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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 OSTI2025

Exploiting correlations in multi-coincidence Coulomb explosion patterns for differentiating molecular structures using machine learning

Coulomb explosion imaging (CEI) is a powerful technique for capturing the real-time motion of individual atoms during ultrafast photochemical reactions. CEI generates high-dimensional data with naturally embedded correlations that allow mapping the coordinated motion of nuclei in molecules. This enables reliable separation of competing reaction pathways and makes this approach uniquely suited for characterizing weak reaction channels. However, rich information contained in experimental CEI patterns remains largely underexploited due to challenges in visualizing correlations between multiple observables in multi-dimensional parameter space. Here we present a new approach to CEI of intermediate-sized polyatomic molecules, detecting up to eight ionic fragments in coincidence and leveraging machine-learning-based analysis to identify patterns and correlations in the resulting high-dimensional momentum-space data, enabling robust molecular structure identification and differentiation. Our approach provides high-dimensional background-free data encoding exceptionally rich structural information and establishes an automated, scalable framework for extracting insightful information from the data. As a demonstration, we apply this method to image and distinguish dichloroethylene isomers, showcasing its potential for broader applications in molecular imaging. Our results pave the way for channel-specific analysis of ultrafast structural dynamics in chemically relevant systems, particularly for disentangling mixed reaction pathways and detecting contributions from weak channels and minority species.

Chemical Physics (physics.chem-ph)↗
DOE OSTI2021

Demonstrating SolarPILOT's Python API Through Heliostat Optimal Aimpoint Strategy Use Case: Preprint

SolarPILOT is a software package that generates heliostat field layouts and characterizes the optical performance of concentrating solar power (CSP) tower systems. SolarPILOT was developed by the National Renewable Energy Laboratory (NREL) as a stand-alone desktop application but has also been incorporated into NREL's System Advisor Model (SAM) in a simplified format. Prior means for user interaction with SolarPILOT have included the application's graphical interface, the SAM routines with limited configurability, and through a built-in scripting language called "LK." This paper presents a new, full-featured Python-based application programmable interface (API) for SolarPILOT, which we hereafter refer to as CoPylot. CoPylot provides access to all SolarPILOT's capabilities to generate and characterize power tower CSP systems seamlessly through Python. Supported capabilities include (i) creating and destroying a model instances with message reporting tools; (ii) accessing and setting any SolarPILOT variable including custom land boundaries for field layout; (iii) programmatically managing receiver and heliostat objects with varied attributes for systems with multiple receiver or heliostat types; (iv) generating, assigning, and modifying heliostat field layouts including the ability to set individual heliostat locations, aimpoints, soiling rates, and reflectivity levels; (v) simulating heliostat field performance; (vi) returning detailed results describing performance of individual heliostats, the aggregate field, and receiver flux; and, (vii) exporting Python-based model instances to multiple file formats. CoPylot enables Python users to perform detailed tower CSP analysis utilizing either the Hermite expansion technique (analytical) or the SolTrace ray-tracing engine. In addition to CoPylot's functionality, Python users have access to the over 100,000 open-source libraries to develop, analyze, optimize, and visualize CSP tower research.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2021

Spatiotemporal mapping of mesoscopic liquid dynamics

The study of liquid dynamics at mesoscopic scales is still strewn with difficulty due to limitations in theory and experiment. Historically, significant attention has been given to the analysis of space-time correlation functions and their frequency-Fourier transforms at a few discrete wave numbers. The massive computing power afforded by modern high performance computing clusters and the advent of a wide-angle neutron spin-echo spectrometer, however, have unlocked a more intuitive and fruitful approach to this problem. Using molecular dynamics simulations, here we demonstrate the benefits of spatiotemporally mapping intermediate scattering functions on a dense grid of correlation times and wave numbers. Four model systems are investigated: a Lennard-Jones liquid, a coarse-grained bead-spring polymer, a molten sodium chloride, and a poly(ethylene oxide) melt. We show that the spatiotemporal mapping approach is particularly useful for elucidating the mesoscopic dynamics in these liquids, where several underlying mechanisms, such as molecular relaxations, hydrodynamic modes, and nonhydrodynamic excitations, are potentially at play. Therefore, compared to the traditional method, direct visualization of density space-time correlation functions on two-dimensional color maps permits appraisals of complicated dynamical behavior at mesoscales in a global manner. For example, the scaling relations between space and time for different types of molecular motions can be straightforwardly identified on these plots, without any model-dependent analysis. Additionally, we show how theoretical ideas regarding collective mesoscopic dynamics, such as the classical hydrodynamic theory, the convolution approximation, and a recently proposed phenomenological model, can be discussed in terms of the global features of spatiotemporal maps of intermediate scattering functions. The new perspective offered by the spatiotemporal mapping method should prove useful for the study of liquid dynamics in general.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Transportation and System Analysis Collaborations in Support of a Federal Consolidated Interim Storage Facility

