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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Relating structure and composition with accessibility of a single catalyst particle using correlative 3-dimensional micro-spectroscopy

To understand how hierarchically structured functional materials operate, analytical tools are needed that can reveal small structural and chemical details in large sample volumes. Often, a single method alone is not sufficient to get a complete picture of processes happening at multiple length scales. Here we present a correlative approach combining three-dimensional X-ray imaging techniques at different length scales for the analysis of metal poisoning of an individual catalyst particle. The correlative nature of the data allowed establishing a macro-pore network model that interprets metal accumulations as a resistance to mass transport and can, by tuning the effect of metal deposition, simulate the response of the network to a virtual ageing of the catalyst particle. In conclusion, the developed approach is generally applicable and provides an unprecedented view on dynamic changes in a material’s pore space, which is an essential factor in the rational design of functional porous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multidimensional measurements of beam single-spin asymmetries in semi-inclusive deep-inelastic charged-kaon electroproduction off protons in the valence region

Measurements of beam single-spin asymmetries in semi-inclusive deep-inelastic electron scattering (SIDIS) with positively charged kaons off protons have been performed with 10.6 and 10.2 GeV incident electron beams using the CLAS12 spectrometer at Jefferson Lab. We report an analysis of the electroproduction of positively charged kaons over a large kinematic range of fractional energy, Bjorken 𝑥, transverse momentum, and photon virtualities 𝑄 2 ranging from 1 GeV 2 up to 6 GeV 2 . This is the first published multidimensionally binned CLAS12 measurement of a kaon SIDIS single-spin asymmetry in the valence quark regime. The data provide constraints on the structure function ratio $𝐹^{sin \space𝜙}_{𝐿⁢𝑈}$⁡/$𝐹_{𝑈⁢𝑈}$, where $𝐹^{sin \space𝜙}_{𝐿⁢𝑈}$ is a quantity with a leading twist of twist-3 that can reveal novel aspects of the quark-gluon correlations within the nucleon. The impact of the data on understanding the underlying reaction mechanisms and their kinematic variation is explored using theoretical models for the different contributing twist-3 parton-distribution functions (PDFs) and fragmentation functions (FFs).

form factors↗
DOE OSTI2025

𝜂 and 𝜂′ meson production in 𝐽/𝜓 radiative decays from lattice QCD

We report on the computation of amplitudes describing the radiative decay processes 𝐽/𝜓 →𝛾⁢𝜂 and 𝐽/𝜓 →𝛾⁢𝜂′ from first principles via lattice quantum chromodynamics (QCD). Using lattices with two heavier than physical degenerate flavors of light quark where 𝑚 𝜋 ∼391 MeV, and a strange quark tuned to approximately the physical value, we compute three-point correlation functions using optimized meson operators with a range of momenta. The use of optimized operators allows access to the 𝜂′, even though it appears as an excited state, lying above the ground-state 𝜂 in the isoscalar pseudoscalar channel. Statistically precise signals are obtained in this disconnected process by averaging over large numbers of kinematically equivalent correlators. We determine transition form factors as a function of photon virtuality across the timelike region, which describe also the Dalitz processes 𝐽/𝜓 →𝑒 + ⁢𝑒 − ⁢𝜂 (′) . Significantly lower magnitudes of transition form factor for both the 𝜂 and 𝜂′ are found than those extracted from experimental data, and possible explanations for this observation are presented.

form factors↗
DOE OSTI2019

Evaluation of Hydrogen Production Feasibility for a Light Water Reactor in the Midwest

