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DOE OSTI2013

An extremely luminous and variable ultraluminous X-ray source in the outskirts of Circinus observed with NuSTAR

Following a serendipitous detection with the Nuclear Spectroscopic Telescope Array (NuSTAR), we present a multi-epoch spectral and temporal analysis of an extreme ultraluminous X-ray source (ULX) located in the outskirts of the Circinus galaxy, hereafter Circinus ULX5, including coordinated XMM-Newton+NuSTAR follow-up observations. The NuSTAR data presented here represent one of the first instances of a ULX reliably detected at hard (E > 10 keV) X-rays. Circinus ULX5 is variable on long time scales by at least a factor of ∼5 in flux, and was caught in a historically bright state during our 2013 observations (0.3-30.0 keV luminosity of 1.6 × 10{sup 40} erg s{sup –1}). During this epoch, the source displayed a curved 3-10 keV spectrum, broadly similar to other bright ULXs. Although pure thermal models result in a high energy excess in the NuSTAR data, this excess is too weak to be modeled with the disk reflection interpretation previously proposed to explain the 3-10 keV curvature in other ULXs. In addition to flux variability, clear spectral variability is also observed. While in many cases the interpretation of spectral components in ULXs is uncertain, the spectral and temporal properties of all the high quality data sets currently available strongly support a simple disk-corona model reminiscent of that invoked for Galactic binaries, with the accretion disk becoming more prominent as the luminosity increases. However, although the disk temperature and luminosity are well correlated across all time scales currently probed, the observed luminosity follows L∝T {sup 1.70±0.17}, flatter than expected for simple blackbody radiation. The spectral variability displayed here is highly reminiscent of that observed from known Galactic black hole binaries (BHBs) at high luminosities. This comparison implies a black hole mass of ∼90 M {sub ☉} for Circinus ULX5. However, given the diverse behavior observed from Galactic BHB accretion disks, this mass estimate is still uncertain. Finally, the limits placed on any undetected iron absorption features with the 2013 data set imply that we are not viewing the central regions of Circinus ULX5 through any extreme super-Eddington outflow.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series

The COVID-19 pandemic has underscored the need for accurate epidemic forecasting to predict pathogen spread, evolution, and evaluate intervention strategies. Forecast reliability hinges on detailed knowledge of disease transmission across population segments, which may be inferred from contact surveys or mobility data. However, these indirect approaches make it difficult to estimate rare transmissions between socially or geographically distant communities. We show that the steep ramp-up of genome sequencing surveillance during the pandemic can be leveraged to directly identify transmission patterns between geographically defined communities. Our approach uses a hidden Markov model to infer the fraction of infections a community imports from others based on how rapidly allele frequencies in the focal community converge to those in the donor communities. Applying this method to SARS-CoV-2 sequencing data from England and the United States, we uncover networks of intercommunity transmission that reflect geographical relationships while exposing significant long-range interactions. The scaling of importation rate with distance is consistent across both countries, yet weaker than expected based on mobility data, highlighting limitations of indirect inference. We show that transmission patterns can change between waves of variants of concern and analyze how the inferred heterogeneity in intercommunity transmission impacts evolutionary forecasts. While applied here to geographically defined communities, our approach could be applied to those defined by other traits (e.g., age, socioeconomic status), provided time-series data can be stratified accordingly. Overall, our study highlights population genomic time series data as a crucial record of epidemiological interactions, which can be deciphered using tree-free inference methods.