The U.S. Department of Energy’s Integrated Waste Management (IWM) program under the Office of Nuclear Energy is planning for the future transportation, storage, and eventual disposal of spent nuclear fuel (SNF) and high-level radioactive waste (HLW) from nuclear power plant and waste custodian sites across the United States. To better enable informed decision-making regarding the back end of the nuclear fuel cycle, the IWM program has been sponsoring the development and application of system analysis tools capable of analyzing various options for managing SNF and HLW. With these tools, integrated waste management system (IWMS) architecture analyses are being conducted to support the future deployment of a comprehensive nuclear waste management system that considers all major back-end aspects of the nuclear fuel cycle (i.e., transportation, storage, and disposal). System analyses and assessments typically use these modeling and simulation tools to investigate implications of changes in various assumptions and parameters such as acceptance rates, receipt logic, facility capacities and capabilities, use of standardized canisters, start and stop dates of facilities, etc. The Next Generation System Analysis Model (NGSAM) is an agent-based simulation toolkit that is used for a system-level simulation and analysis focused on SNF management in the United States. NGSAM’s primary purpose is to provide a system analyst with capabilities to model the IWMS and gain insights into SNF and HLW management alternatives including the impact of system choices, associated cost estimates, and development of integrated yet flexible approaches. An analyst using NGSAM can define several factors like the number of storage facilities, capacity at each facility, transportation schedules, shipment rates, and other conditions. IWM is also developing the Stakeholder Tool for Assessing Radioactive Transportation (START). START is a web-based geospatial tool developed to provide the visualization and initial evaluation of transportation options associated with future SNF and HLW shipment planning and operations. This includes characterizing safety, economic, and environmental conditions at and in proximity to shipment origins as well as along prospective transportation routes. Information from the START tool can be presented/shared as maps, graphics, geospatial files, and tabular form to enable easy data representation and export functionality. The system analysis, NGSAM, and START teams have been working closely for several years before formalizing this collaboration. START provides the SNF transportation routing information for use in NGSAM. System analysts use the NGSAM tool to generate results (schedule, costs, infrastructure acquisitions, shipment rates, etc.). Subject-matter experts and system analysts work together to inform how NGSAM should model the waste management system. Specifically, this paper discusses the collaborations between the system analysis, NGSAM, and START teams and their accomplishments over the past year. Some examples of these efforts include calibrating and adding data to the START output files to meet NGSAM needs, gaining a better understanding of START data used in NGSAM as well as how updates in START data could result in an improved NGSAM analysis. Detailed examples of various tasks that have been performed by the team will be discussed in the full paper. Continued efforts in this direction are expected in the coming years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Transportation and Systems Analysis Collaborations in Support of a Federal Consolidated Interim Storage Facility

