach has the advantage that the information of the log files is extracted automatically and the format of the logs can be arbitrary. In this work the performance of the log file analysis with NLP is presented and compared to previous approaches.

Layer, Lukas↗
DOE OSTI2013

Development of a Low NOx Medium sized Industrial Gas Turbine Operating on Hydrogen-Rich Renewable and Opportunity Fuels (Final Technical Report)

This report presents the accomplishments at the completion of the DOE sponsored project (Contract # DE-FC26-09NT05873) undertaken by Solar Turbines Incorporated. The objective of this 54-month project was to develop a low NOx combustion system for a medium sized industrial gas turbine engine operating on Hydrogen-rich renewable and opportunity Fuels. The work in this project was focused on development of a combustion system sized for 15MW Titan 130 gas turbine engine based on design analysis and rig test results. Although detailed engine evaluation of the complete system is required prior to commercial application, those tasks were beyond the scope of this DOE sponsored project. The project tasks were organized in three stages, Stages 2 through 4. In Stage 2 of this project, Solar Turbines Incorporated characterized the low emission capability of current Titan 130 SoLoNOx fuel injector while operating on a matrix of fuel blends with varying Hydrogen concentration. The mapping in this phase was performed on a fuel injector designed for natural gas operation. Favorable test results were obtained in this phase on emissions and operability. However, the resulting fuel supply pressure needed to operate the engine with the lower Wobbe Index opportunity fuels would require additional gas compression, resulting in parasitic load and reduced thermal efficiency. In Stage 3, Solar characterized the pressure loss in the fuel injector and developed modifications to the fuel injection system through detailed network analysis. In this modification, only the fuel delivery flowpath was modified and the air-side of the injector and the premixing passages were not altered. The modified injector was fabricated and tested and verified to produce similar operability and emissions as the Stage 2 results. In parallel, Solar also fabricated a dual fuel capable injector with the same air-side flowpath to improve commercialization potential. This injector was also test verified to produce 15-ppm NOx capability on high Hydrogen fuels. In Stage 4, Solar fabricated a complete set of injectors and a combustor liner to test the system capability in a full-scale atmospheric rig. Extensive high-pressure single injector rig test results show that 15-ppm NOx guarantee is achievable from 50% to 100% Load with fuel blends containing up to 65% Hydrogen. Because of safety limitations in Solar Test Facility, the atmospheric rig tests were limited to methane-based fuel blends. Further work to validate the durability and installed engine capability would require long-term engine field test.

42 ENGINEERING↗
DOE OSTI2013

DOE SciDAC’s Earth System Grid Center for Enabling Technologies Final Report for University of Southern California Information Sciences Institute

The mission of the Earth System Grid Federation (ESGF) is to provide the worldwide climate-research community with access to the data, information, model codes, analysis tools, and intercomparison capabilities required to make sense of enormous climate data sets. Its specific goals are to (1) provide an easy-to-use and secure web-based data access environment for data sets; (2) add value to individual data sets by presenting them in the context of other data sets and tools for comparative analysis; (3) address the specific requirements of participating organizations with respect to bandwidth, access restrictions, and replication; (4) ensure that the data are readily accessible through the analysis and visualization tools used by the climate research community; and (5) transfer infrastructure advances to other domain areas. For the ESGF, the U.S. Department of Energy’s (DOE’s) Earth System Grid Center for Enabling Technologies (ESG-CET) team has led international development and delivered a production environment for managing and accessing ultra-scale climate data. This production environment includes multiple national and international climate projects (such as the Community Earth System Model and the Coupled Model Intercomparison Project), ocean model data (such as the Parallel Ocean Program), observation data (Atmospheric Radiation Measurement Best Estimate, Carbon Dioxide Information and Analysis Center, Atmospheric Infrared Sounder, etc.), and analysis and visualization tools, all serving a diverse user community. These data holdings and services are distributed across multiple ESG-CET sites (such as ANL, LANL, LBNL/NERSC, LLNL/PCMDI, NCAR, and ORNL) and at unfunded partner sites, such as the Australian National University National Computational Infrastructure, the British Atmospheric Data Centre, the National Oceanic and Atmospheric Administration Geophysical Fluid Dynamics Laboratory, the Max Planck Institute for Meteorology, the German Climate Computing Centre, the National Aeronautics and Space Administration Jet Propulsion Laboratory, and the National Oceanic and Atmospheric Administration. The ESGF software is distinguished from other collaborative knowledge systems in the climate community by its widespread adoption, federation capabilities, and broad developer base. It is the leading source for present climate data holdings, including the most important and largest data sets in the globalclimate community, and—assuming its development continues—we expect it to be the leading source for future climate data holdings as well. Recently, ESG-CET extended its services beyond data-file access and delivery to include more detailed information products (scientific graphics, animations, etc.), secure binary data-access services (based upon the OPeNDAP Data Access Protocol), and server-side analysis. The latter capabilities allow users to request data subsets transformed through commonly used analysis and intercomparison procedures. As we transition from development activities to production and operations, the ESG-CET team is tasked with making data available to all users seeking to understand, process, extract value from, visualize, and/or communicate it to others—this is of course if funding continues at some level. This ongoing effort, though daunting in scope and complexity, would greatly magnify the value of numerical climate model outputs and climate observations for future national and international climate-assessment reports. The ESG-CET team also faces substantial technical challenges due to the rapidly increasing scale of climate simulation and observational data, which will grow, for example, from less than 50 terabytes for the last Intergovernmental Panel on Climate Change (IPCC) assessment to multiple Petabytes for the next IPCC assessment. In a world of exponential technological change and rapidly growing sophistication in climate data analysis, an infrastructure such as ESGF must constantly evolve if it is to remain relevant and useful.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Analysis of Tank 38H (HTF-38-21-24, -25) and Tank 43H (HTF-43-21-26, -27) Samples for Support of the Enrichment Control and Corrosion Control Programs

