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At least 487 records · Page 27

Interdisciplinary Approaches Improve Understanding of Cryptogenic Species: A Historical Case Study of Crayfish in Montana, USA

ABSTRACT Cryptogenic species are those that are not yet “demonstrably native or introduced” in a given area, such as crayfish in western Montana, USA. Delving into evidence from diverse fields can help clarify the status of cryptogenic species. Primary historical sources and indigenous knowledge have informed various ecological questions but are seldom used to clarify the status of cryptogenic species, especially aquatic taxa. We summarize types of evidence used to illuminate species status and offer a case study applying historical sources to cryptogenic crayfish in Montana. We searched for crayfish mentions in dictionaries of indigenous languages and primary historical documents (e.g., travel journals, newspaper accounts, early biological surveys). Early explorer accounts we examined did not mention crayfish in Montana, though they noted them in the nearby Snake River drainage of Idaho and Wyoming. The first mention of crayfish in Montana that we found was from an 1868 newspaper account, probably referencing the upper Missouri River. The species was not noted, but an 1887 article suggested signal crayfish Pacifastacus leniusculus introductions near Bozeman, where non‐native signal crayfish still persist. The earliest crayfish mention we found west of the Great Divide in Montana was from 1934 in Ninepipes and probably referred to non‐native virile crayfish ( Faxonius virilis ). Signal crayfish were not mentioned west of the Divide until a 1944 newspaper account noted their 1937 introduction to the Bitterroot River drainage. The case study demonstrates the value of historical sources in identifying the absence of species and documenting their presence or introduction during periods predating scientific data.

Kennedy, Hampton L. [USDA Forest Service, Southern↗

Passive force balancing of an active magnetic regenerative liquefier

Active magnetic regenerators (AMR) have the potential for high efficiency cryogen liquefaction. One active magnetic regenerative liquefier (AMRL) configuration consists of dual magnetocaloric regenerators that reciprocate in a persistent-mode superconducting solenoid. Issues with this configuration are the spatial and temporal magnetization gradients that induce large magnetic forces and winding currents. To solve the coupled problem, we present a force minimization approach using passive magnetic material to balance a dual-regenerator AMR. A magnetostatic model is developed and simulated force waveforms are compared with experimental measurements. A genetic algorithm identifies force-minimizing passive structures with virtually ideal balancing characteristics. Finally, implementation details are investigated which affirm the potential of the proposed methodology.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Source-Resolved Inversion of Elemental Carbon Emissions in California Using Log-Space Bayesian Inference

Elemental carbon (EC), operationally quantified by thermal-optical analysis, is widely used as a proxy for black carbon (BC) relevant to short-term climate forcing and public health. Current EC emission inventories remain highly uncertain, with persistent discrepancies between bottom-up and top-down estimates. In this study, we develop a source-resolved, log-space Bayesian inversion framework applied to estimate California’s statewide EC emissions in 2019. By integrating surface EC measurements from the EPA’s Air Quality System network with high-resolution source contributions simulated by a chemical transport model, we identify a one-third underestimation in the existing statewide EC inventory, requiring an increase of the total from a prior of 8.58 [5.49–13.75] Gg year–1 to a posterior estimate of 12.78 [10.71–15.37] Gg year–1. This discrepancy is primarily driven by substantial underestimations in the power and industrial and off-road mobile sectors. Furthermore, population-weighted exposure analysis reveals a marked sectoral divergence between emission mass and health burden: off-road mobile sources dominate both emissions and exposure, accounting for 31% of statewide exposure, while residential wood combustion contributes 26% of total exposure despite comprising only 19% of total emissions, due to its source proximity to population. These findings underscore the need to update sector-specific EC speciation profiles and demonstrate that mitigation strategies targeting off-road mobile sources and residential wood combustion are critical for reducing EC-related health impacts in California.