The U.S. Department of Energy’s Integrated Waste Management (IWM) program under the Office of Nuclear Energy is planning for the future transportation, storage, and eventual disposal of spent nuclear fuel (SNF) and high-level radioactive waste (HLW) from nuclear power plant sites across the United States. To better enable informed decision-making regarding the back end of the nuclear fuel cycle, the IWM program has been sponsoring the development and application of system analysis tools capable of analyzing various options for managing SNF and HLW. With these tools, integrated waste management system (IWMS) architecture analyses are being conducted to support the future deployment of a comprehensive nuclear waste management system that considers all major back-end aspects of the nuclear fuel cycle (i.e., transportation, storage, and disposal). System analyses and assessments typically use these modeling and simulation tools to investigate implications of changes in various assumptions and parameters such as acceptance rates, receipt logic, facility capacities and capabilities, use of standardized canisters, start and stop dates of facilities, etc. The Next Generation System Analysis Model (NGSAM) is an agent-based simulation toolkit that is used for a system-level simulation and analysis focused on SNF management in the United States. An analyst using NGSAM has the ability to define several factors like the number of storage facilities, capacity at each facility, transportation schedules, shipment rates, and other conditions. NGSAM’s primary purpose is to provide a system analyst with capabilities to model the IWMS and gain insights into SNF and HLW management alternatives including the impact of system choices, associated cost estimates, and development of integrated yet flexible approaches. IWM is also developing the Stakeholder Tool for Assessing Radioactive Transportation (START). START is a web-based geospatial tool developed to provide visualization and initial evaluation of transportation options associated with future SNF and HLW shipment planning and operations. This includes characterizing safety, economic, and environmental conditions on and in proximity to shipment origins as well as along prospective transportation routes. Information from the START tool can be presented/shared as maps, graphics, geospatial files, and tabular form to enable easy data representation and export functionality. The system analysis, NGSAM, and START teams had been working closely for several years before formalizing this collaboration. START provides the SNF routing information for use in NGSAM. System analysts use the NGSAM tool to generate results (schedule, costs, infrastructure acquisitions, shipment rates, etc.). Subject-matter experts and system analysts work together to inform how NGSAM should model the waste management system. Specifically, this paper discusses the collaborations between the system analysis, NGSAM, and START teams and their accomplishments over the past year. Some examples of these efforts include calibrating and adding data to the START output files to meet NGSAM needs, gaining a better understanding of START data used in NGSAM, as well as how updates in START data could result in an improved NGSAM analysis. Detailed examples of various tasks that have been performed by the team will be discussed in the full paper. Continued efforts in this direction are expected in the coming years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Meeting Global Health Needs via Infectious Disease Forecasting: Development of a Reliable Data-Driven Framework

Infectious diseases (IDs) have a significant detrimental impact on global health. Timely and accurate ID forecasting can result in more informed implementation of control measures and prevention policies. To meet the operational decision-making needs of real-world circumstances, we aimed to build a standardized, reliable, and trustworthy ID forecasting pipeline and visualization dashboard that is generalizable across a wide range of modeling techniques, IDs, and global locations. We forecasted 6 diverse, zoonotic diseases (brucellosis, campylobacteriosis, Middle East respiratory syndrome, Q fever, tick-borne encephalitis, and tularemia) across 4 continents and 8 countries. We included a wide range of statistical, machine learning, and deep learning models (n=9) and trained them on a multitude of features (average n=2326) within the One Health landscape, including demography, landscape, climate, and socioeconomic factors. The pipeline and dashboard were created in consideration of crucial operational metrics—prediction accuracy, computational efficiency, spatiotemporal generalizability, uncertainty quantification, and interpretability—which are essential to strategic data-driven decisions. While no single best model was suitable for all disease, region, and country combinations, our ensemble technique selects the best-performing model for each given scenario to achieve the closest prediction. For new or emerging diseases in a region, the ensemble model can predict how the disease may behave in the new region using a pretrained model from a similar region with a history of that disease. The data visualization dashboard provides a clean interface of important analytical metrics, such as ID temporal patterns, forecasts, prediction uncertainties, and model feature importance across all geographic locations and disease combinations. As the need for real-time, operational ID forecasting capabilities increases, this standardized and automated platform for data collection, analysis, and reporting is a major step forward in enabling evidence-based public health decisions and policies for the prevention and mitigation of future ID outbreaks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Analysis of Tank 38H (HTF-38-22-91, -92) and Tank 43H (HTF-43-22-93, -94) Samples for Support of the Enrichment Control and Corrosion Control Programs

