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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Embedded sensors integrated into critical components for in situ health monitoring of steam turbines

Operational flexibility is desired in today’s coal-fired power plants to balance power grids by compensating for the variable electricity supply from renewable energy sources and distributed gensets. This demanding requirement accelerates materials degradation and makes in-situ health monitoring essential. Life monitoring of components and subsystems is thus seen as essential in assessing material and mechanical behavior to estimate system reliability, move to a conditionbased maintenance strategy and determine time to failure of the units in their actual operating conditions. Vibration monitoring can be exploited for blade tip timing to measure blade vibration amplitude and tip clearance to detect any deterioration taking place in the condition of steam turbine blades. A failure of a rotating blade can lead to severe turbine damage followed by extensive repairs and loss of power production. A blade vibration monitoring system can help early detection of abnormal blade vibration behavior. In conjunction with a health monitoring system, the vibration characteristics can be analyzed to support a pro-active maintenance and inspection schedule. While the feasibility of this inspection technique has been amply demonstrated, there is a need to install induction probes to magnetize the blade for signal output. Siemens, in partnership with Raytheon Technologies Research Corporation (RTRC), proposes a holistic approach to develop embedded sensors to utilize radio frequency for not only coupling to sensors, but as the sensing modality. The goal of this project is to “embed” the novel sensing approach by using either additively manufactured or extruded waveguides on rotating blades for recording, evaluation and monitoring of blade vibrations in Low Pressure turbines, with applications extending to aero engines

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

High-precision monitoring of outgassing species in model extreme ultraviolet photoresists with a cavity ring-down spectrometer

Background Extreme ultraviolet (EUV) photoresists play a pivotal role in advancing nanopatterning technologies by balancing image quality and sensitivity. The outgassing behavior of photoresist thin films under EUV and deep ultraviolet (DUV) exposure reveals chemical details relevant to their performance. Aim Here, we focus on utilizing an analytical technique not previously used in photolithography, the tabletop cavity ring-down spectrometer, to investigate outgassing dynamics in EUV photoresists, enabling precise chemical identification and deeper insights into resist processing. Approach The spectrometer’s enhanced laser path length (∼ 20 km) and broadband absorption capabilities in the C–H overtone region allow for sensitive and temporally resolved detection of mixtures of outgassed species. Using a model resist comprising a polymer matrix with a photoacid generator and quencher, we analyzed the influence of time delays between exposure and post-exposure bake (PEB) as well as storage under varying environmental conditions. Results Suppression of isobutylene outgassing and thickness loss was observed with extended delays between exposure and PEB, potentially linked to water absorption and acid deactivation. The technique proved highly effective in distinguishing subtle chemical differences between processing stages. Conclusions Delay times and their environmental conditions, particularly humidity, reduce outgassing and thickness loss of photoresists during PEB, suggesting decreased acid-driven deprotection. This can potentially impact sensitivity, defectivity, and roughness of resist patterns, necessitating precise monitoring and control.

Extreme ultraviolet photoresists↗
DOE OSTI2024

Creating Accurate Methane Emission Inventories through Data-Driven Airborne Survey Strategies: Methods and Results from the Haynesville, Anadarko, and Permian Basins

Significantly reducing methane emissions from the oil and gas sector can decrease the rate of climate change over the next two decades, buying critical time for a global energy transition. However, emissions inventories that can be used by oil and gas operators and environmental regulators to identify optimal methane emission mitigation strategies are either based on conservative emission factor methods, or are inconsistent between studies due to differences in sampling strategies or survey technologies. We developed a new approach for methane emissions survey design that yields representative basinwide methane emissions inventories by surveying a subset of total assets in a given oil and gas basin. We identify several sampling and analysis principles, including large sample sizes, balanced sampling across oil and gas production, careful survey area definition, and a unified protocol for analysis, to be vital to producing an unbiased estimate of basin-scale emissions that can be reconciled with future studies. We further present results from deploying this strategy in two oil and gas producing regions in the United States: the Haynesville Basin in Texas and Louisiana, and the Woodford Shale in the Anadarko Basin in Oklahoma. Aerial surveys were performed in 2023 using the Insight M LeakSurveyor™ technology. Preliminary results from methane emissions detected by Insight M indicate that aerially detected emissions above roughly 30 kg(CH4)/hr by themselves contribute a fractional loss rate of 1.13% of gross gas production across oil and gas operations in the Haynesville Basin, with aerially detected emissions equivalent to 2.67% of gross gas production in the Woodford Shale. We supplement these aerial estimates with modeled emissions that are below the LeakSurveyor’s survey sensitivity using a recently published inventory-based model of methane emissions, which we update for our survey areas. We then combine our aerial detections with modeled emissions to yield methane emission distributions and inventories that incorporate the full range of potential methane emissions from the smallest to the largest. These results can be used to identify the most effective methane mitigation strategies for our study areas, and can be reconciled with future methane emissions surveys that use different technologies.