Zhang, Jie↗

Multiple spillovers from humans and onward transmission of SARS-CoV-2 in white-tailed deer

Many animal species are susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and could act as reservoirs; however, transmission in free-living animals has not been documented. White-tailed deer, the predominant cervid in North America, are susceptible to SARS-CoV-2 infection, and experimentally infected fawns can transmit the virus. To test the hypothesis that SARS-CoV-2 is circulating in deer, 283 retropharyngeal lymph node (RPLN) samples collected from 151 free-living and 132 captive deer in Iowa from April 2020 through January of 2021 were assayed for the presence of SARS-CoV-2 RNA. Ninety-four of the 283 (33.2%) deer samples were positive for SARS-CoV-2 RNA as assessed by RT-PCR. Notably, following the November 2020 peak of human cases in Iowa, and coinciding with the onset of winter and the peak deer hunting season, SARS-CoV-2 RNA was detected in 80 of 97 (82.5%) RPLN samples collected over a 7-wk period. Whole genome sequencing of all 94 positive RPLN samples identified 12 SARS-CoV-2 lineages, with B.1.2 (n = 51; 54.5%) and B.1.311 (n = 19; 20%) accounting for ~75% of all samples. The geographic distribution and nesting of clusters of deer and human lineages strongly suggest multiple human-to-deer transmission events followed by subsequent deer-to-deer spread. These discoveries have important implications for the long-term persistence of the SARS-CoV-2 pandemic. Our findings highlight an urgent need for a robust and proactive “One Health” approach to obtain enhanced understanding of the ecology, molecular evolution, and dissemination of SARS-CoV-2.

60 APPLIED LIFE SCIENCES↗

On the origin of wind line variability in O stars

We analyze 10 UV time series for five stars that fulfill specific sampling and spectral criteria to constrain the origin of large-scale wind structure in O stars. We argue that excited state lines must arise close to the stellar surface and are an excellent diagnostic complement to resonance lines which, due to radiative transfer effects, rarely show variability at low velocity. Consequently, we splice dynamic spectra of the excited state line N iv λ1718 at low velocity with those of Si iv λλ1400 at high velocity in order to examine the temporal evolution of wind line features. These spliced time series reveal that nearly all of the features observed in the time series originate at or very near the stellar surface. Furthermore, we positively identify the observational signature of equatorial corotating interaction regions in two of the five stars and possibly two others. In addition, we see no evidence of features originating further out in the wind. We use our results to confirm the fact that the features seen in dynamic spectra must be huge in order to remain in the line of sight for days, persisting to very large velocity, and that the photospheric footprint of the features must also be quite large, ∼15%–20% of the stellar diameter.

79 ASTRONOMY AND ASTROPHYSICS↗

The Southern Ocean as a constraint to reduce uncertainty in future ocean carbon sinks

Earth system model (ESM) simulations exhibit large biases compares to observation-based estimates of the present ocean CO 2 sink. The inter-model spread in projections increases nearly 2-fold by the end of the 21st century and therefore contributes significantly to the uncertainty of future climate projections. In this study, the Southern Ocean (SO) is shown to be one of the hot-spot regions for future uptake of anthropogenic CO 2 , characterized by both the solubility pump and biologically mediated carbon drawdown in the spring and summer. Here, we show, by analyzing a suite of fully interactive ESMs simulations from the Coupled Model Intercomparison Project phase 5 (CMIP5) over the 21st century under the high-CO 2 Representative Concentration Pathway (RCP) 8.5 scenario, that the SO is the only region where the atmospheric CO 2 uptake rate continues to increase toward the end of the 21st century. Furthermore, our study discovers a strong inter-model link between the contemporary CO 2 uptake in the Southern Ocean and the projected global cumulated uptake over the 21st century. This strong correlation suggests that models with low (high) carbon uptake rate in the contemporary SO tend to simulate low (high) uptake rate in the future. None the less, our analysis also shows that none of the models fully capture the observed biophysical mechanisms governing the CO 2 fluxes in the SO. The inter-model spread for the contemporary CO 2 uptake in the Southern Ocean is attributed to the variations in the simulated seasonal cycle of surface p CO 2 . Two groups of model behavior have been identified. The first one simulates anomalously strong SO carbon uptake, generally due to both too strong a net primary production and too low a surface p CO 2 in December–January. The second group simulates an opposite CO 2 flux seasonal phase, which is driven mainly by the bias in the sea surface temperature variability. Furthermore, we show that these biases are persistent throughout the 21st century, which highlights the urgent need for a sustained and comprehensive biogeochemical monitoring system in the Southern Ocean to better constrain key processes represented in current model systems.