Increased electricity production from renewable energy resources coupled with low natural gas prices has caused existing light-water reactor (LWRs) to experience ever diminishing returns from the electricity market. Via partnership among Idaho National Laboratory (INL), The National Renewable Energy Laboratory (NREL), Argonne National Laboratory (ANL), Exelon, and Fuel Cell Energy a techno-economic analysis on the viability of retrofitting existing pressurized water reactors (PWRs) to produce hydrogen (H2) via high temperature steam electrolysis (HTSE) has been conducted. Such integration would allow nuclear facilities to expand into additional markets that may be more profitable in the long-term. To accommodate such an integration, a detailed analysis of HTSE process operation, requirements, and flexibility was conducted. Technical analysis includes proposed nuclear system control scheme modifications to allow dynamic operation of the HTSE via both thermal and electrical connection to the nuclear plant. High fidelity Modelica simulations showcase the viability of such control schemes. However, due to limited knowledge of solid oxide fuel cell (SOFC) stack degradation due to thermal gradients; thermal cycling of the HTSE was not included. Therefore, the control schemes proposed are only utilized to re-distribute steam at startup and only the portion of electricity utilized in the electrolyzers is cycled. From the detailed analysis of the nuclear integration and the HTSE process design, a comprehensive cost estimation was conducted in the APEA and H2A models to elucidate capital and operational costs associated with the production, compression, and distribution of hydrogen from a nuclear facility. Alongside this costing analysis, market analyses were conducted by NREL and ANL on the electric and hydrogen markets respectively in the PJM interconnect. Utilizing the electricity data market projections in the PJM interconnect from NREL and hydrogen demand/pricing projections from ANL a five variable sweep over component capacities, discount rates, and hydrogen pricing was completed using the stochastic framework RAVEN (Risk Analysis Virtual ENVironment) through its resource dispatch plugin HERON (Heuristic Energy Resource Optimization Network). Each combination of variables was evaluated stochastically four times over a seventeen year timespan from 2026-2042 (inclusive) to determine the most economically advantageous solution. Following the five variable sweep an optimization was conducted about the best sweep point to determine optimal component sizing and setpoints. Results suggest positive gain is achievable at all projected hydrogen market pricing levels and at all discount rates. However, exact component sizing and net returns vary based on these values and if incorrect sizing is selected; major net losses can occur. The optimal result occurred with set points as follows: high hydrogen prices, the largest possible HTSE unit in the sweep set at 7.47 kg/sec [645.4 tpd], a contractual hydrogen market agreement 7.29 kg/sec [629.8 tpd], and a hydrogen storage size 115,188 kg. The analysis suggested that with a discount rate of 8%, a ΔNPV = 1.2 billion over the seventeen year span can be achieved. The results illuminate that by operating in multiple markets the nuclear facility is capable of avoiding sale of electricity during times of low electricity market pricing, while maintaining the ability to capitalize on the high electricity market pricing. It should be noted that the analysis conducted in this report is a differential cash flow analysis and as such does not present profit levels. Instead it highlights the net benefit between building and competing in the hydrogen market utilizing nuclear facilities and conducting business as usual in the electricity markets. Additionally, results presented in this report exhibit conservatism due to four key assumptions: Given the limited knowledge on SOFC stack degradation due to thermal gradients the high temperature steam electrolysis plant is not allowed to thermally cycle. This limitation decreases electricity generation capacity in the nuclear plant, reducing capacity payments and the maximum output to the electrical grid. This analysis considers building a separate hydrogen pipeline for use in the nuclear facility. Research is currently being conducted to determine if existing natural gas pipelines can accommodate direct hydrogen injection. If hydrogen can be integrated into existing natural gas pipelines then a capital savings of ~$19,000,000 per kg/sec [1 kg/sec = 86.4 tpd] of installed HTSE capacity could be realized. Fast transients in the electric grid are typically served by flywheels and electric batteries. With electrolysis only operation the nuclear plant can flex its electricity just as quickly. However, for this analysis, the ancillary services market has been neglected. Should the nuclear plant have the ability to operate in the ancillary services market during periods when it is producing hydrogen, an additional substantial income stream that would increase overall system profitability could be considered. Subsidies for non-emitting generation technologies are not introduced in the cash flow analysis, but instead are completed assuming zero subsidies. Profitability is based solely on electricity pricing. Electric pricing is assumed to never go negative. Instead, it is assumed overall system curtailment by the Independent System Operator (ISO) will occur in such a manner that pricing remains at or above zero. This assumption inflates the “business as usual” scenario, thus decreasing the ΔNPV calculated. If negative pricing scenarios continue to occur as they do today, one would expect a further increase in ΔNPV. Overall, results advocate that, through market diversification, nuclear power plants have the potential to substantially increase current profit margins, increase market penetration, and ultimately solidify their place as a mainstay in energy production.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Spatially Adaptive Tunable Lighting Control System with Expanded Wellness and Energy Saving Benefits