Sherwin, Evan (ORCID:0000000321804297)↗
DOE OSTI2023

High‐Latitude Stratospheric Aerosol Injection to Preserve the Arctic

Abstract Stratospheric aerosol injection (SAI) has been shown in climate models to reduce some impacts of global warming in the Arctic, including the loss of sea ice, permafrost thaw, and reduction of Greenland Ice Sheet (GrIS) mass; SAI at high latitudes could preferentially target these impacts. In this study, we use the Community Earth System Model to simulate two Arctic‐focused SAI strategies, which inject at 60°N latitude each spring with injection rates adjusted to either maintain September Arctic sea ice at 2030 levels (“Arctic Low”) or restore it to 2010 levels (“Arctic High”). Both simulations maintain or restore September sea ice to within 10% of their respective targets, reduce permafrost thaw, and increase GrIS surface mass balance by reducing runoff. Arctic High reduces these impacts more effectively than a globally focused SAI strategy that injects similar quantities of SO 2 at lower latitudes. However, Arctic‐focused SAI is not merely a “reset button” for the Arctic climate, but brings about a novel climate state, including changes to the seasonal cycles of Northern Hemisphere temperature and sea ice and less high‐latitude carbon uptake relative to SSP2‐4.5. Additionally, while Arctic‐focused SAI produces the most cooling near the pole, its effects are not confined to the Arctic, including detectable cooling throughout most of the northern hemisphere for both simulations, increased mid‐latitude sulfur deposition, and a southward shift of the location of the Intertropical Convergence Zone. For these reasons, it would be incorrect to consider Arctic‐focused SAI as “local” geoengineering, even when compared to a globally focused strategy.

Lee, Walker Raymond↗
DOE OSTI2022

Removal of Bond Sodium from Full-Length Unirradiated Fermi-1 Blanket Elements and Assembly via Melt-Drain-Evaporate Process

Equipment was designed, fabricated, tested, and operated in an inert atmosphere radiological glovebox at Idaho National Laboratory to demonstrate the removal of bond sodium from full-length unirradiated Fermi-1 radial blanket elements and an entire radial blanket assembly using a Melt-Drain-Evaporate process. A series of three runs was performed with individual and multiple radial Fermi-1 blanket elements, and a fourth run was conducted with an entire Fermi-1 radial blanket assembly. After each run, the depleted uranium alloy slugs in every element slid out of its cladding, mechanically exhibiting the effectual absence of bond sodium. Quantitative and further qualitative analyses of the treated Fermi-1 material revealed the substantive, if not complete, absence of sodium metal in blanket element components. Indeed, entire columns of depleted uranium alloy slugs and associated cladding from select treated elements were separately contacted with water to react with residual sodium metal on the element surfaces, forming hydrogen gas. Samples of the resultant gas were analyzed to quantify the hydrogen concentration, which correlated to a residual sodium metal content for the treated element. Accordingly, no detectable sodium metal (<7 µg) was found on the surfaces of multiple depleted uranium alloy slugs after removal from its cladding. Detectable sodium metal, ranging from 14 to 30 µg, was found on the surfaces of one separated column of slugs and two separated full-length cladding segments. Each element originally contained ~25 g of bond sodium, resulting in quantitative sodium metal removal efficiencies of =99.9998%. The remaining separated uranium alloy slugs and cladding segments from the four runs were piece-wise immersed in alcohol while videorecording possible gas bubble formation as an additional qualitative analysis for residual sodium metal on treated surfaces, which identified the predominant absence of sodium reactivity on the balance of treated Fermi-1 blanket material. The results of this demonstration substantiate a path forward for treatment and disposal of 34 metric tons heavy metal of irradiated sodium-bonded Fermi-1 blanket material currently stored at Idaho National Laboratory.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Facile Measurement of the Rotation of a Single Optically Trapped Nanoparticle Using the Diagonal Ratio of a Quadrant Photodiode