Okada, Takashi [Department of Physics; University ↗

DOE OSTI2024

Studying Transient Phenomena in Thin Films with Reinforcement Learning

Neutron reflectometry has long been a powerful tool to study the interfacial properties of energy materials. Recently, time-resolved neutron reflectometry has been used to better understand transient phenomena in electrochemical systems. Those measurements often comprise a large number of reflectivity curves acquired over a narrow q range, with each individual curve having lower information content compared to a typical steady-state measurement. In this work, we present an approach that leverages existing reinforcement learning tools to model time-resolved data to extract the time evolution of structure parameters. Further, by mapping the reflectivity curves taken at different times as individual states, we use the Soft Actor-Critic algorithm to optimize the time series of structure parameters that best represent the evolution of an electrochemical system. We show that this approach constitutes an elegant solution to the modeling of time-resolved neutron reflectometry data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Full spectrum (350-2500 nm) leaf and canopy spectral reflectance, Seward Peninsula, Alaska, 2019

Full-range (350 - 2500 nm) leaf and canopy reflectance spectra of various Arctic tundra ecosystem endmembers, including species-level leaf reflectance, canopy-scale species endmember spectra, plot-scale spectra, and transect spectra. These data were collected in support of ongoing NASA ABoVE AVIRIS data synthesis work. The datasets were collected at the NGEE-Arctic watershed sites, Kougarok MM64 and MM80, and Teller MM27 on the Seward Peninsula, Alaska. The data were collected in July 2019 using a full-range Spectra Vista Corporation (SVC) HR-1024i spectroradiometer. Leaf-level spectra were collected with the original SVC leaf clip/plant probe connected to the spectrometer through a 1.15 meter long fiber optic cable, while canopy-scale reflectance was collected with an 8-degree field-of-view (FOV) foreoptic lens. All spectral measurements were collected as calibrated surface radiance and converted to surface reflectance using a 99.99% reflective Spectralon white reference standard. For those canopy spectra collected with associated functional trait data, the FOV of the instrument was positioned to include the same leaves harvested for functional trait measurements, including leaf mass per area (LMA) and foliar carbon and nitrogen content (see leaf trait data package for these data). Canopy spectra were obtained for 23 different species, and leaf spectra for 8 species. This data package includes processed canopy and leaf spectra (*.csv), processed dGPS locations (*.csv and *.kmz), digital photographs of spectral targets (*.jpg) and raw data from spectroradiometer and dGPS instruments (compressed as tar.gz). Metadata files include data descriptions (_dd.csv) for tabular data and a key to species symbols used in data files. All included files are listed and described in NGA212_flmd.csv.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Ghost fringe removal techniques using Lissajous data presentation

A VISAR (Velocity Interferometer System for Any Reflector) is a Dopplervelocity interferometer which is an important optical diagnostic in shockwave experiments at the national laboratories, used to measureequation of state(EOS) of materials under extreme conditions. Unwanted reflection of laser light from target windows can produce an additional component to the VISAR fringe record that can distort and obscure the true velocity signal. When accurately removing this so-called ghost artifact component is essential for achieving high accuracy EOSmeasurements, especially when the true light signal is only weakly reflected from the shock front. Independent of the choice of algorithm for processing the raw data into a complex fringe signal, we have found it beneficial to plot this signal as a Lissajous and seek the proper center of this path, even under time varying intensity which can shift the perceived center. Moreover, the ghost contribution is then solved by a simple translation in the complex plane that recenters the Lissajous path. For continuous velocity histories, we find that plotting the fringe magnitude vs nonfringing intensity and optimizing linearity is an invaluable tool for determining accurate ghost offsets. For discontinuous velocity histories, we have developed graphically inspired methods which relate the results of two VISARs having different velocity per fringe proportionalities or assumptions of constant fringe magnitude to find the ghost offset. The technique can also remove window reflection artifacts in generic interferometers, such as in the metrology of surfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

EXONEST: Bayesian model selection applied to the detection and characterization of exoplanets via photometric variations

EXONEST is an algorithm dedicated to detecting and characterizing the photometric signatures of exoplanets, which include reflection and thermal emission, Doppler boosting, and ellipsoidal variations. Using Bayesian inference, we can test between competing models that describe the data as well as estimate model parameters. We demonstrate this approach by testing circular versus eccentric planetary orbital models, as well as testing for the presence or absence of four photometric effects. In addition to using Bayesian model selection, a unique aspect of EXONEST is the potential capability to distinguish between reflective and thermal contributions to the light curve. A case study is presented using Kepler data recorded from the transiting planet KOI-13b. By considering only the nontransiting portions of the light curve, we demonstrate that it is possible to estimate the photometrically relevant model parameters of KOI-13b. Furthermore, Bayesian model testing confirms that the orbit of KOI-13b has a detectable eccentricity.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