Lighting design is becoming increasingly complex, including active dimming for energy savings and spectral tuning for human wellbeing. Modern commercial lighting control systems are already difficult to use, and maintain, and even with so-called Smart Lighting, optimizing light settings is rapidly exceeding the capabilities of direct human control, limiting the adoption of lighting control systems. The growing importance of Occupancy Centric Controls (OCC) for advanced building management systems can be applied to the development of autonomous lighting system controls needed to drive the adoption of advanced lighting controls for improved adaptive “sculpted illumination” for both greater energy savings and broader human wellbeing perspectives. This project, led by Rensselaer Polytechnic Institute, entitled “Spatially adaptive tunable lighting control system with expanded wellness and energy saving benefits” will develop and test an entirely new platform for automated optimized lighting design and control that requires little or no human engagement, yet contours lighting profiles automatically to minimize lighting energy use. We call this approach to lighting control “dynamic light sculpting” since the right amount of illumination is automatically delivered to occupants in real time. Since the system uses new, privacy-preserving occupant position and pose detection technologies developed by Rensselaer for broad OCC building applications, the control system will analyze how to deliver the right amount of the right type of illumination only where and when it is needed based these OCC platforms. To create these powerful autonomous lighting control platforms, the project will integrate evolving augmented reality (AR) and virtual reality (VR) tools with sophisticated lighting and interior design toolkits to create interactive lighting design and control simulators. Using the quickly growing paradigm of digital twins, these tools will integrate light fixture properties, occupancy sensor data, interior design data, and lighting specifications to accurately visualize how various design concepts interact with simulated yet realistic human activities that occur in commercial office buildings of various types. These advanced digital twin design and simulation tools will be combined with a new class of digitally-programmable LED lighting fixtures that can dynamically change the spectral content and direction of light emission. When fully integrated, the new autonomous lighting control system will take all of the guesswork out of optimizing light quality while minimizing energy consumption. Digital twin tools will simplify the design, installation, commissioning, operation, and maintenance of future energy-efficient lighting systems. It should be possible to reduce lighting energy costs from 40% to 70% with OCC based dynamic light sculpting systems. The work will be led by the Center for Lighting Enabled Systems and Applications (LESA) and the Center for Architectural Science and Ecology (CASE), both at Renssealer Polytechnic Institute; Lumileds, a global leader in the development of advanced LED systems; and HKS, a leading global architecture design firm. This interdisciplinary project team’s experience includes all of the design simulation tools, VR/AR digital twin visualization technology, advanced occupancy sensing technology, and complex control system design capabilities that will revolutionize lighting design and control technology to autonomously deliver high-quality lighting that improves human health and wellbeing while simultaneously maximizing lighting energy savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Protein-ligand binding affinity prediction using multi-instance learning with docking structures