Optical tweezers are a powerful tool for exploring physical properties of particles in various environments through analysis of their dynamics in a trapping potential. Analysis of the trapped particle's position is often done using interferometric back-focal-plane detection microscopy in which interference between the trapping laser and the light interacting with the trapped particle is projected on a quadrant photo-diode (QPD). The QPD measurements are almost universally the voltage ratios between the transverse components of the detector (left/right; up/down) that are calibrated to ascertain particle positions and orientations (i.e., rotation). In this paper, we demonstrate how measuring the diagonal ratio of the QPD allows tracking the spinning and orbital motion of optically trapped objects with enhanced sensitivity compared to the conventional transverse ratio and reveals additional information about particle dynamics. The diagonal ratio "balances" the signal from opposite sides of the QPD, allowing common mode noise reduction and increased measurement sensitivity of the rotating nanospheres at frequencies from below 200 Hz to above 15 kHz. We show that the variability in particle rotation rates is due to slight differences in the aspect ratio of the nanoparticles. We also measure in situ a gradual acceleration in the spinning frequency of trapped nanoparticles due to photothermal shedding of surface ligands and the resulting decrease of rotational friction in solution. The accelerating particles spin at rates exceeding 30 kHz and are eventually "optically printed" onto the glass coverslip on top of the liquid cell enclosure. The diagonal ratio is a simple, readily available, and powerful enabler for measuring rotational dynamics with a 5-fold sensitivity increase over conventional QPD measurements. This affords opportunities for controlling the orientational dynamics of trapped nanoparticles, which is crucial for various applications, including nanoscale mechanical motors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

The JmjC-domain protein NO66/RIOX-1 affects the balance between proliferation and maturation in acute myeloid leukemia

Highlights: • NO66/RIOX1 is not expressed in the AML cell line KG1a regarded as a “stem cell-like” model system. • NO66/RIOX1 is not expressed in primary HSC-enriched CD34{sup +}/CD38{sup -} cells of healthy donors. • Ectopic expression of NO66/RIOX1 in KG1a cells inhibits proliferation and rDNA transcription. • NO66/RIOX1 impacts on the transition from stem cells to progenitors by regulation of gene expression. As epigenetic regulators are frequently dysregulated in acute myeloid leukemia (AML) we determined expression levels of the JmjC-protein NO66 in AML cell lines and sub fractions of healthy human hematopoietic cells. NO66 is absent in the AML cell lines KG1/KG1a which consist of cells with the immature CD34{sup +}/CD38{sup -} phenotype and is regarded as a “stem cell-like” model system. Similarly, NO66 is not detectable in CD34{sup +}/CD38{sup -} cells purified from healthy donors but is clearly expressed in the more committed CD34{sup +}/CD38{sup +} cell population. Loss of NO66 expression in KG1/KG1a cells is due to hyper-methylation of its promoter and is released by DNA-methyltransferase inhibitors. In KG1a cells stably expressing exogenous wild type (KG1a66wt) or enzymatically inactive mutant (KG1a66mut) NO66, respectively, the wild type protein inhibited proliferation and rDNA transcription. Gene expression profiling revealed that the expression of NO66 induces a transcriptional program enriched for genes with roles in proliferation and maturation (e.g.EPDR1, FCER1A, CD247, MYCN, SNORD13). Genes important for the maintenance of stem cell properties are downregulated (e.g. SIRPA, Lin28B, JAML). Our results indicate that NO66 induces lineage commitment towards myeloid progenitor cell fate and suggest that NO66 contributes to loss of stem cell properties.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Getting to the Root of Plant–Mediated Methane Emissions and Oxidation in a Thermokarst Bog