58 GEOSCIENCES↗

Automated Extraction of Energy Systems Information from Remotely Sensed Data: A Review and Analysis

We report high quality energy systems information is a crucial input to energy systems research, modeling, and decision-making. Unfortunately, actionable information about energy systems is often of limited availability, incomplete, or only accessible for a substantial fee or through a non-disclosure agreement. Recently, remotely sensed data (e.g., satellite imagery, aerial photography) have emerged as a potentially rich source of energy systems information. However, the use of these data is frequently challenged by its sheer volume and complexity, precluding manual analysis. Recent breakthroughs in machine learning have enabled automated and rapid extraction of useful information from remotely sensed data, facilitating large-scale acquisition of critical energy system variables. Here we present a systematic review of the literature on this emerging topic, providing an in-depth survey and review of papers published within the past two decades. We first taxonomize the existing literature into ten major areas, spanning the energy value chain. Within each research area, we distill and critically discuss major features that are relevant to energy researchers, including, for example, key challenges regarding the accessibility and reliability of the methods. We then synthesize our findings to identify limitations and trends in the literature as a whole, and discuss opportunities for innovation. These include the opportunity to extend the methods beyond electricity to broader energy systems and wider geographic areas; and the ability to expand the use of these methods in research and decision making as satellite data become cheaper and easier to access. We also find that there are persistent challenges: limited standardization and rigor of performance assessments; limited sharing of code, which would improve replicability; and a limited consideration of the ethics and privacy of data.

97 MATHEMATICS AND COMPUTING↗

Employment access assessed using the mobility energy productivity (MEP) metric

Transit agencies, local governments, employers, and job-seekers have a shared interest in connecting residents with jobs in an affordable and time efficient manner, with public agencies also caring about energy efficiency and air quality. Employment hubs are an opportunity to solve the spatial mismatch between homes of job-seekers and the locations of desirable jobs. Such is the case in Columbus, Ohio, between Rickenbacker Industrial Park and the Linden neighborhood, which has experienced persistent poverty. Using the mobility energy productivity (MEP) metric to examine travel time, cost, and energy efficiency, we show current transit service is undesirable due to excessive travel time (70 min, MEP = 0), while driving alone (MEP = 0.20) may be less desirable than a hypothetical, fare-free microtransit service (MEP = 0.23). Updating MEP to use locally-derived input data can help identify parameters under which providing microtransit service in a specific place has compelling benefits in terms of vehicle energy efficiency as well as cost and travel time for riders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Emergence of quasiparticles in a doped Mott insulator

How a Mott insulator develops into a weakly coupled metal upon doping is a central question to understanding various emergent correlated phenomena. To analyze this evolution and its connection to the high- T c cuprates, we study the single-particle spectrum for the doped Hubbard model using cluster perturbation theory on superclusters. Starting from extremely low doping, we identify a heavily renormalized quasiparticle dispersion that immediately develops across the Fermi level, and a weakening polaronic side band at higher binding energy. The quasiparticle spectral weight roughly grows at twice the rate of doping in the low doping regime, but this rate is halved at optimal doping. In the heavily doped regime, we find both strong electron-hole asymmetry and a persistent presence of Mott spectral features. Finally, we discuss the applicability of the single-band Hubbard model to describe the evolution of nodal spectra measured by angle-resolved photoemission spectroscopy (ARPES) on the single-layer cuprate La 2– x Sr x CuO 4 (0 ≤ x ≤ 0.15). This work benchmarks the predictive power of the Hubbard model for electronic properties of high- T c cuprates.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Radiation hydrodynamics modeling of the highest compression inertial confinement fusion ignition experiment from the National Ignition Campaign