Recent advances in 3D structure-based deep learning approaches demonstrate improved accuracy in predicting protein-ligand binding affinity in drug discovery. These methods complement physics-based computational modeling such as molecular docking for virtual high-throughput screening. Despite recent advances and improved predictive performance, most methods in this category primarily rely on utilizing co-crystal complex structures and experimentally measured binding affinities as both input and output data for model training. Nevertheless, co-crystal complex structures are not readily available and the inaccurate predicted structures from molecular docking can degrade the accuracy of the machine learning methods. We introduce a novel structure-based inference method utilizing multiple molecular docking poses for each complex entity. Our proposed method employs multi-instance learning with an attention network to predict binding affinity from a collection of docking poses. We validate our method using multiple datasets, including PDBbind and compounds targeting the main protease of SARS-CoV-2. The results demonstrate that our method leveraging docking poses is competitive with other state-of-the-art inference models that depend on co-crystal structures. This method offers binding affinity prediction without requiring co-crystal structures, thereby increasing its applicability to protein targets lacking such data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Promising Innovations for the Lighting Profession: Big Data, New Tools

The use of parametric modeling is increasing as computing power increases, supporting the use of generative design software to design shoes and plan architectural spaces. This big data inclusive design process is used for daylighting studies, and is ripe for development by the larger lighting community.

Lighting, generative design, virtual reality↗
DOE OSTI2023

Semi-Automatic Geographic Information System Framework for Creating Photo-Realistic Digital Twin Cities to Support Autonomous Driving Research

Digital twin cities are frequently used in vehicle and traffic simulations to render realistic on-road driving scenarios under various traffic and environmental conditions. These digital twins provide a high-fidelity replica of the physical world (e.g., buildings, roads, infrastructures, traffic) to create three-dimensional (3D) virtual-physical environments to support various emerging vehicle and transportation technologies such as connected and automated vehicles. These virtual environments provide a cost-effective digital proving ground to evaluate, validate, and test emerging technologies that include control algorithms, localization, perception, and sensors. Replicating a real-world traffic scenario in a digital twin using a traditional 3D modeling approach is a time-consuming and labor-intensive effort. Here this paper presents a semi-automated spatial framework to construct realistic 3D digital twin cities to support autonomous driving research using readily available geographic information system (GIS) data and 3D prefabricated (prefab) models. We start with a comprehensive review of geospatial data sources of essential digital entities required in a 3D digital twin city and present an integrated GIS-3D modeling pipeline using customized QGIS/GDAL and Blender scripting in Python. The pipeline outputs are realistic 3D digital twin cities compatible with common vehicle simulation software, such as CARLA and IPG CarMaker. The paper closes with a showcase to demonstrate the quality and usability of a digital twin city created to replicate the Shallowford Road corridor in Chattanooga in both Unity and Unreal engine-based virtual environment. The generated digital twin city can be applied to a hardware-in-the-loop simulation environment with an actual testing vehicle to facilitate autonomous driving research.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

The TELPERION survey for distant [O iii ] clouds around luminous and hibernating AGN

ABSTRACT We present a narrow-band [O iii] imaging survey of 111 active galactic nucleus (AGN) hosts and 17 merging-galaxy systems, in search of distant extended emission-line regions (EELRs) around AGNs (either extant or faded). Our data reach deeper than detection from the broad-band SDSS data and cover a wider field than some early emission-line surveys used to study extended structure around AGNs. Spectroscopic follow-up confirms two new distant AGN-ionized clouds, in the merging systems NGC 235 and NGC 5514, projected at 26 and 75 kpc from the nuclei (respectively). We also recover the previously known region in NGC 7252. These results strengthen the connection between EELRs and tidal features; kinematically quiescent distant EELRs are virtually always photoionized tidal debris. We see them in ≈10 per cent of the galaxies in our sample with tidal tails. Energy budgets suggest that the AGN in NGC 5514 has faded by >3 times during the extra light traveltime ≈250 000 yr from the nucleus to the cloud and then to the observer; strong shock emission in outflows masks the optical signature of the AGN. For NGC 235 our data are consistent with but do not unequivocally require variation over ≈85 000 yr. In addition to these very distant ionized clouds, we find luminous and extensive line emission within four galaxies – IC 1481, ESO 362-G08, NGC 5514, and NGC 7679. Among these, IC 1481 shows apparent ionization cones, a rare combination with its LINER AGN spectrum. In NGC 5514, we measure a 7-kpc shell expanding at ≈370 km s−1 west of the nucleus.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches

