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At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Evaluating Polymer Properties with Different Additives for Carbon Capture and Other Applications

Anthropogenic climate change is one of this generation’s most pressing concerns, with the potential to completely alter the delicate balance we’ve struck with nature. Already, global temperatures have risen 1.29°C, leading to disrupted weather systems, extinctions, increased risks of wildfires, and sea level rise, to name a few effects. Carbon dioxide emission from the combustion of fossil fuels and other industrial activity is a large driver of this phenomenon, as it absorbs heat before it can be radiated away from Earth, trapping it. Carbon dioxide has reached unprecedented levels in our atmosphere, showing a 50% increase from preindustrial averages to a whopping 430 ppm. Thus, reducing the amount of carbon dioxide via carbon capture technology is an important endeavor that serves to benefit everyone. The Microencapsulated CO 2 Sorbent (MECS) team at Lawrence Livermore National Laboratory (LLNL) has turned to microencapsulation to approach this endeavor. Microcapsules provide an attractive approach to carbon capture, combining large surface areas for more efficient mass transfer, regenerative abilities, reduced solvent loss, and improved handling. Additionally, while existing carbon capture technology relies on industrial plants, capsules could present a modular approach to carbon capture, reducing the need for extensive physical infrastructure. The MECS team’s design consists of a polymer membrane that contains a liquid carbon sequestering sorbent, aqueous sodium carbonate. The carbon capturing reaction occurs in three distinct steps, the first of which is the dissolution of carbon dioxide into the sorbent solution and its conversion into carbonic acid (H 2 CO 3 ), shown in equations 1 and 2 respectively. Because this step hinges upon the ability of carbon dioxide to reach the solution inside the capsule, it is necessary that the microcapsule shell is permeable to carbon dioxide gas. The MECS team produces these microcapsules using the in-air droplet encapsulation apparatus (IDEA) shown in figure 1, which can produce uniform micron-scale droplets at speeds much faster than traditional single-dispersal microfluidic-based techniques. The IDEA Is 100 times faster than these current techniques and can reach up to 1000 times their speed when incorporating a multi-nozzle design. Additionally, because droplets are produced in-air via vibration, IDEA can decrease post-processing times and material waste by 99% and can fabricate microgels that are 10 to 100 times more viscous than can be produced via traditional microfluidics. While this design represents a breakthrough in the throughput, efficiency, and tunability of microcapsule production, it imposes a major constraint on the microcapsule curing process. Because microcapsule shells are crosslinked with UV light while falling 30 cm through the air, this gives them a reaction window of approximately 0.2 seconds. Thus, the system and shell formulations must be optimized such that the shells can be fully crosslinked within this very narrow window, prompting investigations into curing behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The Mantis Shrimp Dataset

The Mantis Shrimp Dataset (MSD) is a combination of matched cutouts of galaxies with known redshift in the ultra-violet, optical, and infrared wavelengths. MSD redshifts come from ''high-quality'' (as reported by the spectroscopic experiment) redshift measurements from a variety of spectroscopic surveys, including: SDSS, DESI early release, DEEP2, GAMA, VVDS, VIPERS, 6dF, and WiggleZ. Each redshift is accompanies with astrometry (ra,dec) pairs that were used to query cutout image services from PanSTARRs, UnWISE, and GALEX servers. The main data products are image vectors of these cutouts accompanied by the redshift value to be used to train computer vision networks on the supervised photometric redshift task. We also provide extinction values pre-queried at each galaxies' astrometry from the PLANCK and SFD dutstmaps, the SDSS MGS photometric redshift from Beck 2014 (if available) and the WISE x PS1 STRM photometric redshift for the galaxy (if available).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Dark Energy Survey Year 6 Results: Synthetic-source Injection Across the Full Survey Using Balrog

