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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Soil Sample Workplan in Support of the Site 300 Explosives Waste Treatment Facility Ecological Risk Assessment Pursuant to the Hazardous Waste Facility Permit (Part V, Special Condition #14 a-f)

The Department of Toxic Substances Control issued the Final Hazardous Waste Facility Permit to Lawrence Livermore National Laboratory, Site 300 in 2017. As part of the continual process to ensure waste treatment emissions are not impacting ecological receptors, LLNL analyzed soil samples in the vicinity of the Explosive Waste Treatment Facility (EWTF) Burn Units (i.e., Burn Cage and Burn Pan) and the Detonation Pad. Soil samples were analyzed by EPA Solid Waste 846 Methods for furans, explosives, metals, and semi-volatile compounds. In all samples, furans, explosives, and semi-volatile organic compounds were not detected. Metals were detected at concentrations below background levels. This soil sample plan will sample the same four downwind areas of the Burn Units and the same downwind areas of the Detonation, as well as including four new sample locations. The four new locations will be located to the northeast and southwest of the Burn Units and Detonation (as shown in Figure 3). The constituents to be analyzed are in Tables 7 and 8. Perchlorate was not identified as a constituent of concern in the 2007 Soil Sampling Plan. However, for this plan, all soil samples will be analyzed for perchlorate. Nitrate and all CAM17 metals have been added to the sampling plan to comply with DTSC comments received in correspondence dated June 4, 2021. After completion of the sampling event, a soil sample report will be submitted to DTSC in accordance with requirements specified in the Hazardous Waste Facility Permit, Part V, Special Conditions 16 a-f. This proposed soil sampling plan will be fully implemented no later than one year after receiving DTSC approval, in accordance with the Hazardous Waste Facility Permit, Part V, Special Condition 15.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Fuels Characterization for National Research Council Canada 2-m Pool Fire Test Series

This report provides a detailed analysis of the physical and chemical properties of three liquid hydrocarbon fuels: heptane, Bakken crude, and a diluted bitumen, that were subsequently tested in a series of 2-m pool fire experiments at Sandia National Laboratories for the National Research Council Canada. Properties such as relative density, vapor pressure (VPCR x ), composition, and heat of combustion were evaluated. The heptane analysis, with relative density = 0.69 (at 15°C), confirmed that the material tested was consistent with high-purity (>99%) n-heptane. The Bakken crude, with a relative density = 0.81 (at 15°C), exhibited a vapor pressure by VPCR 0.2 (37.8°C) in the range 120-157 kPa. The dilbit, with a relative density = 0.92 (at 15°C) exhibited a vapor pressure by VPCR 0.2 (37.8°C) in the range 85-98 kPa. Solids remaining in the test pans after the pool fires were also collected and weighed. No detectable solids were left after the heptane burns. In contrast, the crude oils left some brittle, black solid residue. On average, dilbit pool fires left about 40 more residue by mass than Bakken pool fires for equivalent mass of fuel feed.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Characterization of CST Post-Processing AP-105 Hanford Tank Waste

The primary goal of the Tank Side Cesium Removal (TSCR) system, under development by Washington River Protection Solutions, LLC (WRPS), is to remove entrained solids and 137 Cs from the Hanford tank waste supernate to expedite production of low-activity waste. Ion exchange (IX) testing of 10.9 L of waste from Hanford tank 241-AP-105 (AP-105), performed by Pacific Northwest National Laboratory, used a lead-lag-polish column format, with a bed volume of 10 mL per column, to decontaminate tank waste supernate using crystalline silicotitanate (CST) as the IX media. The AP-105 Cs IX processing test, discussed elsewhere, resulted in a shorter transition zone (i.e., steeper load curve) than those defined by wastes from tanks 241-AP-107 and 241-AW-102.1 The shorter transition zone was indicative of a matrix effect retarding Cs capacity. Therefore, aliquots of spent CST from the lead, lag, and polish columns were subjected to a digestion protocol to quantify analytes retained by the CST and extrapolate the impact on Cs capacity. The spent CST was digested using a combination of 5 M HNO 3 and H 2 O 2 with vigorous heating and stirring. Due to the radiation dose accompanying the 137 Cs on the CST columns, a secondary Cs separation by ammonium molybdophosphate embedded in polyacrylonitrile (AMP-PAN) was performed to separate the 137 Cs from the CST so the samples could be contact-handled for analysis outside of a shielded facility.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Examining the Ice Nucleating Particles from Southern Great Plains Part II (ExINP-SGP). Field Campaign Report