Vascular plants are important in the wetland methane cycle, but their effect on production, oxidation, and transport has high uncertainty, limiting our ability to predict emissions. In a permafrost–thaw bog in Interior Alaska, we used plant manipulation treatments, field–deployed planar optical oxygen sensors, direct measurements of methane oxidation, and microbial DNA analyses to disentangle mechanisms by which vascular vegetation affect methane emissions. Vegetation operated on top of baseline methane emissions, which varied with proximity to the thawing permafrost margin. Emissions from vegetated plots increased over the season, resulting in cumulative seasonal methane emissions that were 4.1–5.2 g m –2 season –1 greater than unvegetated plots. Mass balance calculations signify these greater emissions were due to increased methane production (3.0–3.5 g m –2 season –1 ) and decreased methane oxidation (1.1–1.6 g m –2 season –1 ). Minimal oxidation occurred along the plant–transport pathway, and oxidation was suppressed outside the plant pathway. Our data indicate suppression of methane oxidation was stimulated by root exudates fueling competition among microbes for electron acceptors. This contention is supported by the fact that methane oxidation and relative abundance of methanotrophs decreased over the season in the presence of vegetation, but methane oxidation remained steady in unvegetated treatments; oxygen was not detected around plant roots but was detected around silicone tubes mimicking aerenchyma; and oxygen injection experiments suggested that oxygen consumption was faster in the presence of vascular vegetation. In conclusion, root exudates are known to fuel methane production, and our work provides evidence they also decrease methane oxidation.

58 GEOSCIENCES↗
DOE OSTI2025

Sorted-cell proteomics reveals an AT1-associated epithelial cornification phenotype and suggests endothelial redox imbalance in human bronchopulmonary dysplasia

Bronchopulmonary dysplasia (BPD) is a neonatal lung disease characterized by inflammation and scarring leading to long-term tissue damage. Previous whole tissue proteomics identified BPD-specific proteome changes and cell type shifts. Little is known about the proteome-level changes within specific cell populations in disease. Here, we sorted epithelial (EPI) and endothelial (ENDO) cell populations based on their differential surface markers from normal and BPD human lungs. Using a low-input compatible sample preparation method (MicroPOT), proteins were extracted and digested into peptides and subjected to liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteome analysis. Of the 4,970 proteins detected, 293 were modulated in abundance or detection in the EPI population and 422 were modulated in ENDO cells. Modulation of proteins associated with actin-cytoskeletal function, such as SCEL, LMO7, and TBA1B was observed in the BPD EPIs. Using confocal imaging and analysis, we validated the presence of aberrant multilayer-like structures comprising SCEL and LMO7, known to be associated with epidermal cornification, in the human BPD lung. This is the first report of the accumulation of cornification-associated proteins in BPD. Their localization in the alveolar parenchyma, primarily associated with alveolar type 1 (AT1) cells, suggests a role in the BPD postinjury response. In the ENDOs, redox balance and mitochondrial function pathways were modulated. Alternative mRNA splicing and cell proliferative functions were elevated in both populations, suggesting potential dysregulation of cell progenitor fate. This study characterized the proteome of epithelial and endothelial cells from the BPD lung for the first time, identifying population-specific changes in BPD pathogenesis.

BPD↗
DOE OSTI2022

Metallic Technetium Sequestration in Nickel Core/Shell Microstructure during Fe(OH)2 Transformation with Ni doping

This study investigates the impacts of Ni doping on technetium-99 (Tc) sequestration in aqueous solutions through transformation of Fe(OH)2(s) to iron spinel (magnetite) under alkaline conditions. Extensive solid characterization was performed for the mineral phases produced, as well as the Tc/Ni speciation and distribution within these phases. X-ray diffraction results show that iron spinel was the dominant mineral product without detectable Ni incorporation. The doped Ni ions mainly precipitated as fine Fe/Ni oxide/hydroxide particles, including strongly reduced nanometer?sized spheroidal Ni-rich and metallic Ni phases. High-resolution analytical scanning transmission electron microscopy using energy dispersive X-ray spectroscopy and electron energy loss spectroscopy on the produced solid samples (focused ion beam-prepared specimens) revealed three Tc distribution domains dominated by nanocrystals and, especially, a Tc-rich metallic phase. Instances of metallic Tc were specifically found in spheroidal, Ni-rich and metallic nanoparticles exhibiting a core/shell microstructure that suggests strong reduction and sequential precipitation of Ni-Tc-Ni. Mass balance analysis showed nearly 100% Tc removal from the 4.8 × 10-4 M Tc solutions. The finding of the metallic Tc encapsulation indicates that Tc sequestration through Ni-doped Fe(OH)2(s)?to?iron spinel transformation process likely provides an alternative treatment pathway for Tc removal and could be combined into further waste treatment approaches.