The recently completed National Ignition Campaign (NIC) on the National Ignition Facility (NIF) showed significant discrepancies between post-shot simulations of implosion performance and experimentally measured performance, particularly in thermonuclear yield. This discrepancy between simulation and observation persisted despite concerted efforts to include all of the known sources of performance degradation within a reasonable two-dimensional (2-D), and even three-dimensional (3-D), simulation model, e.g., using measured surface imperfections and radiation drives adjusted to reproduce observed implosion trajectories [Clark et al., Phys. Plasmas 20, 056318 (2013)]. Since the completion of the NIC, several effects have been identified that could explain these discrepancies and that were omitted in previous simulations. In particular, there is now clear evidence for larger than anticipated long-wavelength radiation drive asymmetries and a larger than expected perturbation seeded by the capsule support tent. This paper describes an updated suite of one-dimensional (1-D), 2-D, and 3-D simulations that include the current best understanding of these effects identified since the NIC, as applied to a specific NIC shot. The relative importance of each effect on the experimental observables is compared. In combination, these effects reduce the simulated-to-measured yield ratio from 125:1 in 1-D to 1.5:1 in 3-D, as compared to 15:1 in the best 2-D simulations published previously. While the agreement with the experimental data remains imperfect, the comparison to the data is significantly improved and suggests that the largest sources for the previous discrepancies between simulation and experiment are now being included.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Policy-relevant differences between secondhand and thirdhand smoke: strengthening protections from involuntary exposure to tobacco smoke pollutants

Starting in the 1970s, individuals, businesses and the public have increasingly benefited from policies prohibiting smoking indoors, saving thousands of lives and billions of dollars in healthcare expenditures. Smokefree policies to protect against secondhand smoke exposure, however, do not fully protect the public from the persistent and toxic chemical residues from tobacco smoke (also known as thirdhand smoke) that linger in indoor environments for years after smoking stops. Nor do these policies address the economic costs that individuals, businesses and the public bear in their attempts to remediate this toxic residue. We discuss policy-relevant differences between secondhand smoke and thirdhand smoke exposure: persistent pollutant reservoirs, pollutant transport, routes of exposure, the time gap between initial cause and effect, and remediation and disposal. We examine four policy considerations to better protect the public from involuntary exposure to tobacco smoke pollutants from all sources. We call for (a) redefining smokefree as free of tobacco smoke pollutants from secondhandandthirdhand smoke; (b) eliminating exemptions to comprehensive smoking bans; (c) identifying indoor environments with significant thirdhand smoke reservoirs; and (d) remediating thirdhand smoke. We use the case of California as an example of how secondhand smoke-protective laws may be strengthened to encompass thirdhand smoke protections. The health risks and economic costs of thirdhand smoke require that smokefree policies, environmental protections, real estate and rental disclosure policies, tenant protections, and consumer protection laws be strengthened to ensure that the public is fully protected from and informed about the risks of thirdhand smoke exposure.

Public, Environmental & Occupational Health↗

Resolving Detonation NanoDiamond Size Evolution and Morphology at Sub-Microsecond Time-Scales During High-Explosive Detonations