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, recent INP measurements at the Southern Great Plains observatory (SGP; 36'' 36' 18→ N, 97° 29' 6'' W) during multiple campaigns, such as SINCE-2014 (DeMott et al. 2015), Examining the Ice-Nucleating Particles from SGP (ExINP-2019; Hiranuma and Vepuri 2020), and Aerosol-Ice Formation Closure Pilot Study (AEROICESTUDY; Knopf et al. 2021a), strongly suggested the contribution of supermicron aerosol particles to observed INP abundance at SGP. However, verification of this hypothesis was hampered since additional offline laboratory analyses require sufficient amounts of collected airborne PM, which was lacking. Therefore, the principal investigators (PIs) conducted a field campaign, named ExINP-SGP II, to collect airborne PM at SGP for complementary laboratory characterization of the particles’ physicochemical properties (including ice nucleation properties). We used a passive particle sampler, which is a 4’ x 4’ x 2” (L x W x D) aluminum pan inside the 12”-high wooden windshield wall at the rooftop deck of the ARM Aerosol Observing System (AOS) trailer to collect dry PM deposits from January to April 2021. Figure 1 shows images of our experimental setup at the site. Additionally, we also collected surface soil near the ARM AOS trailer on 20 November 2020 (Figure 1b) to examine the ground soil dust particles (< 63 µm sieved) for their propensities to initiate immersion freezing compared to collected ambient PM. Surface soil and airborne samples were stored in the chemically inert container separately and kept in a dry, cool place until analyzed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Experimental Validation and Continuous Testing of an On-Purpose High-Yield Pitch Synthesis Process for Producing Carbon Fiber from US Domestic Coal

This project aims to develop technology that converts domestic United States (US) raw coal to high quality, high value, and marketable carbon fiber. More specifically, the project aims to significantly improve the selectivity and yield of carbon fiber produced per ton of coal over conventional coal pitch-based production by using low-severity direct coal conversion technology to maximize the yield of pitch from coal, suitable for production of carbon fiber. To meet the stated objective of developing a technology platform, capable of producing high quality, high-value and marketable carbon fiber from domestic US coal, the proposed scope of work involves testing of a low-severity direct coal liquefaction (LS-DCL) process approach. The isotropic pitch produced from the LS-DCL process will be thermally treated using conventional processes to convert to a liquid crystal or “mesophase” pitch as a precursor for structural carbon fibers. This mesophase pitch will then be melt-spun into fiber, oxygen stabilized, and carbonized using conventional processes. The resulting carbon fiber will be evaluated for mechanical properties and suitability for structural applications such as automotive parts and spars for wind turbine blades. The overall process is expected to significantly lower the cost of fiber compared to state of the art fibers produced from polyacrylonitrile (PAN) precursors.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Automated, Unmanned Detection and Quantification of Fugitive Methane Emissions

Compressor stations used to move natural gas are one of the largest sources of fugitive methane emissions in the midstream sector, accounting for approximately 50% of all fugitive emissions (Zimmerle et al., 2015). This problem is most widespread at reciprocating compressors (Subramanian et al., 2015) where faulty seals are a key contributor to methane emissions (Johnson et al., 2015). As such, there is a significant need for a robust technology that could provide an early indication of an unexpected emission. Equally important, the technology needs to be able to account for biogenic versus anthropogenic sources of methane. One means of indirectly making this determination, is to leverage optical technologies that can autonomously pinpoint the source of such leaks. This presentation discusses recent work funded by the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL), focused on the development of an innovative remote sensing technology that can reliably and autonomously detect fugitive methane emissions in near real-time, using computer vision and deep learning. The technology called the Smart Methane Leak Detection (SLED/M) system was initially developed to monitor facilities such as compressor stations in a stationary, pan-tilt-zoom configuration. The system has recently been adapted to monitor facilities from an unmanned aerial system (UAS). The speed and maneuverability of UAS platforms are attractive to leak detection and repair program operators, but introduce several challenges. Many existing methane detection algorithms rely on mostly static backgrounds becoming unusable with motion. In addition, top-down views of fugitive methane emissions present differently in Optical Gas Imagers (OGI) compared to looking across the plume. Our work has focused on overcoming these challenges, enhancing the operators ability to detect methane emissions, and pinpoint their sources. Another recent adaptation to SLED/M is the ability to quantify methane emissions using passive sensors (OGI, thermal camera), environmental conditions, plume modeling, and deep learning. SLED/M advances the state-of-the-art for methane emission detection and quantification by focusing on three key critical criteria for effective methane emission mitigation: (1) autonomy (no need for a human to be in the loop), (2) high reliability (low false alarm rates), and (3) real-time performance. Results from this work will be presented.