Synthetic source injection (SSI), the insertion of sources into pixel-level on-sky images, is a powerful method for characterizing object detection and measurement in wide-field, astronomical imaging surveys. Within the Dark Energy Survey (DES), SSI plays a critical role in characterizing all necessary algorithms used in converting images to catalogs, and in deriving quantities needed for the cosmology analysis, such as object detection rates, galaxy redshift estimation, galaxy magnification, star-galaxy classification, and photometric performance. We present here a source injection catalog of 146 million injections spanning the entire 5000 deg 2 DES footprint, generated using the Balrog SSI pipeline. Through this SSI sample, we demonstrate that the DES Year 6 (Y6) image processing pipeline provides accurate estimates of the object properties, for both galaxies and stars, at the percent-level, and we highlight specific regimes where the accuracy is reduced. We then show the consistency between SSI and data catalogs, for all galaxy samples developed within the weak lensing and galaxy clustering analyses of DES Y6. The consistency between the two catalogs also extends to their correlations with survey observing properties (seeing, airmass, depth, extinction, etc.). Lastly, we highlight a number of applications of this catalog to the DES Y6 cosmology analysis, such as estimates of the redshift distribution and lens magnification. This dataset is the largest SSI catalog produced at this fidelity and will serve as a key testing ground for exploring the utility of SSI catalogs in upcoming surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

A Semi-Supervised Learning Method for the Identification of Bad Exposures in Large Imaging Surveys

As the data volume of astronomical imaging surveys rapidly increases, traditional methods for image anomaly detection, such as visual inspection by human experts, are becoming impractical. We introduce a machine-learning-based approach to detect poor-quality exposures in large imaging surveys, with a focus on the DECam Legacy Survey (DECaLS) in regions of low extinction (i.e., E ( B − V ) < 0.04 ). Our semi-supervised pipeline integrates a vision transformer (ViT), trained via self-supervised learning (SSL), with a k-Nearest Neighbor (kNN) classifier. We train and validate our pipeline using a small set of labeled exposures observed by surveys with the Dark Energy Camera (DECam). A clustering-space analysis of where our pipeline places images labeled in good and bad categories suggests that our approach can efficiently and accurately determine the quality of exposures. Applied to new imaging being reduced for DECaLS Data Release 11, our pipeline identifies 780 problematic exposures, which we subsequently verify through visual inspection. Being highly efficient and adaptable, our method offers a scalable solution for quality control in other large imaging surveys.

Luo, Yufeng (ORCID:0000000246230683)↗
DOE OSTI2023

Simulation of a rapid compression machine for evaluation of ignition chemistry and soot formation using gasoline/ethanol blends

Due to the projected decline of demand for gasoline in light duty engines and the advent of ethanol as a green fuel, the use of gasoline/ethanol blend fuels in heavy duty applications are being investigated as they are projected to have lower cost and lower lifecycle green house gas (GHG) emissions. In heavy duty engines, the primary mode of combustion is mixing controlled combustion where wide range of mixture conditions (equivalence ratio) exist. Soot emissions of these fuels in richer conditions are not well understood. The goal of this research is to evaluate some commercially available soot modeling codes for the particulate matter emissions from gasoline/ethanol fuel blends, especially at fuel rich conditions. A Rapid Compression Machine (RCM) is modeled in a three-dimensional numerical simulation using CONVERGE computational software using a reduced chemical kinetic mechanism with SAGE chemistry solver and a RANS k-ϵturbulence model with a sector model including the creviced piston. The creviced piston is used in the experimental setup to reduce boundary layer effects and to maintain a homogeneous core in the reaction cylinder. Computational fluid dynamics simulations are conducted for different gasoline-ethanol fuel blends from E10 (10% ethanol v/v) to E100. The fuel blend is modeled as a surrogate mixture of toluene, iso-octane, n-heptane for gasoline content, and ethanol. The computational results were validated against experimental results using pressure measurements and laser extinction diagnostics. Different soot models are investigated to evaluate their capability of predicting the sooting tendencies of fuel blends, especially in richer conditions experienced during mixing-controlled combustion. The experimental combustion characteristics such as the ignition delay of different blends of fuel are reasonably well predicted. The Particulate Size Mimic (PSM) model accurately predicts the soot generation characteristics of the different fuels, but the Hiroyasu-NSC model falls short in this regard. For accurate prediction of soot with the PSM model, the thermodynamic conditions during combustion must be accurately modeled. While the current computational modeling tools can produce accurate results for the prediction of particulate matter emissions, there is much work to be done in improving our understanding of the underlying fundamental processes.