TH-E-209-00: Radiation Dose Monitoring and Protocol Management

Radiation dose monitoring solutions have opened up new opportunities for medical physicists to be more involved in modern clinical radiology practices. In particular, with the help of comprehensive radiation dose data, data-driven protocol management and informed case follow up are now feasible. Significant challenges remain however and the problems faced by medical physicists are highly heterogeneous. Imaging systems from multiple vendors and a wide range of vintages co-exist in the same department and employ data communication protocols that are not fully standardized or implemented making harmonization complex. Many different solutions for radiation dose monitoring have been implemented by imaging facilities over the past few years. Such systems are based on commercial software, home-grown IT solutions, manual PACS data dumping, etc., and diverse pathways can be used to bring the data to impact clinical practice. The speakers will share their experiences with creating or tailoring radiation dose monitoring/management systems and procedures over the past few years, which vary significantly in design and scope. Topics to cover: (1) fluoroscopic dose monitoring and high radiation event handling from a large academic hospital; (2) dose monitoring and protocol optimization in pediatric radiology; and (3) development of a home-grown IT solution and dose data analysis framework. Learning Objectives: Describe the scope and range of radiation dose monitoring and protocol management in a modern radiology practice Review examples of data available from a variety of systems and how it managed and conveyed. Reflect on the role of the physicist in radiation dose awareness.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Scaling relation for high-temperature biodiesel surrogate ignition delay times

High-temperature Arrhenius ignition delay time correlations are useful for revealing the underlying parameter dependencies of combustion models, for simplifying and optimizing combustion mechanisms for use in engine simulations, for scaling experimental data to new conditions for comparison purposes, and for guiding in experimental design. Here, we have developed a scaling relationship for Fatty Acid Methyl Ester (FAME) ignition time data taken at high temperatures in 4%O 2 /Ar mixtures behind reflected shocks using an aerosol shock tube: τ ign [ms] = 2.24 x 10 -6 [ms] (P [atm]) -.41 ($\phi$) 0.30 (C n ) -.61 x exp $$ \left(\frac{37.1 [kcal/mol]}{\hat{R}_u [kcal / mol K] T [K]}\right) $$ In addition, we have combined our ignition delay time data for methyl decanoate, methyl palmitate, methyl oleate, and methyl linoleate with other experimental results in the literature in order to derive fuel-specific oxygen-mole-fraction scaling parameters for these surrogates. In conclusion, in this article, we discuss the significance of the parameter values, compare our correlation to others found in the literature for different classes of fuels, and contrast the above expression’s performance with correlations obtained using leading FAME kinetic models in 4%O 2 /Ar mixtures.

09 BIOMASS FUELS↗

DOE OSTI2016

Subcritical Copper-Reflected-α-phase Plutonium (SCRαP) Integral Experiment Design