03 NATURAL GAS↗
DOE OSTI2024

Annual Report for Structure-Aware Unsupervised, Transformational Machine Learning for Drug Discovery

The major goal of this project is to develop machine learning (ML) methods to enable improved predictive power on real drug discovery for novel targets. More specifically, we plan to demonstrate the capability and effectiveness of ML tools utilizing unlabeled large-volume protein-ligand datasets. We also plan to demonstrate the capability and effectiveness of the developed methods by testing on a realistic drug discovery task to identify pan-coronavirus protease inhibitors such as SARS-CoV-2. While the overall goals and milestones remain consistent with the original proposal, certain technical details have been modified, which we will describe in this report.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Filament Formation and Melt Spinning of Coal-Based Mesophase Pitch for Carbon Fiber Production

High-performance carbon fibers excel as high specific strength and modulus materials, and are utilized in composites applications ranging across aerospace, automotive, energy, infrastructure, and sports equipment sectors. Compared to PAN-based carbon fiber, mesophase pitch-based carbon fiber has lower tensile strength but provides a higher modulus, higher thermal conductivity, and a lower cost potential. However, challenges in stable, continuous melt spinning processing are a serious limiting factor. Unlike typical melt spinning of long, linear chain polymers, mesophase pitch is a comprised of relatively shorter polycyclic aromatic hydrocarbons which form a liquid crystal. In its ‘green’ or ‘as-spun’ state, the fibers are very fragile. Moreover, its temperature of processing is quite high, often approaching 400ºC. Complex flow dynamics combined with short length and time scale heat transfer render its melt spinning a formidable processing challenge. Improved understanding of the root causes for nascent filament breakage and spinning instabilities are needed. This work aims to determine fundamental phenomena that govern mesophase pitch filament formation by comparison of required draw force and uninterrupted spinning minutes with applied draw down ratio. The effect of perturbations on spinning stability are analyzed using capillary rheometry, microscopy of elongating filaments, and filtration.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Mechanical Waste Gathering System (MWGS)

A Mechanical Waste Gathering System (MWGS) a technology is needed for retrieving solids from Hanford Site tanks that contain primarily solids (sludge, salt cake, and hard pan). An alternative retrieval technology is needed to begin supporting waste retrievals from A and AX Tank Farms. In many single‐shell tanks (SSTs), it is undesirable to use sluicing liquids to break up and remove waste due to the known or suspected reduced integrity of the tanks.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Linking climate change and human systems: a case study of Arctic pipelines

This case study estimates the potential economic risk from permafrost thaw on oil and gas pipelines in the Russian Arctic as part of a larger effort to better understand complex interactions between human and earth systems in the Arctic. Pan-Arctic simulations of permafrost thaw-depth from the Community Land Model version 4.5 and ground ice characteristics were used to generate ground subsidence projections over the period 2020 to 2040 with a quantification of uncertainty. Russian oil and gas transmission pipeline networks were then overlaid on the permafrost thaw projections in ArcGIS to identify pipelines vulnerable to damage from permafrost thaw. Recent pipeline construction costs were used to estimate the total replacement costs for at-risk pipelines under several thaw scenarios. The results indicate that permafrost thaw poses a major threat to pipeline infrastructure, especially gas pipelines, in the Russian Arctic. Over the twenty-year study period, total replacement costs for oil and gas pipelines were estimated at $\$$110 billion in 2020 USD. Reduced economic viability of pipelines under climate change will likely trigger major shifts in the Russian oil and gas industry, which would have impacts on markets, emissions, and geopolitics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Improving Detection of Disease Re-emergence Using a Web-Based Tool (RED Alert): Design and Case Analysis Study