Energy & Fuels↗
DOE OSTI2022

Giant kelp genetic monitoring before and after disturbance reveals stable genetic diversity in Southern California

Given the impacts of climate change and other anthropogenic stressors on marine systems, there is a need to accurately predict how species respond to changing environments and disturbance regimes. The use of genetic tools to monitor temporal trends in populations gives ecologists the ability to estimate changes in genetic diversity and effective population size that may be undetectable by traditional census methods. Although multiple studies have used temporal genetic analysis, they usually involve commercially important species, and rarely sample before and after disturbance. In this study, we run a temporal analysis of giant kelp, Macrocystis pyrifera , genetic diversity over the scope of 10 years (2008-2018) using the same microsatellite marker panel to assess the genetic consequences of disturbance in several populations of giant kelp ( Macrocystis pyrifera ) in the Southern California Bight. The study is a rare pre- and post-disturbance microsatellite analysis that included declines to giant kelp caused by the 2015/16 El Nino Southern Oscillation event. We used canopy biomass estimated by remote sensing (Landsat) to quantify the extent of disturbance to kelp beds, and sea surface temperature data to understand how kelp was pushed towards its temperature limits during this period. Despite prolonged periods with decreased canopy at several sites, no changes in genetic structure and allelic richness were observed. We argue that giant kelp in the region is best described as a “patchy population” system where true extinctions are rare. We discuss how deep refugia of subsurface sporophytes and cryptic microscopic life stages could have kept genetic diversity through disturbance. Given the increasing effects of climate change and uncertainty in modeling impacts of species with cryptic life history stages, we suggest further investigation to reveal the role such stages play in species resilience. Genetic monitoring studies of sites selected by remote census demographic and climate surveys should be continued in the future given the predicted impacts of climate change.

Klingbeil, III, William H.↗
DOE OSTI2023

Hierarchical Modeling to Enhance Spectrophotometry Measurements—Overcoming Dynamic Range Limitations for Remote Monitoring of Neptunium

A robust hierarchical model has been demonstrated for monitoring a wide range of neptunium concentrations (0.75–890 mM) and varying temperatures (10–80 °C) using chemometrics and feature selection. The visible–near infrared electronic absorption spectrum (400–1700 nm) of monocharged neptunyl dioxocation (Np(V) = NpO2+) includes many bands, which have molar absorption coefficients that differ by nearly 2 orders of magnitude. The shape, position, and intensity of these bands differ with chemical interactions and changing temperature. These challenges make traditional quantification by univariate methods unfeasible. Measuring Np(V) concentration over several orders of magnitude would typically necessitate cells with varying path length, optical switches, and/or multiple spectrophotometers. Alternatively, the differences in the molar extinction coefficients for multiple absorption bands can be used to quantify Np(V) concentration over 3 orders of magnitude with a single optical path length (1 mm) and a hierarchical multivariate model. In this work, principal component analysis was used to distinguish the concentration regime of the sample, directing it to the relevant partial least squares regression submodels. Each submodel was optimized with unique feature selection filters that were selected by a genetic algorithm to enhance predictions. Through this approach, the percent root mean square error of prediction values were ≤1.05% for Np(V) concentrations and ≤4% for temperatures. This approach may be applied to other nuclear fuel cycle and environmental applications requiring real-time spectroscopic measurements over a wide range of conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Linear and Nonlinear Optical Properties of Iridium Nanoparticles Grown via Atomic Layer Deposition

Nonlinear optical phenomena enable novel photonic and optoelectronic applications. Especially, metallic nanoparticles and thin films with nonlinear optical properties offer the potential for micro-optical system integration. For this purpose, new nonlinear materials need to be continuously identified, investigated, and utilized for nonlinear optical applications. While noble-metal nanoparticles, nanostructures, and thin films of silver and gold have been widely studied, iridium (Ir) nanoparticles and ultrathin films have not been investigated for nonlinear optical applications yet. Here, we present a combined theoretical and experimental study on the linear and nonlinear optical properties of iridium nanoparticles deposited via atomic layer deposition (ALD). Linear optical constants, such as the effective refractive index and extinction coefficient, were evaluated at different growth stages of nanoparticle formation. Both linear and nonlinear optical properties of these Ir ALD coatings were calculated theoretically using the Maxwell Garnett theory. The third-order susceptibility of iridium nanoparticle samples was experimentally investigated using the z-scan technique. According to the experiment, for an Ir ALD coating with 45 cycles resulting in iridium nanoparticles, the experimentally determined nonlinear third-order susceptibility is about χ Ir (3) = (2.4 – i2.1) × 10 –17 m 2 /V 2 at the fundamental wavelength of 700 nm. The theory fitted to the experimental results predicts a 5 × 10 6 -fold increase around 230 nm. This strong increase is due to the proximity to the Mie resonance of iridium nanoparticles.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Restoring Pre-Industrial CO2 Levels While Achieving Sustainable Development Goals