Wang, Guohui↗
DOE OSTI2020

Hybrid Analytics Solution for Power Plant Operations

Expert Microsystems, Inc., MapEx Software Inc. and XMPLR Energy LLC have teamed to submit a proposal to the US Department of Energy’s Office of Fossil Energy to improve the efficiency, reliability and flexibility of existing coal-based power plants. The project, titled Hybrid Analytics Solution to Improve Coal Power Plant Operations (the “Hybrid Analytics” project), will develop, demonstrate and commercialize a novel approach that integrates two proven real-time monitoring techniques. The Hybrid Analytics approach integrates into a single, integrated solution: a) an established, advanced data-driven analytics solution that includes artificial intelligence, advanced pattern recognition and machine-learning techniques and b) a well-proven, first principle thermal heat balance model solution. The future role of coal plants will depend on the ability to cycle and follow loads to meet marginal power demands, accommodate renewables and support the grid. Essential to success in this new role is a plant’s ability to maintain high reliability, efficiency and flexibility. However, these changing operational demands put significant stresses on power plant components that directly impact the ability to deliver these requirements. In the past, plants have independently monitored performance using physics-based solutions (heat rate, boiler losses, etc.) and reliability using data-driven analytics (advanced pattern recognition). The Hybrid Analytics solution integrates both approaches to enhance fault detection, provide automated diagnostics and estimates of remaining time to act, and provide critical, enhanced and accurate real-time information to coal plant operators. As a result, coal plants can improve efficiency, reliability, and flexibility and can cost-effectively maintain their key role in the power delivery system.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

The electrode–electrolyte interface of Cu via modulation excitation X-ray absorption spectroscopy

The development and application of modulation excitation X-ray absorption spectroscopy with sub-second resolution and better than 0.02% detection sensitivity unveils the kinetics of the anodic oxidation of Cu in bicarbonate electrolytes. Accessing the electrode–electrolyte interface under operating conditions and capturing time-resolved kinetics remain challenging in electrochemical studies. Copper's interfacial oxidation dynamics remain unclear despite extensive research. Modulation excitation X-ray absorption spectroscopy (ME-XAS) was used to probe Cu in 100 mM KHCO 3 with sub-second sensitivity, revealing that hydroxide forms 30 ± 10 ms before the appearance of Cu 2 O at positive potentials (0 to 0.5 V vs. RHE) near open-circuit conditions. From −0.4 to 0.8 V vs. RHE, hydroxide coverage reaches 49%, accompanied by a balanced presence of Cu( i ) and Cu( ii ) oxides. These insights into Cu interfacial redox behavior under intermittent renewable energy operation—relevant to CO 2 electrolyzer durability—enhance our fundamental understanding of electrochemical interfaces.