Identification of endocrine disrupting chemicals is one of the important goals of environmental chemical hazard screening. We report on the development of validated in silico predictors of chemicals likely to cause estrogen receptor (ER)-mediated endocrine disruption to facilitate their prioritization for future screening. A database of relative binding affinity of a large number of ERα and/or ERβ ligands was assembled (546 for ERα and 137 for ERβ). Both single-task learning (STL) and multi-task learning (MTL) continuous quantitative structure–activity relationship (QSAR) models were developed for predicting ligand binding affinity to ERα or ERβ. High predictive accuracy was achieved for ERα binding affinity (MTL R{sup 2} = 0.71, STL R{sup 2} = 0.73). For ERβ binding affinity, MTL models were significantly more predictive (R{sup 2} = 0.53, p < 0.05) than STL models. In addition, docking studies were performed on a set of ER agonists/antagonists (67 agonists and 39 antagonists for ERα, 48 agonists and 32 antagonists for ERβ, supplemented by putative decoys/non-binders) using the following ER structures (in complexes with respective ligands) retrieved from the Protein Data Bank: ERα agonist (PDB ID: 1L2I), ERα antagonist (PDB ID: 3DT3), ERβ agonist (PDB ID: 2NV7), and ERβ antagonist (PDB ID: 1L2J). We found that all four ER conformations discriminated their corresponding ligands from presumed non-binders. Finally, both QSAR models and ER structures were employed in parallel to virtually screen several large libraries of environmental chemicals to derive a ligand- and structure-based prioritized list of putative estrogenic compounds to be used for in vitro and in vivo experimental validation. - Highlights: • This is the largest curated dataset inclusive of ERα and β (the latter is unique). • New methodology that for the first time affords acceptable ERβ models. • A combination of QSAR and docking enables prediction of affinity and function. • The results have potential applications to green chemistry. • Models are publicly available for virtual screening via a web portal.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Explainable discrepancy checker and diagnosis for digital Twin-based supervisory control system

By virtually representing a physical object and process, a digital twin (DT) enables optimal autonomous operations by combining classical and novel frameworks in sensors, state predictions, and multi-input/multi-output systems. A DT’s values depend on how well models estimate quantities of interest and on how uncertainty is handled. Moreover, DTs often combine physics-based and data-driven models with mixed fidelities, where classical uncertainty quantification (UQ) struggles with many sources of uncertainty and real-time constraints. Here, this work presents a UQ-based discrepancy checking and diagnosis tool for a DT-based supervisory control system. The tool is developed using metadata from an automated DT development process to learn correlations between sources of uncertainties and outcomes. During operation, it compares predictions with measurements, attributes discrepancies to dominant sources, and recommends parameter and configuration updates. We verify the workflow on a synthetic temperature-control problem and deploy it on a virtual Thermal Energy Delivery System, reducing mismatch and improving control robustness.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Measurement of the top-quark Yukawa coupling from $t\overline{t}$ production in the lepton+jets final state using pp collisions at $\sqrt{s}=13$ TeV with the ATLAS detector

The top-quark Yukawa coupling is extracted from the distribution of the top-quark pair ($t\overline{t}$) invariant mass in proton-proton collisions using 140 fb −1 of data at $\sqrt{s}=13$ TeV collected in 2015–2018 by the ATLAS experiment at the Large Hadron Collider. In the region near the production threshold, the $t\overline{t}$ invariant mass spectrum is sensitive to electroweak virtual corrections, including contributions from Higgs boson exchange, thereby providing sensitivity to the top-quark Yukawa coupling. This is the first measurement in ATLAS that aims to obtain this coupling exploiting this approach. The $t\overline{t}$ system is reconstructed in the single-lepton final state, requiring exactly one isolated electron or muon and at least four jets with at least two identified as originating from b-quarks. The measured Yukawa coupling is found to be in good agreement with the Standard Model prediction. An upper limit on the top-quark Yukawa coupling strength of Y t < 2.1 relative to the Standard Model prediction is observed at 95% confidence level, consistent with the expected sensitivity.