Unless humanity achieves United Nations Sustainable Development Goals (SDGs) by 2030 and restores the relatively stable climate of pre-industrial CO2 levels (as early as 2140), species extinctions, starvation, drought/floods, and violence will exacerbate mass migrations. This paper presents conceptual designs and techno-economic analyses to calculate sustainable limits for growing high-protein seafood and macroalgae-for-biofuel. We review the availability of wet solid waste and outline the mass balance of carbon and plant nutrients passing through a hydrothermal liquefaction process. The paper reviews the availability of dry solid waste and dry biomass for bioenergy with CO2 capture and storage (BECCS) while generating Allam Cycle electricity. Sufficient wet-waste biomass supports quickly building hydrothermal liquefaction facilities. Macroalgae-for-biofuel technology can be developed and straightforwardly implemented on SDG-achieving high protein seafood infrastructure. The analyses indicate a potential for (1) 0.5 billion tonnes/yr of seafood; (2) 20 million barrels/day of biofuel from solid waste; (3) more biocrude oil from macroalgae than current fossil oil; and (4) sequestration of 28 to 38 billion tonnes/yr of bio-CO2. Carbon dioxide removal (CDR) costs are between 25–33% of those for BECCS with pre-2019 technology or the projected cost of air-capture CDR.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Classification of Wetland Vegetation Based on NDVI Time Series from the HLS Dataset

Natural wetlands are intrinsically heterogeneous and typically composed of a mosaic of ecosystem patches with different vegetation types. Hydrological and biogeochemical processes in wetlands vary strongly among these ecosystem patches. To date, most remote sensing classification approaches for wetland vegetation either rely on coarse images that cannot capture the spatial variability of wetland vegetation or rely on very-high-resolution multi-spectral images that are detailed but very sporadic in time (less than once per year). This study aimed to use NDVI time series, generated from NASA’s HLS dataset, to classify vegetation patches. We demonstrate our approach at a temperate, coastal lake, estuarine marsh. To classify vegetation patches, a standard time series library of the four land-cover patch types was built from referencing specific locations that were identified as “pure” pixels. These were identified using a single-time high-resolution image. We calculated the distance between the HLS-NDVI time series at each pixel and the “pure”-pixel standards for each land-cover type. The resulting true-positive classified rate was >73% for all patch types other than water lily. The classification accuracy was higher in pixels of a more uniform composition. A set of vegetation maps was created for the years 2016 to 2020 at our research site to identify the vegetation changes at the site as it is affected by rapid water elevation increases in Lake Erie. Our results reveal how changes in water elevation have changed the patch distribution in significant ways, leading to the local extinction of cattail by 2019 and a continuous increase in the area cover of water lily patches.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Survey for New Stars and Brown Dwarfs in the Ophiuchus Star-forming Complex

We have performed a survey for new members of the Ophiuchus cloud complex using high-precision astrometry from the second data release of Gaia, proper motions measured with multi-epoch images from the Spitzer Space Telescope, and color–magnitude diagrams constructed with photometry from various sources. Through spectroscopy of candidates selected with those data, we have identified 155 new young stars. Based on available measurements of kinematics, we classify 102, 47, and 6 of those stars as members of Ophiuchus, Upper Sco, and other populations in Sco–Cen, respectively. We have also assessed the membership of all other stars in the vicinity of Ophiuchus that have spectroscopic evidence of youth from previous studies, arriving at a catalog of 373 adopted members of the cloud complex. For those adopted members, we have compiled mid-infrared photometry from Spitzer and the Wide-field Infrared Survey Explorer and have used mid-infrared colors to identify and classify circumstellar disks. We find that 210 of the members show evidence of disks, including 48 disks that are in advanced stages of evolution. Finally, we have estimated the relative median ages of the populations near the Ophiuchus clouds and the surrounding Upper Sco association using absolute K-band magnitudes (M {sub K}) based on Gaia parallaxes. If we adopt an age 10 Myr for Upper Sco, then the relative values of M {sub K} imply median ages of ∼2 Myr for L1689 and embedded stars in L1688, 3–4 Myr for low-extinction stars near L1688, and ∼6 Myr for the group containing ρ Oph.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