A Subcritical Copper-Reflected α-phase Plutonium (SCRαP) integral benchmark experiment is proposed where multiplication will be approximated using correlated neutron data from a detector system consisting of {sup 3}He tubes inside polyethylene. Measurements will be performed on various subcritical experimental configurations consisting of a weapons-grade plutonium sphere surrounded by different Cu thicknesses. In addition to the proposed base experimental configurations with Cu, additional configurations are planned with the plutonium ball nested in various thicknesses of interleaved polyethylene spherical shells mixed in with the Cu shells. The polyethylene is intended to provide fast neutron moderation and reflection, resulting in additional measurements with differing multiplication, spectra, and nuclear data sensitivity. The proposed experiments will performed at the National Criticality Experiments Research Center (NCERC). NCERC is home to a 4.5-kg α-phase stainless steel clad plutonium sphere that is referred to as the BeRP (Beryllium-Reflected Plutonium) ball due to its historical use in a beryllium-reflected critical experiment. In 2014, similar subcritical measurements were performed with the BeRP ball surrounded by nickel and tungsten. The nickel-reflected measurements were documented as a benchmark evaluation which was accepted by the International Criticality Safety Benchmark Evaluation Project (ICSBEP). Similar to past measurements, the proposed work will help both identify deficiencies and quantify uncertainties in nuclear data and validate computational methods related to neutron multiplication inference for subcritical benchmark evaluations. Monte Carlo simulations were performed for the preliminary design of a subcritical Copper-Reflected - phase Plutonium (SCRP) integral benchmark experiment. Specifically, MCNP{sup R} version 6 was used to determine the k{sub eff} and associated nuclear data sensitivities for different preliminary configurations (reflector thickness, material type). The final experimental design process will include continuous-energy nuclear data sensitivity analysis. This will help assess the potential impact of this integral measurement as it relates to international efforts to continuously improve current libraries (ENDF, JEFF, JENDL etc) that still tend to over/under-estimate the measured results of integral experiments, sometimes significantly. Deficiencies in underlying nuclear data quantities such as Nubar have been shown to have an effect on inferred values from subcritical measurements as well. The proposed experiments and subsequent computational validation will help identify such deficiencies. It will also help validate new nuclear data evaluations, including one for Cu that was recently performed in the resolved region up to 100 MeV for {sup 65}Cu and {sup 63}Cu which is expected to improve Cu-related benchmark simulation performance. The final experimental design phase will also include simulation results that will incorporate the detectors that will be used for the subcritical measurements. For the benchmark portion of the measurements, the main detectors that are being considered are portable neutron multiplicity counters made up of {sup 3}He tubes embedded in polyethylene and lined with cadmium. These detectors employ a data acquisition system that produces list-mode data (correlated information where each event is listed sequentially) that can be analyzed using the Feynman variance-to-mean method. Other detector systems including SNAP (single {sup 3}He tube embedded in polyethylene), and a high-purity germanium (HPGe) detector are being considered for supplementary measurements only and are not intended to be used for the final benchmark measurements. Decoupling the supplementary detectors from the system eliminates any contribution to the total system multiplication, and greatly simplifies the final computational benchmark model. Therefore, an optimization of the portable neutron multiplicity counter placement in the benchmark measurements will be performed to ensure that there is minimal contribution to the total system multiplication. In addition, new temperature measurement techniques and hardware will be explored. (authors)

42 ENGINEERING↗

DOE OSTI2019

Nanoconfinement and Mass Transport in Silica Mesopores: the Role of Charge at the Single Molecule and Single Pore Levels

Polarization-dependent single molecule tracking was employed to simultaneously probe the translational and orientational diffusion of four perylene diimide (PDI) dyes, having different lengths and charges, within the one-dimensional (1D) nanoscale pores of surfactant-templated mesoporous silica films. The wide-field fluorescence videos acquired reveal that a significant fraction of the molecules follow 1D pathways and exhibit highly polarized fluorescence, consistent with their orientational confinement. Single-frame step size distributions prepared from these data were fit to a new model that accurately describes the distribution for 1D Fickian diffusion in the presence of finite localization precision. Average diffusion coefficients obtained from mean square displacement (D MSD ) data were 20–100% larger for the two uncharged PDIs compared to the charged PDIs, reflecting electrostatic interactions of the latter with oppositely charged sites on the cationic surfactant headgroups and deprotonated silanol sites on the pore walls. Polarization-dependent tracking data show that the longest uncharged PDI was most strongly confined, while the three shorter dyes were less confined. The cationic PDI produced a wobbling angle distribution that was broader than the others, suggesting it explores more of the pore diameter. In conclusion, the results provide new knowledge on the mechanisms by which the dye molecules interact with the pore-filling medium and the pore surfaces, helping to elucidate the factors controlling the rate of mass transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Urban Effect on Precipitation and Deep Convective Systems Over Dallas‐Fort Worth