SRNL analyzed samples from Tank 38H and Tank 43H to support ECP and CCP. The results indicate the concentrations of most soluble species in the Tank 38H surface sample increased slightly from the previous surface sample. The Tank 38H sub-surface sample shows changes in concentration for soluble species in the solution with some increasing and some decreasing. The current Tank 38H sub-surface sample contains more sludge solids than the previous sample based on visual appearance. The small differences in the concentrations of major components between the Tank 38H surface and sub-surface samples indicate only minimal stratification of solution species within the tank. The Tank 43H surface and sub-surface samples are similar in composition to the previous samples. The similar solution compositions measured in the Tank 43H surface and sub-surface samples indicate a minimal stratification within the tank. The total uranium and plutonium in the current Tank 38H surface sample remains similar to the previous analysis. The Tank 38H sub-surface sample shows an increase in uranium and plutonium concentrations compared to the previous sample likely because of an increase in sludge solids in the current sample. The total uranium concentration in the two Tank 43H samples is essentially unchanged from previous sample results. The plutonium concentration in the Tank 43H surface sample is similar to the previous sample results while the plutonium in the Tank 43H sub-surface sample increased relative to the previous analysis. The sum of the major cations versus the sum of the major anions shows a difference of <10% for both samples from Tank 38H and for both samples from Tank 43H providing an indication of good data quality for the non-radioactive analytes in the samples. The silicon concentrations measured in the Tank 38H sub-surface sample increased compared with the previous sample results likely due to the presence of more sludge solids in the current sample. The Tank 38H surface sample silicon concentrations is similar to the previous sample results. The Tank 43H surface and sub-surface sample silicon concentrations both increased compared to the previous sample results. The samples analyzed from Tanks 38H and 43H show silicon concentrations ranging from 61.5 to 97.3 mg/L.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Visualizing Organizational Influence on Energy Infrastructure

Energy Infrastructure components depend on an evolving, interdependent business ecosystem exposed to long-term, legal, adversarial tactics. An INL-Naval Postgraduate School partnership was designed to support INL Lab Directed Research and Development, NPS graduate research projects, and joint publications. The Technology, Organization, and Person of interest Graph Extraction, Analysis, and Reporting (TOP GEAR) enumerates networks of organizations and people that own, operate, and maintain regional infrastructure assets. TOP GEAR allows analysts to model current and future state what-if scenarios that include technological and policy mitigations.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
DOE OSTI2023

Delamination-Assisted Ultrafast Wrinkle Formation in a Freestanding Film

Freestanding films provide a versatile platform for materials engineering thanks to additional structural motifs not found in films with a substrate. A ubiquitous example is wrinkles, yet little is known about how they can develop over as fast as a few picoseconds due to a lack of experimental probes to visualize their dynamics in real time on the nanoscopic scale. Here, we use time-resolved electron diffraction to directly observe light-activated wrinkling formation in freestanding La 2/3 Ca 1/3 MnO 3 films. Via a “lock-in” analysis of oscillations in the diffraction peak position, intensity, and width, we quantitatively reconstructed how wrinkles develop on the time scale of lattice vibration. Contrary to the common assumption of fixed boundary conditions, we found that wrinkle development is associated with ultrafast delamination at the film boundaries. Finally, our work provides a generic protocol to quantify wrinkling dynamics in freestanding films and highlights the importance of the film–substrate interaction in determining the properties of freestanding structures.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Quality Assurance and Quality Control (QA/QC) of Meteorological Time Series Data for Billy Barr, East River, Colorado USA

A comprehensive Quality Assurance (QA) and Quality Control (QC) statistical framework consists of three major phases: Phase 1—Preliminary raw data sets exploration, including time formatting and combining datasets of different lengths and different time intervals; Phase 2—QA of the datasets, including detecting and flagging of duplicates, outliers, and extreme values; and Phase 3—the development of time series of a desired frequency, imputation of missing values, visualization and a final statistical summary. The time series data collected at the Billy Barr meteorological station (East River Watershed, Colorado) were analyzed. The developed statistical framework is suitable for both real-time and post-data-collection QA/QC analysis of meteorological datasets.The files that are in this data package include one excel file, converted to CSV format (Billy_Barr_raw_qaqc.csv) that contains the raw meteorological data, i.e., input data used for the QA/QC analysis. The second CSV file (Billy_Barr_1hr.csv) is the QA/QC and flagged meteorological data, i.e., output data from the QA/QC analysis. The last file (QAQC_Billy_Barr_2021-03-22.R) is a script written in R that implements the QA/QC and flagging process. The purpose of the CSV data files included in this package is to provide input and output files implemented in the R script.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Development of lithium ion conducting interface between lithium metal and a lithium ion conducting ceramic using block polymers