New Candidates for Planetary-mass Brown Dwarfs in IC 348

We have used infrared images obtained with the Wide Field Camera 3 on board the Hubble Space Telescope to search for planetary-mass brown dwarfs in the star-forming cluster IC 348. In those images, we have identified 12 objects that have colors indicative of spectral types later than M8, corresponding to masses of ≲30 M {sub Jup} at the age of IC 348. The four brightest candidates have been observed with spectroscopy, all of which are confirmed to have late types. Two of those candidates appear to be young, and thus are likely members of the cluster, while the ages and membership of the other two candidates are uncertain. One of the former candidates is the faintest known member of IC 348 in extinction-corrected K {sub s} and is expected to have a mass of 4–5 M {sub Jup} based on evolutionary models and an assumed age of 3 Myr. Four of the remaining eight candidates have ground-based photometry that further supports their candidacy as brown dwarfs, some of which are fainter (and potentially less massive) than the known members.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

An Investigation of Poorly Studied Open Cluster NGC 4337 Using Multicolor Photometric and Gaia DR2 Astrometric Data

We present a comprehensive analysis (photometric and kinematical) of the poorly studied open cluster NGC 4337 using 2MASS, WISE, APASS, and Gaia DR2 databases. By determining the membership probabilities of stars, we identified the 624 most probable members with membership probability higher than 50% by using proper motion and parallax data taken from Gaia DR2. The mean proper motion of the cluster is obtained as μ{sub x}=−8.83±0.01 and μ {sub y} = 1.49 ± 0.006 mas yr{sup −1}. We find the normal interstellar extinction toward the cluster region. The radial distribution of members provides a cluster radius of 7.′75 (5.63 pc). The estimated age of 1600 ± 180 Myr indicates that NGC 4337 is an old open cluster with a bunch of red giant stars. The overall mass function slope for main-sequence stars is found as 1.46±0.18 within the mass range 0.75−2.0 M{sub ⊙}, which is in fair agreement with Salpeter’s value (x = 1.35) within uncertainty. The present study demonstrates that NGC 4337 is a dynamically relaxed open cluster. Using the Galactic potential model, Galactic orbits are obtained for NGC 4337. We found that this object follows a circular path around the Galactic center. Under the kinematical analysis, we compute the apex coordinates (A, D) by using two methods: (i) the classical convergent point method and (ii) the AD-diagram method. The obtained coordinates are (A {sub conv}, D {sub conv}) = (96.°27 ± 0.°10, 13.°14 ± 0.°27) and (A {sub ◦}, D {sub ◦}) = (100.°282 ± 0.°10, 9.°577 ± 0.°323) respectively. We also computed the Velocity Ellipsoid Parameters, matrix elements (μ {sub ij}), direction cosines (l {sub j}, m {sub j}, n {sub j}), and the Galactic longitude of the vertex (l {sub 2}).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

SPISEA: A Python-based Simple Stellar Population Synthesis Code for Star Clusters

We present Stellar Population Interface for Stellar Evolution and Atmospheres (SPISEA), an open-source Python package that simulates simple stellar populations. The strength of SPISEA is its modular interface which offers the user control of 13 input properties including (but not limited to) the initial mass function, stellar multiplicity, extinction law, and the metallicity-dependent stellar evolution and atmosphere model grids used. The user also has control over the initial–final mass relation in order to produce compact stellar remnants (black holes, neutron stars, and white dwarfs). We demonstrate several outputs produced by the code, including color–magnitude diagrams, HR-diagrams, luminosity functions, and mass functions. SPISEA is object-oriented and extensible, and we welcome contributions from the community. The code and documentation are available on GitHub (https://github.com/astropy/SPISEA) and ReadtheDocs (https://spisea.readthedocs.io/en/latest/), respectively.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The Most Metal-poor Stars in the Inner Bulge