A range of multi-year observational data sets are used to characterize the hydroclimate of the Dallas Fort-Worth area (DFW) and to investigate the impact of urban land cover on daily accumulated precipitation, RADAR composite reflectivity (cREF), and cloud top height (CTH) during the warm season. Analyses of observational data indicate rainfall rates (RR) in a 45° annulus sector 50–100 km downwind of the city are enhanced relative to an upwind area of comparable size. Enhancement of mean precipitation intensity in this annulus sector is not observed on days with spatially averaged RR > 6 mm/day. Under some flow directions, the probability of cREF >30 dBZ, occurrence of hail, and the probability of CTH >10,000 geopotential meters are also enhanced up to 200 km downwind of DFW. Two deep convection events that passed over DFW are simulated with the Weather Research and Forecasting model using a range of microphysical schemes and evaluated using RADAR observations. Model configurations that exhibit the highest fidelity in these control simulations are used in a series of perturbation experiments where the areal extent of the city is varied between zero (replacement with grassland) and eight times its current size. These perturbation experiments indicate a non-linear response of Mesoscale Convective System properties to the urban areal extent and a very strong sensitivity to the microphysical scheme used. The impact on precipitation from the urban area, even when it is expanded to eight-times the current extent, is much less marked for deep convection with stronger synoptic forcing.

58 GEOSCIENCES↗

DOE OSTI2015

The role of remote sensing in process-scaling studies of managed forest ecosystems

Sustaining forest resources requires a better understanding of forest ecosystem processes, and how management decisions and climate change may affect these processes in the future. While plot and inventory data provide our most detailed information on forest carbon, energy, and water cycling, applying this understanding to broader spatial and temporal domains requires scaling approaches. Remote sensing provides a powerful resource for "upscaling" process understanding to regional and continental domains. The increased range of available remote sensing modalities, including interferometric radar, lidar, and hyperspectral imagery, allows the retrieval of a broad range of forest attributes. This paper reviews the application of remote sensing for upscaling forest attributes from the plot scale to regional domains, with particular emphasis on how remote sensing products can support parameterization and validation of ecosystem process models. We focus on four key ecological attributes of forests: composition, structure, productivity and evapotranspiration, and disturbance dynamics. For each attribute, we discuss relevant remote sensing technologies, provide examples of their application, and critically evaluate both strengths and challenges associated with their use. Published by Elsevier B.V.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Influence of substrate quality on structural properties of AlGaN/GaN superlattices grown by molecular beam epitaxy

Short-period AlGaN/GaN superlattices were established as versatile test structures to investigate the structural properties of molecular beam epitaxy (MBE)-grown GaN and AlGaN layers and their dependence on the GaN substrate quality. X-ray diffractometry data of the investigated superlattices allow access to relevant structural parameters such as aluminum mole fraction and layer thicknesses. The occurrence of theoretically predicted intense high-order satellite peaks and pronounced interface fringes in the diffraction pattern reflects abrupt interfaces and perfect 2-dimensional growth resulting in smooth surfaces. The data unambiguously demonstrate that the structural quality of the MBE grown layers is limited by the structural properties of the GaN substrate.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2013

Hot Pot Fault Summary

Compilation of faults interpreted from seismic reflection survey and from field observations.

15 GEOTHERMAL ENERGY↗

DOE OSTI2022

Cross-scale sensing of field-level crop residue cover: Integrating field photos, airborne hyperspectral imaging, and satellite data