Feed limits have been established for the 2H-Evaporator system to ensure nuclear criticality is not possible and corrosion is minimized. These limits are protected by the Enrichment Control Program (ECP) and the Corrosion Control Program (CCP) that require periodic sampling and analysis to confirm that the waste supernate composition stays within the limits. Savannah River Remediation (SRR) obtained samples from two different heights within each of the two waste tanks supporting the 2H-Evaporator operations on March 26, 2021. The Tank 38H (evaporator drop tank) and Tank 43H (evaporator feed tank) samples were received by the Savannah River National Laboratory (SRNL) Shielded Cells on March 26, 2021. Analysis of these samples provides information necessary for determining compliance with the ECP and CCP. The sample characterization was requested via a Technical Task Request (TTR) and conducted based on a Task Technical and Quality Assurance Plan (TTQAP).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Normal mode analysis of macromolecular systems with the mobile block Hessian method

Until recently, normal mode analysis (NMA) was limited to small proteins, not only because the required energy minimization is a computationally exhausting task, but also because NMA requires the expensive diagonalization of a 3N{sub a}×3N{sub a} matrix with N{sub a} the number of atoms. A series of simplified models has been proposed, in particular the Rotation-Translation Blocks (RTB) method by Tama et al. for the simulation of proteins. It makes use of the concept that a peptide chain or protein can be seen as a subsequent set of rigid components, i.e. the peptide units. A peptide chain is thus divided into rigid blocks with six degrees of freedom each. Recently we developed the Mobile Block Hessian (MBH) method, which in a sense has similar features as the RTB method. The main difference is that MBH was developed to deal with partially optimized systems. The position/orientation of each block is optimized while the internal geometry is kept fixed at a plausible - but not necessarily optimized - geometry. This reduces the computational cost of the energy minimization. Applying the standard NMA on a partially optimized structure however results in spurious imaginary frequencies and unwanted coordinate dependence. The MBH avoids these unphysical effects by taking into account energy gradient corrections. Moreover the number of variables is reduced, which facilitates the diagonalization of the Hessian. In the original implementation of MBH, atoms could only be part of one rigid block. The MBH is now extended to the case where atoms can be part of two or more blocks. Two basic linkages can be realized: (1) blocks connected by one link atom, or (2) by two link atoms, where the latter is referred to as the hinge type connection. In this work we present the MBH concept and illustrate its performance with the crambin protein as an example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

CSP Systems Analysis 2022-2024 (Final Technical Report)