Background: Currently, the identification of infectious disease re-emergence is performed without describing specific quantitative criteria that can be used to identify re-emergence events consistently. This practice may lead to ineffective mitigation. In addition, identification of factors contributing to local disease re-emergence and assessment of global disease re-emergence require access to data about disease incidence and a large number of factors at the local level for the entire world. This paper presents Re-emerging Disease Alert (RED Alert), a web-based tool designed to help public health officials detect and understand infectious disease re-emergence. Objective: Our objective is to bring together a variety of disease-related data and analytics needed to help public health analysts answer the following 3 primary questions for detecting and understanding disease re-emergence: Is there a potential disease re-emergence at the local (country) level? What are the potential contributing factors for this re-emergence? Is there a potential for global re-emergence? Methods: We collected and cleaned disease-related data (eg, case counts, vaccination rates, and indicators related to disease transmission) from several data sources including the World Health Organization (WHO), Pan American Health Organization (PAHO), World Bank, and Gideon. We combined these data with machine learning and visual analytics into a tool called RED Alert to detect re-emergence for the following 4 diseases: measles, cholera, dengue, and yellow fever. We evaluated the performance of the machine learning models for re-emergence detection and reviewed the output of the tool through a number of case studies. Results: Our supervised learning models were able to identify 82%-90% of the local re-emergence events, although with 18%-31% (except 46% for dengue) false positives. This is consistent with our goal of identifying all possible re-emergences while allowing some false positives. The review of the web-based tool through case studies showed that local re-emergence detection was possible and that the tool provided actionable information about potential factors contributing to the local disease re-emergence and trends in global disease re-emergence. Conclusions: To the best of our knowledge, this is the first tool that focuses specifically on disease re-emergence and addresses the important challenges mentioned above.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Evaluating the Impact of gRNA SNPs in CasRx Activity for Reducing Viral RNA in HCoV-OC43

Viruses within a given family often share common essential genes that are highly conserved due to their critical role for the virus’s replication and survival. In this work, we developed a proof-of-concept for a pan-coronavirus CRISPR effector system by designing CRISPR targets that are cross-reactive among essential genes of different human coronaviruses (HCoV). We designed CRISPR targets for both the RNA-dependent RNA polymerase (RdRp) gene as well as the nucleocapsid (N) gene in coronaviruses. Using sequencing alignment, we determined the most highly conserved regions of these genes to design guide RNA (gRNA) sequences. In regions that were not completely homologous among HCoV species, we introduced mismatches into the gRNA sequence and tested the efficacy of CasRx, a Cas13d type CRISPR effector, using reverse transcription quantitative polymerase chain reaction (RT-qPCR) in HCoV-OC43. We evaluated the effect that mismatches in gRNA sequences has on the cleavage activity of CasRx and found that this CRISPR effector can tolerate up to three mismatches while still maintaining its nuclease activity in HCoV-OC43 viral RNA. This work highlights the need to evaluate off-target effects of CasRx with gRNAs containing up to three mismatches in order to design safe and effective CRISPR experiments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Mechanical and Dielectric Properties of Aligned Electrospun Fibers

This review paper examines the current state-of-the-art in fabrication of aligned fibers via electrospinning techniques and the effects of these techniques on the mechanical and dielectric properties of electrospun fibers. Molecular orientation, system configuration to align fibers, and post-drawing treatment, like hot/cold drawing process, contribute to better specific strength and specific stiffness properties of nanofibers. The authors suggest that these improved, aligned nanofibers, when applied in composites, have better mechanical and dielectric properties for many structural and multifunctional applications, including advanced aerospace applications and energy storage devices. For these applications, most fiber alignment electrospinning research has focused on either mechanical property improvement or dielectric property improvement alone, but not both simultaneously. Relative to many other nanofiber formation techniques, the electrospinning technique exhibits superior nanofiber formation when considering cost and manufacturing complexity for many situations. Even though the dielectric property of pure nanofiber mat may not be of general interest, the analysis of the combined effect of mechanical and dielectric properties is relevant to the present analysis of improved and aligned nanofibers. A plethora of nanofibers, in particular, polyacrylonitrile (PAN) electrospun nanofibers, are discussed for their mechanical and dielectric properties. In addition, other types of electrospun nanofibers are explored for their mechanical and dielectric properties. An exploratory study by the author demonstrates the relationship between mechanical and dielectric properties for specimens obtained from a rotating mandrel horizontal setup.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Tailoring Mesopores and Nitrogen Groups of Carbon Nanofibers for Polysulfide Entrapment in Lithium–Sulfur Batteries