Garcia-Esparza, Angel T↗
DOE OSTI2026

CHESS 2025: Orthorectified airborne RGB imagery from NEON AOP surveys

This dataset provides Level 1 (L1) and Level 3 (L3) orthorectified Red-Green-Blue (RGB) imagery collected for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). This high-resolution imagery is a photographic record of red, green, and blue visible light from sunlight reflected off of the Earth’s surface. The data comprise full-color images of the ground surface and are primarily intended to provide context to imaging spectroscopy and light detection and ranging (LiDAR) data. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. RGB images were acquired using the PhaseOne IXM-RS150F high-resolution digital camera onboard the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP). The package data include both an L1 product comprising one camera frame per file and an L3 mosaic aligned to the Universal Transverse Mercator (UTM) Zone 13N grid and the World Geodetic System (WGS) 84 projection. Both products are provided in geotif (.tif) format at 0.1 m ground resolution. The bulk of the imagery was collected during the main CHESS field campaign from June 13 to July 15, 2025. Additional images of a portion of the Upper Taylor (UPTA) domain were collected on September 18, 2025, to fill gaps in imagery identified after the main campaign was complete. RGB camera imagery is not radiometrically calibrated, and therefore pixel values should not be exploited for scientific analysis. Pixel values have undergone a manual adjustment to enhance feature identification. The imagery is rigorously geolocated which does allow for reliable geometric information to be retrieved. To generate the orthorectified imagery, the NEON AOP camera captured visible spectrum in red, green, and blue bands. The raw images were then processed using NEON’s camera orthorectification workflow. A boresight calibration flight was made to build a complete camera, distortion, and alignment model. Color balance/white balance and exposure correction were applied to the raw RGB images. The corrected images were orthorectified by ray-tracing image pixels to a lidar-derived digital surface model (DSM) mesh using the refined camera model, outputting orthorectified raster pixels on a regular grid. Flightline-level data were mosaicked by selecting per-pixel contributions from overlapping orthorectified images using line-of-sight (LOS) zenith angle minimization to reduce edge distortions. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2024

Daily Arctic Lightning Strokes

In recent decades, lightning activity at high latitudes has increased. Tall thunderstorm clouds affect radiation balance directly, as well as indirectly through lightning-initiated fires and the resulting smoke. One can remotely sense lightning strokes over the globe through their VLF radio emission, and, with multiple receivers, it is possible to precisely locate lightning strokes. This technique makes it possible to continuously monitor arctic lightning--a capability not possible by other means. In this research effort, a World-Wide Lightning Location Network station, consisting of a VLF receiver, signal processing hardware, and analysis software, were installed at the North Slope of Alaska (NSA) facility and planned to operate for several years. This far north location is expected to improve the network's high-latitude detection efficiency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Machine learning prediction of incidence of Alzheimer’s disease using large-scale administrative health data

Nationwide population-based cohort provides a new opportunity to build an automated risk prediction model based on individuals’ history of health and healthcare beyond existing risk prediction models. We tested the possibility of machine learning models to predict future incidence of Alzheimer’s disease (AD) using large-scale administrative health data. From the Korean National Health Insurance Service database between 2002 and 2010, we obtained de-identified health data in elders above 65 years (N = 40,736) containing 4,894 unique clinical features including ICD-10 codes, medication codes, laboratory values, history of personal and family illness and socio-demographics. To define incident AD we considered two operational definitions: “definite AD” with diagnostic codes and dementia medication (n = 614) and “probable AD” with only diagnosis (n = 2026). We trained and validated random forest, support vector machine and logistic regression to predict incident AD in 1, 2, 3, and 4 subsequent years. For predicting future incidence of AD in balanced samples (bootstrapping), the machine learning models showed reasonable performance in 1-year prediction with AUC of 0.775 and 0.759, based on “definite AD” and “probable AD” outcomes, respectively; in 2-year, 0.730 and 0.693; in 3-year, 0.677 and 0.644; in 4-year, 0.725 and 0.683. The results were similar when the entire (unbalanced) samples were used. Important clinical features selected in logistic regression included hemoglobin level, age and urine protein level. This study may shed a light on the utility of the data-driven machine learning model based on large-scale administrative health data in AD risk prediction, which may enable better selection of individuals at risk for AD in clinical trials or early detection in clinical settings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Alert Classification for the ALeRCE Broker System: The Light Curve Classifier

We present the first version of the Automatic Learning for the Rapid Classification of Events (ALeRCE) broker light curve classifier. ALeRCE is currently processing the Zwicky Transient Facility (ZTF) alert stream, in preparation for the Vera C. Rubin Observatory. The ALeRCE light curve classifier uses variability features computed from the ZTF alert stream and colors obtained from AllWISE and ZTF photometry. We apply a balanced random forest algorithm with a two-level scheme where the top level classifies each source as periodic, stochastic, or transient, and the bottom level further resolves each of these hierarchical classes among 15 total classes. This classifier corresponds to the first attempt to classify multiple classes of stochastic variables (including core- and host-dominated active galactic nuclei, blazars, young stellar objects, and cataclysmic variables) in addition to different classes of periodic and transient sources, using real data. We created a labeled set using various public catalogs (such as the Catalina Surveys and Gaia DR2 variable stars catalogs, and the Million Quasars catalog), and we classify all objects with ≥6 g-band or ≥6 r-band detections in ZTF (868,371 sources as of 2020 June 9), providing updated classifications for sources with new alerts every day. For the top level we obtain macro-averaged precision and recall scores of 0.96 and 0.99, respectively, and for the bottom level we obtain macro-averaged precision and recall scores of 0.57 and 0.76, respectively. Updated classifications from the light curve classifier can be found at the ALeRCE Explorer website (http://alerce.online).