Hadron-Hadron Scattering↗
DOE OSTI2022

Photo- and Electrocouplings of Nucleon Resonances

Advances in the exploration of the spectrum and structure of the excited states of the nucleon from experiments with electromagnetic probes on proton targets are presented here. Impressive progress has been achieved in the studies of exclusive meson photoproduction in experiments with continuous electron beams and with detectors of almost 4π acceptance. The high-quality data, coupled with the advances in the amplitude analyses of exclusive photo- and hadroproduction data, allow for the observation of several long-awaited new baryon states known previously as the “missing” resonances. Studies of exclusive meson electroproduction in the resonance region with the CLAS detector at JLab have provided the dominant part of the available world information on exclusive meson electroproduction observables. These data offer unique information on the structure of most well-established excited nucleon states in the mass region up to 1.8 GeV in terms of the evolution of their electroexcitation amplitudes with momentum transfer of the virtual photon. We discuss the impact of these results on the insight into the strong interaction dynamics that underlie the generation of the full spectrum of nucleon resonances of distinctively different structure. These results shed light on the emergence of hadron mass, which is one of the most important and still open problems in the Standard Model. The extension of the nucleon resonance stud

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Lights on: Dye dequenching reveals polymersome fusion with polymer, lipid and stealth lipid vesicles

In this study, we develop a quantitative dye dequenching technique for the measurement of polymersome fusion, using it to characterize the salt mediated, mechanically-induced fusion of polymersomes with polymer, lipid, and so-called stealth lipid vesicles. While dye dequenching has been used to quantitatively explore liposome fusion in the past, this is the first use of dye dequenching to measure polymersome fusion of which we are aware. In addition to providing quantitative results, dye dequenching is ideal for detecting fusion in instances where DLS results would be ambiguous, such as low yield levels and size ranges outside the capabilities of DLS. The dye chosen for this study was a cyanine derivative, 1,1'-dioctadecyl-3,3,3',3'-tetramethylindotricarbocyanine iodide (DiR), which proved to provide excellent data on the extent of polymersome fusion. Using this technique, we have shown the limited fusion capabilities of polymersome/liposome heterofusion, notably DOPC vesicles fusing with polymersomes at half the efficiency of polymersome homofusion and DPPC vesicles showing virtually no fusion. In addition to these key heterofusion experiments, we determined the broad applicability of dye dequenching in measuring kinetic rates of polymersome fusion; and showed that even at elevated temperatures or over multiple weeks' time, no polymersome fusion occurred without agitation. Stealth liposomes formed from DPPC and PEO-functionalized lipid, however, fused with polymersomes and stealth liposomes with relatively high efficiency, lending support to our hypothesis that the response of the PEO corona to salt is a key factor in the fusion process. This last finding suggests that although the conjugation of PEO to lipids increases vesicle biocompatibility and enables their longer circulation times, it also renders the vesicles subject to destabilization under high salt and shear (e.g. in the circulatory system) that may lead to, in this case, fusion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure-based modeling methods