The CSP Systems Analysis project estimates the current market cost of CSP subsystems and technologies for use by the DOE Program and within NREL analysis tools. The project addresses upgrades to NREL's System Advisor Model (SAM) related to CSP, as well as development of new modules within SAM to expand the types of CSP systems that can be simulated and new tools for evaluating CSP subsystem performance or optimizing CSP system layouts, for example, SolarPILOT and SolTrace. The project evaluates the potential cost and performance of new CSP-relevant technologies and generally includes assessment of CSP technologies in support of the DOE subprogram. A primary goal of the CSP System Analysis project is to provide timely and accurate cost data to the DOE to assess the current state of CSP technologies as well as predict performance and cost for pre-commercial and emerging technologies that may impact the industry. Prior work in this task has produced technology cost reports and roadmaps for DOE and highlighted promising research paths that could reduce overall CSP cost, such as the supercritical CO2 power cycle and molten-salt trough systems. CSP Systems Analysis produces modeling tools to evaluate the performance of CSP systems, subsystems, or components, and journal articles, conference papers, technical reports and databases to disseminate information to the CSP industry. CSP technology costs are estimated and tracked using these tools as well as analysis of literature and industry sources. The CSP modeling tools and NREL analysis results are used by researchers; government, financial, and industry analysts; and other CSP stakeholders. The purpose of this final technical report is to summarize the key accomplishments of the past three years of this project. The project was divided into seven separate tasks, and in what follows, we describe the background, objectives, key accomplishments, and path forward for each task within the project, with one section of this report summarizing each task.

14 SOLAR ENERGY↗
DOE OSTI2016

A Business Case for Nuclear Plant Control Room Modernization

This paper presents a generic business case for implementation of technology that supports Control Room Modernization (CRM). The analysis presented in two forms; 1) a standalone technology upgrade, and 2) a technology upgrade that is built upon and incremental to a prior business case created for Mobile Work Packages (MWP). The business case contends that advanced communication and networking and analytical technologies will allow NPP to conduct control room operations with improved focus by reducing human factors and redundant manpower, and therefore operate with fewer errors. While some labor savings can be harvested in terms of overtime, the majority of savings are demonstrated as reduced time to take the plant off line and bring back on line in support of outages. The benefits are quantified to a rough order of magnitude that provides directional guidance to NPPs that are interested in developing a similar business case. This business case focuses on modernization of the operator control room and does not consider a complete overhaul and modernization of a plants instrument and control systems. While operators may be considering such an investment at their plants, the sizable capital investment required is not likely supported by a cost/benefit analysis alone. More likely, it is driven by obsolescence and reliability issues, and requires consideration of mechanical condition of plant systems, capital depreciation, financing, relicensing and overall viability of the plant asset over a 20-year horizon in a competitive market. Prior studies [REF] have indicated that such a modernization of plant I&C systems, alone or as part of a larger modernization effort, can yield very significant reductions in O&M costs. However, the depth of research and analysis required to develop a meaningful business case for a plant modernization effort is well beyond the scope of this study. While CRM as considered in this study can be easily integrated as part of grander plant modernization effort, it can also be considered as a stand-alone project, implemented as a supervisorial layer over and above existing systems. CRM is enabled by a suite of technologies, which are described in further detail in the body of this report. They include: • Modernized control room with interactive displays • High-bandwidth wireless networks • Mobile devices • Component identification technology • Mobile wireless video cameras • Smart or task based operator displays • Computer-Based Procedures (CBP)/Automated Mobile Work Packages (MWP) • Intelligent plant configuration • Advanced data analytics An analysis was conducted to determine how these technologies might impact outage operations at an NPP. The analysis concluded that outage management capabilities would be improved with application of these technologies, and result in annual benefits for the plant. These improved capabilities were identified and described in further detail in this report. • Reduction in need redundant manpower (verification, etc) • Improved critical path shutdown and restart duration during outages • Reduction in human factors and errors • Remote watches • Paperless outage coordination • Bulk work optimization