In the current work, we combined different physical and chemical modifications of carbon nanofibers through the creation of micro-, meso-, and macro-pores as well as the incorporation of nitrogen groups in cyclic polyacrylonitrile (CPAN) using gas-assisted electrospinning and air-controlled electrospray processes. We incorporated them into electrode and interlayer in Li–Sulfur batteries. First, we controlled pore size and distributions in mesoporous carbon fibers (mpCNF) via adding polymethyl methacrylate as a sacrificial polymer to the polyacrylonitrile carbon precursor, followed by varying activation conditions. Secondly, nitrogen groups were introduced via cyclization of PAN on mesoporous carbon nanofibers (mpCPAN). We compared the synergistic effects of all these features in cathode substrate and interlayer on the performance Li–Sulfur batteries and used various characterization tools to understand them. Our results revealed that coating CPAN on both mesoporous carbon cathode and interlayer greatly enhanced the rate capability and capacity retention, leading to the capacity of 1000 mAh/g at 2 C and 1200 mAh/g at 0.5 C with the capability retention of 88% after 100 cycles. The presence of nitrogen groups and mesopores in both cathodes and interlayers resulted in more effective polysulfide confinement and also show more promise for higher loading systems.

25 ENERGY STORAGE↗
DOE OSTI2020

Census of the Young Stellar Population in the Galactic H ii Region Sh2-242

We present here identification and characterization of the young stellar population associated with an active star-forming site Sh2-242. We used our own new optical imaging and spectroscopic observational data, as well as several archival catalogs, e.g., Pan-STARRS 1, Gaia DR2, IPHAS, Wide-field InfraRed Camera, 2MASS, and Spitzer. Slit spectroscopic results confirm the classification of the main ionizing source BD+26 980 as an early-type star of spectral type B0.5 V. The spectrophotometric distance of the star is estimated as 2.08 ± 0.24 kpc, which confirms the source as a member of the cluster. An extinction map covering a large area (diameter ∼50′) is generated with H and K photometry toward the region. From the map, three distinct locations of peak extinction complexes (A {sub V} ≃ 7–17 mag) are identified for the very first time. Using the infrared color excess, a total of 33 Class I and 137 Class II young objects are classified within the region. The IPHAS photometry reveals classification of 36 Hα emitting sources, which might be class II objects. Among 36 Hα emitting sources, 5 are already identified using infrared excess emission. In total, 201 young objects are classified toward S242 from this study. The membership status of the young sources is further windowed with the inclusion of parallax from the Gaia DR2 catalog. Using the optical and infrared color–magnitude diagrams, the young stellar objects are characterized with an average age of ∼1 Myr and masses in the range 0.1–3.0 M {sub ☉}. The census of the stellar content within the region is discussed using combined photometric and spectroscopic data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Photometric and Kinematic Study of the Open Clusters SAI 44 and SAI 45