The thyroid hormone receptor (THR) is an important member of the nuclear receptor family that can be activated by endocrine disrupting chemicals (EDC). Quantitative Structure–Activity Relationship (QSAR) models have been developed to facilitate the prioritization of THR-mediated EDC for the experimental validation. The largest database of binding affinities available at the time of the study for ligand binding domain (LBD) of THRβ was assembled to generate both continuous and classification QSAR models with an external accuracy of R{sup 2} = 0.55 and CCR = 0.76, respectively. In addition, for the first time a QSAR model was developed to predict binding affinities of antagonists inhibiting the interaction of coactivators with the AF-2 domain of THRβ (R{sup 2} = 0.70). Furthermore, molecular docking studies were performed for a set of THRβ ligands (57 agonists and 15 antagonists of LBD, 210 antagonists of the AF-2 domain, supplemented by putative decoys/non-binders) using several THRβ structures retrieved from the Protein Data Bank. We found that two agonist-bound THRβ conformations could effectively discriminate their corresponding ligands from presumed non-binders. Moreover, one of the agonist conformations could discriminate agonists from antagonists. Finally, we have conducted virtual screening of a chemical library compiled by the EPA as part of the Tox21 program to identify potential THRβ-mediated EDCs using both QSAR models and docking. We concluded that the library is unlikely to have any EDC that would bind to the THRβ. Models developed in this study can be employed either to identify environmental chemicals interacting with the THR or, conversely, to eliminate the THR-mediated mechanism of action for chemicals of concern. - Highlights: • This is the largest curated dataset for ligand binding domain (LBD) of the THRβ. • We report the first QSAR model for antagonists of AF-2 domain of THRβ. • A combination of QSAR and docking enables prediction of both affinity and efficacy. • Models can be used to identify environmental chemicals interacting with THRβ. • Models can be used to eliminate the THRβ-mediated mechanism of action.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-FG-207B-12: Quantitative Evaluation of a Spectral CT Scanner in a Phantom Study: Results of Spectral Reconstructions

Purpose: To evaluate the quantitative image quality of spectral reconstructions of phantom data from a spectral CT scanner. Methods: The spectral CT scanner (IQon Spectral CT, Philips Healthcare) is equipped with a dual-layer detector and generates conventional 80-140 kVp images and variety of spectral reconstructions, e.g., virtual monochromatic (VM) images, virtual non-contrast (VNC) images, iodine maps, and effective atomic number (Z) images. A cylindrical solid water phantom (Gammex 472, 33 cm diameter and 5 cm thick) with iodine (2.0-20.0 mg I/ml) and calcium (50-600 mg/ml) rod inserts was scanned at 120 kVp and 27 mGy CTDIvol. Spectral reconstructions were evaluated by comparing image measurements with theoretical values calculated from nominal rod compositions provided by the phantom manufacturer. The theoretical VNC was calculated using water and iodine basis material decomposition, and the theoretical Z was calculated using two common methods, the chemical formula method (Z1) and the dual-energy ratio method (Z2). Results: Beam-hardening-like artifacts between high-attenuation calcium rods (≥300 mg/ml, >800 HU) influenced quantitative measurements, so the quantitative analysis was only performed on iodine rods using the images from the scan with all the calcium rods removed. The CT numbers of the iodine rods in the VM images (50∼150 keV) were close to theoretical values with average difference of 2.4±6.9 HU. Compared with theoretical values, the average difference for iodine concentration, VNC CT number and effective Z of iodine rods were −0.10±0.38 mg/ml, −0.1±8.2 HU, 0.25±0.06 (Z1) and −0.23±0.07 (Z2). Conclusion: The results indicate that the spectral CT scanner generates quantitatively accurate spectral reconstructions at clinically relevant iodine concentrations. Beam-hardening-like artifacts still exist when high-attenuation objects are present and their impact on patient images needs further investigation. YY is an employee of Philips Healthcare.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Experimental investigation of ρ{sup 0} photoproduction on the pion in the H1 experiment