The bulge is the oldest component of the Milky Way. Since numerous simulations of Milky Way formation have predicted that the oldest stars at a given metallicity are found on tightly bound orbits, the Galaxy’s oldest stars are likely metal-poor stars in the inner bulge with small apocenters (i.e., R {sub apo} ≲ 4 kpc). In the past, stars with these properties have been impossible to find due to extreme reddening and extinction along the line of sight to the inner bulge. We have used the mid-infrared metal-poor star selection of Schlaufman & Casey (2014) on Spitzer/Galactic Legacy Infrared Mid-Plane Survey Extraordinaire data to overcome these problems and target candidate inner bulge metal-poor giants for moderate-resolution spectroscopy with Anglo-Australian Telescope/AAOmega. We used those data to select three confirmed metal-poor giants ([Fe/H] = −3.15, −2.56, −2.03) for follow-up high-resolution Magellan/Magellan Inamori Kyocera Echelle spectroscopy. A comprehensive orbit analysis using Gaia DR2 astrometry and our measured radial velocities confirms that these stars are tightly bound inner bulge stars. We determine the elemental abundances of each star and find high titanium and iron-peak abundances relative to iron in our most metal-poor star. We propose that the distinct abundance signature we detect is a product of nucleosynthesis in the Chandrasekhar-mass thermonuclear supernova of a CO white dwarf accreting from a helium star with a delay time of about 10 Myr. Even though chemical evolution is expected to occur quickly in the bulge, the intense star formation in the core of the nascent Milky Way was apparently able to produce at least one Chandrasekhar-mass thermonuclear supernova progenitor before chemical evolution advanced beyond [Fe/H]∼−3.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Mathematical Underpinnings of the Multiwavelength Structure of the Tip of the Red Giant Branch

We consider the application of the tip of the red giant branch (TRGB) in the optical and in the near-infrared for the determination of distances to nearby galaxies. We analyze ACS VI (F555W and F814W) data and self-consistently cross-calibrate WFC3-IR JH (F110W and F120W) data using an absolute magnitude calibration of M {sub I} = −4.05 mag as determined in the Large Magellanic Cloud using detached eclipsing binary star geometric parallaxes. We demonstrate how the optical and near-infrared calibrations of the TRGB method are mathematically self-consistent, and illustrate the mathematical basis and relations among these multiwavelength calibrations. We go on to present a method for determining the reddening, extinction, and the true modulus to the host galaxy using multiwavelength data. The power of the method is that with high-precision data, the reddening can be determined using the TRGB stars themselves, and decreases the systematic (albeit generally small) uncertainty in distance due to reddening for these halo stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Untangling the Galaxy. II. Structure within 3 kpc

We present the results of the hierarchical clustering analysis of the Gaia DR2 data to search for clusters, comoving groups, and other stellar structures. The current paper builds on the sample from the previous work, extending it in distance from 1 to 3 kpc and increasing the number of identified structures up to 8292. To aid in the analysis of the population properties, we developed a neural network called Auriga to robustly estimate the age, extinction, and distance of a stellar group based on the input photometry and parallaxes of the individual members. We apply Auriga to derive the properties of not only the structures found in this paper, but also previously identified open clusters. Through this work, we examine the temporal structure of the spiral arms. Specifically, we find that the Sagittarius Arm has moved by >500 pc in the last 100 Myr and the Perseus Arm has been experiencing a relative lull in star formation activity over the last 25 Myr. We confirm the findings of the previous paper on the transient nature of the spiral arms, with the timescale of transition of a few 100 Myr. Finally, we find a peculiar ~1 Gyr old stream of stars that appears to be heliocentric. Its origin is unclear.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Early High-contrast Imaging Results with Keck/NIRC2-PWFS: The SR 21 Disk

High-contrast imaging of exoplanets and protoplanetary disks depends on wave front sensing and correction made by adaptive optics instruments. Classically, wave front sensing has been conducted at optical wavelengths, which made high-contrast imaging of red targets such as M-type stars or extincted T Tauri stars challenging. Keck/NIRC2 has combined near-infrared (NIR) detector technology with the pyramid wave front sensor (PWFS). With this new module we observed SR 21, a young star that is brighter at NIR wavelengths than at optical wavelengths. Compared with the archival data of SR 21 taken with the optical wave front sensing we achieved ~20% better Strehl ratio in similar natural seeing conditions. Further post-processing utilizing angular differential imaging and reference-star differential imaging confirmed the spiral feature reported by the Very Large Telescope/Spectro-Polarimetric High-contrast Exoplanet REsearch instrument polarimetric observation, which is the first detection of the SR 21 spiral in total intensity at L' band. We also compared the contrast limit of our result (10 -4 at 0.'4 and 2 × 10 -5 at 1.'0) with the archival data that were taken with optical wave front sensing and confirmed the improvement, particularly at ≤0.'5. Our observation demonstrates that the NIR PWFS improves AO performance and will provide more opportunities for red targets in the future.

79 ASTRONOMY AND ASTROPHYSICS↗