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

IAEA Photonuclear Data Library 2019

Here, photo-induced reaction cross section data are of importance for a variety of current or emerging applications, such as radiation shielding design and radiation transport analyses, calculations of absorbed dose in the human body during radiotherapy, physics and technology of fission reactors (influence of photo-reactions on neutron balance) and fusion reactors (plasma diagnostics and shielding), activation analyses, safeguards and inspection technologies, nuclear waste transmutation, medical isotope production and astrophysical applications. To address these data needs the IAEA Photonuclear Data library was produced in 1999, containing evaluated photo-induced cross sections and neutron spectra for 164 nuclides which were deemed relevant for the applications. Since the release of the IAEA Photonuclear Data Library however, new experimental data as well as new methods to assess the reliability of experimental cross sections have become available. Theoretical models and input parameters used to evaluate photo-induced reactions have improved significantly over the years. In addition, new measurements of partial photoneutron cross sections using mono-energetic photon beams and advanced neutron detection systems have been performed allowing for the validation of the evaluations and assessments of the experimental data. Furthermore, technological advances have led to the construction of new and more powerful gamma-beam facilities, therefore new data needs are emerging. We report our coordinated efforts to address these data needs and present the results of the new up-to-date evaluations included in the new updated IAEA Photonuclear Data Library consisting of 219 nuclides. The new library includes 188 new evaluations produced by the CRP evaluators, and one evaluation taken from the JENDL/PD-2016 library, while 20 evaluations were retained from the previous 1999 IAEA Photonuclear Data Library. In most of the cases, the photon energy goes up to 200 MeV. A total of 55 nuclides are new in this library reflecting the progress in measurements but also the developing data needs. In this paper we discuss the new assessment method and make recommendations to the user community in cases where the experimental data are discrepant and the assessments disagree. In addition, in the absence of experimental data, we present model predictions for photo-induced reaction cross section on nuclides of potential interest to medical radioisotope production.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Structural evolution during solution-based synthesis of Li 7 P 3 S 11 solid electrolyte by synchrotron X-ray total scattering

Solution-based synthesis has emerged as a promising approach for scalable and efficient synthesis of solid electrolytes (SEs). However, the ionic conductivity of solution-synthesized SEs is much lower than that of SEs synthesized by solid state approaches. The structural evolution during the synthesis of SEs is crucial to explaining the decreased ionic conductivities but has not been well understood. Here, in this work, we use synchrotron X-ray total scattering combined with pair distribution function (PDF) analysis to understand the structural evolution during annealing of the solution-processed precursor for the synthesis of Li 7 P 3 S 11 SEs. Combining Bragg diffraction and diffuse scattering, X-ray total scattering enables detection of structural information including phase transition and crystallinity. The results show that the formation of Li 7 P 3 S 11 glass-ceramic starts at 230 °C. Increasing the annealing temperature helps to improve the crystallinity, but the degree of crystallization is still lower than 70.3% even after annealing at 290 °C when thermal decomposition of Li 7 P 3 S 11 to Li 4 P 2 S 6 has occurred. PDF analysis also revealed the existence of acetonitrile used in the solution-based synthesis in the SEs after annealing at high temperatures. The results rationalize the synthesis–property relationship, explain why annealing at 290 °C provides the highest ionic conductivity at the studied temperatures due to an optimal balance for achieving a high crystallinity while suppressing severe decomposition of Li 7 P 3 S 11 , and provide novel insights to develop approaches for synthesizing superior Li 7 P 3 S 11 SEs on a large scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