The lithium-air (Li-air) technology developed by EDF uses an air electrode which works with an aqueous electrolyte, which prevent the use of unprotected lithium metal electrode. A Li+ ionic conductor glass ceramic is used to separate the aqueous electrolyte compartment from the negative lithium electrode. However, this glass-ceramic is not stable in contact with lithium, it is thus necessary to add a protective buffer layer. In another hand, this protection should ideally resist to lithium dendritic growth. It is in this context that this research project which has as goal the development of a protective buffer layer based on block copolymer electrolytes (BCE) between the lithium metal and the lithium ionic conductor ceramic, for lithium-air battery. In a first part, the BCE is studied in lithium-lithium symmetric cells, in order to determine their electrochemical properties such as ionic conductivity, steady state transference number, and finally their resistance to dendritic growth during cycling. Several characterization techniques were employed and especially hard X-ray micro-tomography to analyze the lithium morphology before and after cycling. For single-ion BCE, we expect to suppress dendritic growth, however, we report here for the first time, the visualization of a homogeneous growth of lithium but the formation of dense lithium objects. In another part, the composite BCE-ceramic is studied by electrochemical impedance spectroscopy (EIS). The cycling of lithium-composite-lithium symmetric cells and the analysis of the EIS measurement after each cycle permit to determine if the dendrites have cross the protective layer and are in contact with the ceramic. Besides, the quantification of the polarization loss at the interface polymer-ceramic is evaluated by polarization experiments. This contribution is found to be small.

36 MATERIALS SCIENCE↗
DOE OSTI2022

MPLBM-UT: Multiphase LBM library for permeable media analysis

MPLBM-UT is a specialized lattice-Boltzmann library that makes running single- and two-phase flow simulations in porous media accessible to everyone. We provide a suite of tools to pre-process computational domains for simulation, to set up custom boundary conditions, to run simulations, to post-process simulation outputs, and to visualize simulation results and data. All of these tools are easily accessible to users through the mplbm_utils Python package included in and automatically installed with MPLBM-UT. The high-performance, highly parallel library Palabos is used as the solver backend. MPLBM-UT is easily deployed in a variety of systems, from laptops to supercomputer clusters. MPLBM-UT also features multiple examples and benchmark templates that allow for fast prototyping of different porous media problems. We also provide an interface for reading in different file types and downloading domains from the Digital Rocks Portal to perform simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

NanoPSD: A software for automatic detection of Nano-Particle Shape Distribution in electron microscopy images

Accurate quantification of the size and morphology of nanoparticles from electron microscopy (EM) images is essential to understand growth mechanisms, surface reactivity, and functional behavior in nanoscale materials. Manual analysis remains slow, subjective, and difficult to reproduce in large datasets. We introduce NanoPSD (Nano-Particle Shape Distribution), an open-source and fully automated framework for quantitative particle detection and morphology analysis from EM images. NanoPSD integrates adaptive contrast enhancement, polarity-agnostic scale-bar detection, Optical Character Recognition (OCR)-based calibration, and classical segmentation via Otsu thresholding with morphological refinement. Particle contours are used to extract geometric descriptors, including equivalent circular diameter, aspect ratio, circularity, and solidity, enabling automated classification into spherical, rod-like, and aggregate morphologies. The framework supports both single-image and batch processing, generating publication-quality visualizations, LaTeX-ready tables, and structured comma-separated values (CSV) datasets. As a demonstration, we applied NanoPSD to plasma-synthesized nanoparticle samples diagnosed via transmission electron microscopy (TEM). The code produced statistically robust size and morphology distributions spanning a few to tens of nanometers with minimal user supervision. The pipeline demonstrates high reproducibility and scalability, processing large image collections with consistent calibration and output formatting. Its modular design enables seamless integration of future deep-learning-based segmentation models, providing a pathway toward intelligent, data-driven electron microscopy analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Clear as mud redefined: Tunable transparent mineral scaffolds for visualizing microbial processes below ground