Conservation tillage practices can bring benefits to agricultural sustainability. Accurate spatial and temporal resolved information of field-scale crop residue cover, which reflects tillage intensity, is highly valuable for evaluating the outcomes of government conservation programs and voluntary ecosystem service markets, as well as facilitating agroecosystem modeling to quantify cropland biogeochemical processes. Remote sensing has the potential to cost-effectively detect crop residue cover, however, existing regional-scale studies were limited by insufficient ground truth data, scale mismatch between coarse satellite pixels and ground data, and the lack of key spectral data for detecting crop residues. Therefore, this study developed an innovative cross-sensing framework to integrate proximal sensing, airborne hyperspectral imaging, and satellite Earth Observation through deep learning to quantify field-level crop residue cover fractions at the regional scale. Specifically, we have collected intensive ground orthographic photos and conducted airborne hyperspectral surveys at corn and soybean fields of Champaign and nearby counties in Illinois, the heartland of the U.S. Corn Belt. Through semi-automatic labeling aided by ResNet-50 and superpixel image segmentation, we obtained 6719 records of ground residue fractions. With these ground data, we developed the 1-dimensional convolution neural network (CNN) model using airborne hyperspectral reflectance, which has 0.5m spatial resolution and 3–5 nm spectral resolution from 400 to 2400 nm, to predict residue fractions. By applying the CNN model to airborne pixels, we augmented “ground truth” data of crop residues and further combined them with Harmonized Landsat and Sentinel-2 (HLS) satellite data to quantify regional residue fractions at 30 m resolution. Results show that airborne hyperspectral imagery with CNN can accurately detect residue fractions (R 2 = 0.82, relative RMSE = 11.73%) to effectively generate quasi “ground truth” data to support satellite upscaling to all fields. With independent ground data for testing, we found that the ground-airborne-satellite integrative framework achieved better predictions in estimating crop residue cover (R 2 = 0.67, relative RMSE = 17.53%) than the conventional ground-satellite upscaling (R 2 = 0.22, relative RMSE = 32.09%). Here we also found that the shortwave infrared wavelengths, particularly 2100–2300 nm, are vital for predicting crop residue cover. Sentinel-2 and Landsat-8 data have a comparable capability to track residue fractions due to similar shortwave infrared wavelengths. This study highlights the high accuracy of hyperspectral imaging to detect agroecosystem tillage management practices and the advantages of cross-scale sensing to cost-effectively integrate multi-source data to quantify field-level agroecosystem variables across scales.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Comparative analysis of plasmon modes in layered Lindhard metals and strange metals

The enigmatic strange metal remains one of the central unsolved problems of 21st century science. Understanding this phase of matter requires knowledge of the momentum- and energy-resolved dynamic charge susceptibility 𝜒⁡(𝑞,𝜔), especially at finite momentum. Inelastic electron scattering (EELS), performed in either transmission or reflection geometry, is a powerful probe of 𝜒⁡(𝑞,𝜔). For the prototypical strange metal Bi 2 ⁢Sr 2 ⁢CaCu 2 ⁢O 8+𝑥 , transmission- and reflection EELS, and infrared (IR) spectroscopy agree at 𝑞∼0, all revealing a highly damped plasmon near 1 eV. At larger 𝑞, however, EELS results show unresolved discrepancies. Since IR data are highly reproducible, it is advantageous to use IR data to calculate what the expected EELS response should be at modest 𝑞. Building on prior momentum-resolved reflection geometry M-EELS work [Chen et al., Phys. Rev. B 109, 045108 (2024)], we extend this approach to transmission EELS for finite stacks of metallic layers, comparing a “textbook” Lindhard metal to a strange metal. In the Lindhard case, the low-𝑞 response is dominated by long-lived, standing wave plasmon modes arising from interlayer Coulomb coupling, with in-plane dispersions that resemble the well-known Fetter modes of layered metals. This behavior depends only on the geometry and the long-range nature of the Coulomb interaction and is largely insensitive to layer details. At larger 𝑞, the response reflects the microscopic properties of individual layers. For the strange metal, calculations based on IR data predict a highly damped plasmon with weak dispersion and no distinct surface mode. While our results match IR and M-EELS at low 𝑞, they do not reproduce any published EELS spectra at large 𝑞, highlighting unresolved discrepancies that demand further experimental investigation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2016

TH-E-209-01: Fluoroscopic Dose Monitoring and Patient Follow-Up Program at Massachusetts General Hospital

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-E-209-02: Dose Monitoring and Protocol Optimization: The Pediatric Perspective

60 APPLIED LIFE SCIENCES↗