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2011

Solar Energy Research Center Instrumentation Facility

SOLAR ENERGY RESEARCH CENTER INSTRUMENTATION FACILITY The mission of the Solar Energy Research Center (UNC SERC) at the University of North Carolina at Chapel Hill (UNC-CH) is to establish a world leading effort in solar fuels research and to develop the materials and methods needed to fabricate the next generation of solar energy devices. We are addressing the fundamental issues that will drive new strategies for solar energy conversion and the engineering challenges that must be met in order to convert discoveries made in the laboratory into commercially available devices. The development of a photoelectrosynthesis cell (PEC) for solar fuels production faces daunting requirements: (1) Absorb a large fraction of sunlight; (2) Carry out artificial photosynthesis which involves multiple complex reaction steps; (3) Avoid competitive and deleterious side and reverse reactions; (4) Perform 13 million catalytic cycles per year with minimal degradation; (5) Use non-toxic materials; (6) Cost-effectiveness. PEC efficiency is directly determined by the kinetics of each reaction step. The UNC SERC is addressing this challenge by taking a broad interdisciplinary approach in a highly collaborative setting, drawing on expertise across a broad range of disciplines in chemistry, physics and materials science. By taking a systematic approach toward a fundamental understanding of the mechanism of each step, we will be able to gain unique insight and optimize PEC design. Access to cutting-edge spectroscopic tools is critical to this research effort. We have built professionally-staffed facilities equipped with the state-of the-art instrumentation funded by this award. The combination of staff, facilities, and instrumentation specifically tailored for solar fuels research establishes the UNC Solar Energy Research Center Instrumentation Facility as a unique, world-class capability. This congressionally directed project funded the development of two user facilities: TASK 1: SOLAR DEVICE FABRICATION LABORATORY DEVELOPMENT The space allocated for this laboratory was shell space that required an upfit in order to accommodate nano-fabrication equipment in a quasi-clean room environment. This construction project (cost $279,736) met the non-federal cost share requirement of $250,000 for this award. The central element of the fabrication laboratory is a new $400,000+ stand-alone system, funded by other sources, for fabricating and characterizing photovoltaic devices, in a state-of-the-art nanofabrication environment. This congressionally directed project also included the purchase of an energy dispersive x-ray analysis (EDX) detector for a pre-existing transmission electron microscope (TEM). This detector allows elemental analysis and elemental mapping of materials used to fabricate solar energy devices which is a key priority for our research center. TASK 2: SOLAR ENERGY SPECTROSCOPY LABORATORY DEVELOPMENT (INSTRUMENTATION) This laboratory provides access to modern spectroscopy and photolysis instrumentation for characterizing devices, materials and components on time scales ranging from femtoseconds to seconds and for elucidating mechanisms. The goals of this congressionally directed project included the purchase and installation of spectroscopy and photolysis instrumentation that would substantially and meaningfully enhance the capabilities of this laboratory. Some changes were made to the list of equipment proposed in the original budget. These changes did not represent a change in scope, approach or aims of this project. All of the capabilities and experiments represented in the original budget were maintained. The outcome of this Congressionally Directed Project has been the development of world-class fabrication and spectroscopy user facilities for solar fuels research at UNC-CH. This award has provided a significant augmentation of our pre-existing instrumentation capabilities which were funded by earlier UNC SERC projects, including the Energy Frontier Research Center UNC EFRC, funded by the US Department of Energy Office of Basic Energy Sciences. Equipment funded by this congressional award has provided important new capabilities for UNC SERC and has greatly facilitated collaborative research by many multi-institutional teams in the six partner institutions of the UNC EFRC, including Duke University, North Carolina Central University, and North Carolina State University. This state-of-the-art instrumentation has allowed us to design cutting-edge experiments that provide insight into the molecular structure and dynamics of materials and components for solar energy conversion under real working conditions. This research has resulted in ten publications already published or in preparation that acknowledge support from DOE EERE for this congressionally directed project.

14 SOLAR ENERGY↗
DOE OSTI2018

Behavioural phenotypes in mice after prenatal and early postnatal exposure to intermediate frequency magnetic fields