Microbes inhabiting complex porous microenvironments in sediments and aquifers catalyze reactions that are critical to global biogeochemical cycles and ecosystem health. However, the opacity and complexity of porous sediment and rock matrices have considerably hindered the study of microbial processes occurring within these habitats. Here, we generated microbially compatible, optically transparent mineral scaffolds to visualize and investigate microbial colonization and activities occurring in these environments, in laboratory settings and in situ. Using inexpensive synthetic cryolite mineral, we produced optically transparent scaffolds mimicking the complex 3D structure of sediments and rocks by adapting a suspension-based, freeze-casting technique commonly used in materials science. Fine-tuning of parameters, such as freezing rate and choice of solvent, provided full control of pore size and architecture. The combined effects of scaffold porosity and structure on the movement of microbe-sized particles, tested using velocity tracking of fluorescent beads, showed diverse yet reproducible behaviors. The scaffolds we produced are compatible with epifluorescence microscopy, allowing the fluorescence-based identification of colonizing microbes by DNA-based staining and fluorescence in situ hybridization (FISH) to depths of 100 µm. Additionally, Raman spectroscopy analysis indicates minimal background signal in regions used for measuring deuterium and 13 C enrichment in microorganisms, highlighting the potential to directly couple D 2 O or 13 C stable isotope probing and Raman-FISH for quantifying microbial activity at the single-cell level. To demonstrate the relevance of cryolite scaffolds for environmental field studies, we visualized their colonization by diverse microorganisms within rhizosphere sediments of a coastal seagrass plant using epifluorescence microscopy. The tool presented here enables highly resolved, spatially explicit, and multimodal investigations into the distribution, activities, and interactions of underground microbes typically obscured within opaque geological materials until now.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Self-reported health impacts of do-it-yourself air cleaner use in a smoke-impacted community

Smoke exposure from wildfires or residential wood burning for heat is a public health problem for many communities. Do-It-Yourself (DIY) portable air cleaners (PACs) are promoted as affordable alternatives to commercial PACs, but evidence of their effect on health outcomes is limited. Pilot test an evaluation of the effect of DIY PAC usage on self-reported symptoms, and investigate barriers and facilitators of PAC use, among members of a tribal community that routinely experiences elevated concentrations of fine particulate matter (PM 2.5 ) from smoke. We conducted studies in Fall 2021 (“wildfire study”; N = 10) and Winter 2022 (“wood stove study”; N = 17). Each study included four sequential one-to-two-week phases: 1) initial, 2) DIY PAC usage ≥8 h/day, 3) commercial PAC usage ≥8 h/day, and 4) air sensor with visual display and optional PAC use. We continuously monitored PAC usage and indoor/outdoor PM 2.5 concentrations in homes. Concluding each phase, we conducted phone surveys about participants’ symptoms, perceptions, and behaviors. We analyzed symptoms associated with PAC usage and conducted an analysis of indoor PM 2.5 concentrations as a mediating pathway using mixed effects multivariate linear regression. We categorized perceptions related to PACs into barriers and facilitators of use. No association was observed between PAC usage and symptoms, and the mediation analysis did not indicate that small observed trends were attributable to changes in indoor PM 2.5 concentrations. Small sample sizes hindered the ability to draw conclusions regarding the presence or absence of causal associations. DIY PAC usage was low; loud operating noise was a barrier to use. This research is novel in studying health effects of DIY PACs during wildfire and wood smoke exposures. Such research is needed to inform public health guidance. Recommendations for future studies on PAC use during smoke exposure include building flexibility of intervention timing into the study design.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Examining Perceptions of Spanish Language Health Information Among Hispanics Living in the United States: A Qualitative Study Assessing Videos, Brochures, and Websites