We carry out a detailed photometric and kinematic study of the poorly studied sparse open clusters SAI 44 and SAI 45 using ground-based BVR {sub c} I {sub c} data supplemented by archival data from Gaia eDR3 and Pan-STARRS. The stellar memberships are determined using a statistical method based on Gaia eDR3 kinematic data, and we found 204 members in SAI 44 while only 74 members are identified in SAI 45. The average distances to SAI 44 and SAI 45 are calculated to be 3670 ± 184 and 1668 ± 47 pc. The logarithmic age of the clusters are determined to be 8.82 ± 0.10 and 9.07 ± 0.10 yr for SAI 44 and SAI 45, respectively. The color–magnitude diagram of SAI 45 hosts an extended main-sequence turnoff (eMSTO). The apparent age spread is found to be similar to the apparent age spread predicted on the basis of the age spread and cluster age relation predicted by rotation models. This indicates that eMSTO is a stellar evolution rather than star formation phenomenon in SAI 45. We conclude that eMSTO in SAI 45 is mainly caused by the different rotation rates of stars as the SYCLIST synthetic population with different rotation rates was able to reproduce the observed eMSTO, and stars in the red part of the eMSTO were preferentially concentrated in the inner region, which again hints at different rotations being the reason for the extension in the upper MS. This finding supports the theory attributing the origin of eMSTO to the different rotations of eMSTO stars. The mass function slopes are obtained as -2.24 ± 0.66 and -2.58 ± 3.20 in the mass rages 2.426–0.990 M{sub ⊙} and 2.167–1.202 M{sub ⊙} for SAI 44 and SAI 45, respectively. SAI 44 exhibits the signature of mass segregation while we found weak evidence of mass segregation in SAI 45 possibly due to tidal stripping. The dynamical relaxation times of these clusters indicate that both clusters are in a dynamically relaxed state. Using the AD-diagram method, the apex coordinates are found to be ([[Formula]], -[[Formula]]) for SAI 44 and (-[[Formula]], -[[Formula]]) for SAI 45. The average space velocity components of the clusters SAI 44 and SAI 45 are calculated in units of km s{sup -1} as (-15.14 ± 3.90, -19.43 ± 4.41, -20.85 ± 4.57) and (28.13 ± 5.30, -9.78 ± 3.13, -19.59 ± 4.43), respectively.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Random Forests as a Viable Method to Select and Discover High-redshift Quasars

We present a method of selecting quasars up to redshift ≈6 with random forests, a supervised machine-learning method, applied to Pan-STARRS1 and WISE data. We find that, thanks to the increasing set of known quasars, we can assemble a training set that enables supervised machine-learning algorithms to become a competitive alternative to other methods up to this redshift. We present a candidate set for the redshift range 4.8–6.3, which includes the region around z = 5.5 where selecting quasars is difficult due to their photometric similarity to red and brown dwarfs. We demonstrate that, under our survey restrictions, we can reach a high completeness (66% ± 7% below redshift 5.6/83{sub -9}{sup +6}% above redshift 5.6) while maintaining a high selection efficiency (78{sub -8}{sup +10}%/94{sub -8}{sup +5}%). Our selection efficiency is estimated via a novel method based on the different distributions of quasars and contaminants on the sky. The final catalog of 515 candidates includes 225 known quasars. We predict the candidate catalog to contain additional 148{sub -33}{sup +41} new quasars below redshift 5.6 and 45{sub -8}{sup +5} above, and we make the catalog publicly available. Spectroscopic follow-up observations of 37 candidates led us to discover 20 new high redshift quasars (18 at 4.6 ≤ z ≤ 5.5, 2 z ~ 5.7). These observations are consistent with our predictions on efficiency. We argue that random forests can lead to higher completeness because our candidate set contains a number of objects that would be rejected by common color cuts, including one of the newly discovered redshift 5.7 quasars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A Catalog of Distance Determinations for the LAMOST DR8 K Giants in the Galactic Halo

We present a catalog of distances for 19,544 K giants drawn from Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) DR8. Most of them are located in the halo of the Milky Way up to ~120 kpc. There are 15% K giants without Sloan Digital Sky Survey (SDSS) photometry, for which we supplements with Pan-STARRS1 (PS1) photometry calibrated to SDSS photometric system. The possible contamination of the red clumps/horizontal branch are removed according to metallicities and colors before the distance determination. Combining the LAMOST spectroscopic metallicities with the SDSS/PS1 photometry, we estimate the absolute magnitudes in the SDSS r band, the distance moduli, and the corresponding uncertainties through an Bayesian approach devised by Xue et al. for the Sloan Extension for Galactic understanding and exploration halo K giants. The typical distance precision is about 11%. The stars in the catalog lie in a region of 4–126 kpc from the Galactic center, of which with 6320 stars beyond 20 kpc and 273 stars beyond 50 kpc, forming the largest spectroscopic sample of distant tracers in the Milky Way halo so far.

79 ASTRONOMY AND ASTROPHYSICS↗