Experimental results on quasielastic photoproduction of the ρ{sup 0} meson in association with a neutron, obtained at the HERA collider, are presented. The total and differential cross sections of the γp → ρ{sup 0}nπ{sup +} reaction at the positron–proton center-of-mass energy of √s =319 GeV are measured. The data collected with the H1 detector in 2006 and 2007 correspond to an integrated luminosity of 1.16 pb{sup −1}. The kinematic region of the photon–proton cms energy of 20 < W{sub γp} <100 GeV, photon virtuality of Q{sup 2} < 2 GeV{sup 2}, and the ρ{sup 0} transverse momentum below 1 GeV/c is analyzed. Secondary neutrons with energies x{sub L} > 0.35 (in proton-energy units) and emission angles below 0.75 mrad are selected. The model of double peripheral exchange, in which the ρ{sup 0} is elastically produced via the photon interaction with the virtual pion from the proton–neutron vertex, is employed for interpreting the results. The cross section for the ρ{sup 0} elastic photoproduction on the pion, γπ{sup +}→ ρ{sup 0}π{sup +}, is extracted in the one-pion-exchange approximation. The magnitude of the cross section suggests that the γp → ρ{sup 0}nπ{sup +} reaction is significantly affected by absorption.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

HIBP Applications to Advance Understanding of Plasma Transport Physics (2011-2017) (and subsequently titled) Development of Beam Measurements to Advance Understanding of Transients and Improve Validation (2017-2020) (Final Technical Report)

This is the Final Technical Report for the DoE Measurement Innovation (previously Diagnostic Development) grant DE-SC0006077 titled HIBP Applications to Advance Understanding of Plasma Transport Physics (2011-2017), and subsequently titled Development of Beam Measurements to Advance Understanding of Transients and Improve Validation (2017-2020). The grant was funded by the Office of Fusion Energy Sciences (FES) for the period 1 May 2011–17 July 2020. Work performed through the grant has resulted in diagnostic innovations and new measurement capabilities that will improve understanding of transport, magnetic equilibrium, and electric fields in magnetically confined plasmas. We have developed novel hardware and advanced techniques to expand beam-based diagnostic capabilities, and extend measurements to new operating regimes. Some have been realized using a Heavy Ion Beam Probe (HIBP) having traditional features, while other applications have joined our innovations with subsets of advantageous HIBP features. This work has established smaller, more economical detection systems and, in doing so, may enable substantial extension of scenarios in which beam-based diagnostics are deployed. Key Measurement Innovations include: Computer Models and Simulations of HIBP Applications-Computer modeling and simulating of HIBP applications is central to predicting interaction of beam particles with plasmas, designing diagnostic systems, and anticipating measurement characteristics. We have extended the capability and improved measurement fidelity of the HIBP diagnostic on the Madison Symmetric Torus (MST) reversed field pinch (RFP); simulated feasibility of HIBP operation in the Helically Symmetric eXperiment (HSX) optimized stellarator; and investigated the plausibility of HIBP measurements in the ASDEX Upgrade tokamak. We have also developed a new technique that uses ion optics to model a finite phase-space beam. It yields more realistic (than traditional method) estimates of sample volume characteristics, which influence measurement resolution and sensitivity. Extension of Diagnostic Capabilities and Measurements on the MST RFP-Capabilities have been extended using the first and only HIBP installation on an RFP. Challenges associated with operation of the diagnostic on MST include the three-dimensional nature of particle trajectories, temporal topology and amplitude changes in the plasma equilibrium, and strong particle and radiative emission from the plasma. We have addressed these challenges through development of detailed and higher precision diagnostic simulations, calibrated subtraction of noise to resolve secondary ion signals, and implementation of hardware that enables higher fidelity measurement of plasma fluctuations. Development of New Hardware and Measurement Techniques - We have advanced beam-based measurement capabilities via development of new detectors and techniques to determine the poloidal magnetic flux ψ in the plasma, and enable placement of detectors close to the plasma and thus allow a smaller and less expensive diagnostic. We have demonstrated measurement of ψ, an ability that was made possible by development of highly effective noise reduction techniques. We also modeled the effect of non-ideal and instrumentation effects by developing a virtual (simulated) diagnostic. Application of beam-based diagnostics on various devices and multiple magnetic configurations (e.g. stellarator, tokamak, and reversed field pinch) enables investigation of critical physics issues and measurements resulting in the broad parameter space data needed to test and validate theory & modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