Background Nationally, Hispanics experience health disparities manifested as a higher prevalence of chronic diseases in comparison to non-Hispanic Whites. Factors that influence health disparities in this population include inadequate dissemination of culturally and linguistically appropriate health information. Method Our qualitative analysis is based on data obtained from three focus groups with Spanish-speaking Hispanic adults conducted at a clinic in Nebraska. Participants were asked about their perceptions of health information in the form of videos, brochures, and websites. We followed the consolidated criteria for reporting qualitative research and used the theoretical framework of content analysis. Results For videos, attributes associated with higher levels of trust included a friendly health professional, the logo or name of a health care institute, and a reference specifying “se habla Español.” For brochures, attributes associated with trust included use of visual aids, use of numerous colors and big font sizes, the year of printing, and a health care agency logo. For websites, characteristics associated with trust were inclusion of plain language, use of pictures and videos, and date of last update. In all focus groups, participants perceived the use of mixed English/Spanish language in health information from pamphlets and websites as unprofessional. The use of unknown governmental logos in health promotional videos and websites was perceived as untrustworthy information. Conclusions Spanish-speaking Hispanics prefer health information supported by a health care agency or delivered by a health care professional. Health communication strategies should avoid the use of mixed English/Spanish language in sensitive information especially when combined with governmental logos.

De Alba Rosales, Armando↗
DOE OSTI2025

bmdrc: Python package for quantifying phenotypes from chemical exposures with benchmark dose modeling

Though chemical exposures are known to potentially have negative impacts on health, including contributing to chronic diseases such as cancer, the quantitative contribution of risk is not fully understood for every chemical. A commonly used approach to quantify levels of risk is to measure the proportion of organisms (such as a total number of zebrafish on a plate or mice in a cage) with abnormal behavioral responses or morphology at increasing concentrations of chemical exposure. A particular challenge with processing the proportional data from these assays is the appropriate estimation of chemical concentration levels that result in malformations or acute toxicity, as these values typically vary between experimental measurements. The recommended approach by the Environmental Protection Agency (EPA) is to fit benchmark dose curves with specific filters and model fitting steps, which are crucial to properly processing the proportional data. Several tools exist for the fitting of benchmark dose response curves, but none are standalone Python libraries built to process both morphological and behavioral data as proportions with all the EPA recommended filters, filter parameters, models, and model parameters. Thus, here we present the benchmark dose response curve (bmdrc) Python library, which was built to closely follow these EPA guidelines with helpful visualizations of filters and fitted model curves, and reports for reproducibility purposes. bmdrc is open-source and has demonstrated utility as a support package to an existing web portal for information on chemicals (https://srp.pnnl.gov). Our package will support any toxicology analysis where the response is a proportional value at increasing levels of a concentration of a chemical or chemical mixture.

Superfund↗
DOE OSTI2021

X-Ray Spectra and Multiwavelength Machine Learning Classification for Likely Counterparts to Fermi 3FGL Unassociated Sources

We conduct X-ray spectral fits on 184 likely counterparts to Fermi-LAT 3FGL unassociated sources. Characterization and classification of these sources allows for more complete population studies of the high-energy sky. Most of these X-ray spectra are well fit by an absorbed power-law model, as expected for a population dominated by blazars and pulsars. A small subset of seven X-ray sources have spectra unlike the power law expected from a blazar or pulsar and may be linked to coincident stars or background emission. We develop a multiwavelength machine learning classifier to categorize unassociated sources into pulsars and blazars using gamma-ray and X-ray observations. Training a random forest (RF) procedure with known pulsars and blazars, we achieve a cross-validated classification accuracy of 98.6%. Applying the RF routine to the unassociated sources returned 126 likely blazar candidates (defined as P {sub bzr} ≥ 90%) and five likely pulsar candidates (P {sub bzr} ≤ 10%). Our new X-ray spectral analysis does not drastically alter the RF classifications of these sources compared to previous works, but it builds a more robust classification scheme and highlights the importance of X-ray spectral fitting. Our procedure can be further expanded with UV, visual, or radio spectral parameters or by measuring flux variability.

79 ASTRONOMY AND ASTROPHYSICS↗