Highlights: • Human exposure to intermediate frequency magnetic fields (MF) is increasing. • We exposed prenatal and early postnatal male mice to 7.5 kHz MFs at 12 and 120 μT. • A behavioural teratology study focused on the developing nervous system. • No consistent adverse effects were observed. Electromagnetic fields are ubiquitous in the environment. Human exposure to intermediate frequency (IF) fields is increasing due to applications like electronic article surveillance systems, wireless power transfer, and induction heating cooking hobs. However, there are limited data on possible health effects of exposure to IF magnetic fields (MF). In the present study, we set out to assess cognitive and behavioural effects of IF MF in mice exposed during prenatal and early postnatal periods. Pregnant female mice were exposed continuously to 7.5 kHz MFs at 12 and 120 μT, from mating until weaning of pups. Sham exposed pregnant mice were used as a control group. A behavioural teratology study was conducted on the male offspring at two months of age to detect possible effects on the developing nervous system. Body weight development did not differ between the exposure groups. The exposure did not alter spontaneous motor activity when exploring a novel cage or anxiety in novelty-suppressed feeding or marble burying tests. Improved performance in the Rotarod task was observed in the 12 µT group, while the 120 μT exposure group swam more slowly than the sham exposed group in the Morris swim navigation task. However, indices of learning and memory (path length and escape latency during task acquisition and search bias during the probe test) did not differ between the exposure groups. Furthermore, the passive avoidance task did not indicate any impairment of long-term memory over a 48 h interval in the exposed groups. In a post-mortem histopathological analysis, there was no evidence for an effect of IF MF exposure on astroglial reactivity or hippocampal neurogenesis. The results suggest that the IF MF used did not have detrimental effects on spatial learning and memory or histological markers of tissue reaction. The two statistically significant findings that were observed (improved performance in the Rotarod task in the 12 µT group and decreased swimming speed in the 120 µT group) are likely to be chance findings, as they do not form an internally consistent, dose-dependent pattern indicative of specific developmental effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Electromagnetic analysis of the plasma chamber of an ECR-based charge breeder

The optimization of the efficiency of an ECR-based charge breeder is a twofold task: efforts must be paid to maximize the capture of the injected 1+ ions by the confined plasma and to produce high charge states to allow post-acceleration at high energies. Both tasks must be faced by studying in detail the electrons heating dynamics, influenced by the microwave-to-plasma coupling mechanism. Numerical simulations are a powerful tools for obtaining quantitative information about the wave-to-plasma interaction process: this paper presents a numerical study of the microwaves propagation and absorption inside the plasma chamber of the PHOENIX charge breeder, which the selective production of exotic species project, under construction at Legnaro National Laboratories, will adopt as charge breeder. Calculations were carried out with a commercial 3D FEM solver: first, all the resonant frequencies were determined by considering a simplified plasma chamber; then, the realistic geometry was taken into account, including a cold plasma model of increasing complexity. The results gave important information about the power absorption and losses and will allow the improvement of the plasma model to be used in a refined step of calculation reproducing the breeding process itself.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Statistical model based iterative reconstruction (MBIR) in clinical CT systems. Part II. Experimental assessment of spatial resolution performance

Purpose: Statistical model based iterative reconstruction (MBIR) methods have been introduced to clinical CT systems and are being used in some clinical diagnostic applications. The purpose of this paper is to experimentally assess the unique spatial resolution characteristics of this nonlinear reconstruction method and identify its potential impact on the detectabilities and the associated radiation dose levels for specific imaging tasks. Methods: The thoracic section of a pediatric phantom was repeatedly scanned 50 or 100 times using a 64-slice clinical CT scanner at four different dose levels [CTDI{sub vol} =4, 8, 12, 16 (mGy)]. Both filtered backprojection (FBP) and MBIR (Veo{sup ®}, GE Healthcare, Waukesha, WI) were used for image reconstruction and results were compared with one another. Eight test objects in the phantom with contrast levels ranging from 13 to 1710 HU were used to assess spatial resolution. The axial spatial resolution was quantified with the point spread function (PSF), while the z resolution was quantified with the slice sensitivity profile. Both were measured locally on the test objects and in the image domain. The dependence of spatial resolution on contrast and dose levels was studied. The study also features a systematic investigation of the potential trade-off between spatial resolution and locally defined noise and their joint impact on the overall image quality, which was quantified by the image domain-based channelized Hotelling observer (CHO) detectability index d′. Results: (1) The axial spatial resolution of MBIR depends on both radiation dose level and image contrast level, whereas it is supposedly independent of these two factors in FBP. The axial spatial resolution of MBIR always improved with an increasing radiation dose level and/or contrast level. (2) The axial spatial resolution of MBIR became equivalent to that of FBP at some transitional contrast level, above which MBIR demonstrated superior spatial resolution than FBP (and vice versa); the value of this transitional contrast highly depended on the dose level. (3) The PSFs of MBIR could be approximated as Gaussian functions with reasonably good accuracy. (4) Thez resolution of MBIR showed similar contrast and dose dependence. (5) Noise standard deviation assessed on the edges of objects demonstrated a trade-off with spatial resolution in MBIR. (5) When both spatial resolution and image noise were considered using the CHO analysis, MBIR led to significant improvement in the overall CT image quality for both high and low contrast detection tasks at both standard and low dose levels. Conclusions: Due to the intrinsic nonlinearity of the MBIR method, many well-known CT spatial resolution and noise properties have been modified. In particular, dose dependence and contrast dependence have been introduced to the spatial resolution of CT images by MBIR. The method has also introduced some novel noise-resolution trade-off not seen in traditional CT images. While the benefits of MBIR regarding the overall image quality, as demonstrated in this work, are significant, the optimal use of this method in clinical practice demands a thorough understanding of its unique physical characteristics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Analysis of Near-Field Magnetic Responses on ZrTe 5 through Cryogenic Magneto-THz Nano-Imaging

One manifestation of light-Weyl fermion interaction is the emergence of chiral magnetic effects under magnetic fields. Probing real space magnetic responses at terahertz (THz) scales is challenging but highly desired, as the local responses are less affected by the topologically trivial inhomogeneity that is ubiquitous in spatially averaged measurements. Here, we implement a cryogenic THz microscopy instrument under a magnetic field environment—a task only recently achieved. We explore the technical approach of this system and characterize the magnetic field’s influence on our AFM operation by statistical noise analysis. We find evidence for local near-field spatial variations in the topological semimetal ZrTe 5 up to a 5-Tesla magnetic field and obtain near-field THz spectra to discuss their implications for future studies on the chiral magnetic effect.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Big Data in HEP: A comprehensive use case study

Experimental Particle Physics has been at the forefront of analyzing the worlds largest datasets for decades. The HEP community was the first to develop suitable software and computing tools for this task. In recent times, new toolkits and systems collectively called Big Data technologies have emerged to support the analysis of Petabyte and Exabyte datasets in industry. While the principles of data analysis in HEP have not changed (filtering and transforming experiment-specific data formats), these new technologies use different approaches and promise a fresh look at analysis of very large datasets and could potentially reduce the time-to-physics with increased interactivity. In this talk, we present an active LHC Run 2 analysis, searching for dark matter with the CMS detector, as a testbed for Big Data technologies. We directly compare the traditional NTuple-based analysis with an equivalent analysis using Apache Spark on the Hadoop ecosystem and beyond. In both cases, we start the analysis with the official experiment data formats and produce publication physics plots. Lastly, we will discuss advantages and disadvantages of each approach and give an outlook on further studies needed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

SparseLU, A Novel Algorithm and Math Library for Sparse LU Factorization

Decomposing sparse matrices into lower and upper triangular matrices (sparse LU factorization) is a key operation in many computational scientific applications. We developed SparseLU, a sparse linear algebra library that implements a new algorithm for LU factorization on general sparse matrices. The new algorithm divides the input matrix into tiles to which OpenMP tasks are created for factorization computation, where only tiles that contain nonzero elements are computed. For comparative performance analysis, we used the reference library SuperLU. Testing was performed on synthetically generated matrices which replicate the conditions of the real-world matrices. SparseLU is able to reach a mean speedup of ~29× compared to SuperLU.

Valero Lara, Pedro↗
DOE OSTI2018

Towards Malware Detection via CPU Power Consumption: Data Collection Design and Analytics

This paper presents an experimental design and data analytics approach aimed at power-based malware detection on general-purpose computers. Leveraging the fact that malware executions must consume power, we explore the postulate that malware can be accurately detected via power data analytics. Our experimental design and implementation allow for programmatic collection of CPU power profiles for fixed tasks during uninfected and infected states using five different rootkits. To characterize the power consumption profiles, we use both simple statistical and novel, sophisticated features. We test a one-class anomaly detection ensemble (that baselines non-infected power profiles) and several kernel-based SVM classifiers (that train on both uninfected and infected profiles) in detecting previously unseen malware and clean profiles. The anomaly detection system exhibits perfect detection when using all features and tasks, with smaller false detection rate than the supervised classifiers. The primary contribution is the proof of concept that baselining power of fixed tasks can provide accurate detection of rootkits. Moreover, our treatment presents engineering hurdles needed for experimentation and allows analysis of each statistical feature individually. This work appears to be the first step towards a viable power-based detection capability for general-purpose computers, and presents next steps toward this goal.

Bridges, Robert↗