Characterization of the initial morphology of detonation nanodiamond (DND) has been the focus of many research studies that aim to develop fundamental understanding of carbon condensation under extreme conditions. Identifying the pathways of DND formation has the potential for significant impact in many of the controlled synthesis of nanoscale carbon with tailored functionality; currently, a wide range of possible (and conflicting) mechanisms of nucleation and growth have been proposed and further research is essential. Building a comprehensive understanding of DND formation is challenging because it requires in situ characterization on the sub-µs time-scale during a high explosive detonation. In this study, time resolved small angle X-ray scattering (TR-SAXS) is used to reveal the early-stage DND morphology from < 0.1 μs to 6 μs after the detonation front passes through the X-ray beam path. We address the ambiguity of models previously reported for analysis of small angle scattering from DND by comparing (i) in situ, TR-SAXS recorded during early-stage particulate formation and (ii) ex situ SAXS and transmission electron microscopy measurements (TEM) of products recovered from detonation of the same high-explosive within a carefully designed ice chamber. The SAXS from both late-time ( > 1 μs) in situ and recovered DND exhibit consistent features in the I(q) curve. Such close similarity allows a high fidelity SAXS model derived from the ex situ SAXS and TEM measurements to be applied to the in situ data, which yields new insight into the early stage (< 1µs) morphology of DND. Our analysis indicates a size-distribution of DND particles is observed within 0.1 μs post-detonation and have a mean core diameter slightly below 4 nm and surface texture that consists of hemispherical protrusions that extend ~ 1 nm from the surface. Beyond ~ 0.3 μs, the size distribution increases slightly, while the surface texture persists for several microseconds after the detonation. Combined with thermochemical simulations, these results indicate that during detonation of Composition B, carbon is condensed into nanoscale diamond much faster than previously reported in other studies. Furthermore, the surface texture of the DND is shown to arise during condensation rather than via subsequent graphitization.

carbon condensation↗

Structural and chemical evolution in layered oxide cathodes of lithium-ion batteries revealed by synchrotron techniques

Abstract Rechargeable battery technologies have revolutionized electronics, transportation and grid energy storage. Many materials are being researched for battery applications, with layered transition metal oxides (LTMO) the dominating cathode candidate with remarkable electrochemical performance. Yet, daunting challenges persist in the quest for further battery developments targeting lower cost, longer lifespan, improved energy density and enhanced safety. This is, in part, because of the intrinsic complexity of real-world batteries, featuring sophisticated interplay among microstructural, compositional and chemical heterogeneities, which has motivated tremendous research efforts using state-of-the-art analytical techniques. In this research field, synchrotron techniques have been identified as a suite of effective methods for advanced battery characterization in a non-destructive manner with sensitivities to the lattice, electronic and morphological structures. This article provides a holistic overview of cutting-edge developments in synchrotron-based research on LTMO battery cathode materials. We discuss the complexity and evolution of LTMO’s material properties upon battery operation and review recent synchrotron-based research works that address the frontier challenges and provide novel insights in this field. Finally, we formulate a perspective on future directions of synchrotron-based battery research, involving next-generation X-ray facilities and advanced computational developments.

25 ENERGY STORAGE↗

Interrogation of the Burkholderia pseudomallei genome to address differential virulence among isolates

Infection by the Gram-negative pathogen Burkholderia pseudomallei results in the disease melioidosis, acquired from the environment in parts of southeast Asia and northern Australia. Clinical symptoms of melioidosis range from acute (fever, pneumonia, septicemia, and localized infection) to chronic (abscesses in various organs and tissues, most commonly occurring in the lungs, liver, spleen, kidney, prostate and skeletal muscle), and persistent infections in humans are difficult to cure. Understanding the basic biology and genomics of B. pseudomallei is imperative for the development of new vaccines and therapeutic interventions. This formidable task is becoming more tractable due to the increasing number of B. pseudomallei genomes that are being sequenced and compared. Here, we compared three B. pseudomallei genomes, from strains MSHR668, K96243 and 1106a, to identify features that might explain why MSHR668 is more virulent than K96243 and 1106a in a mouse model of B. pseudomallei infection. Our analyses focused on metabolic, virulence and regulatory genes that were present in MSHR668 but absent from both K96243 and 1106a. We also noted features present in K96243 and 1106a but absent from MSHR668, and identified genomic differences that may contribute to variations in virulence noted among the three B. pseudomallei isolates. While this work contributes to our understanding of B. pseudomallei genomics, more detailed experiments are necessary to characterize the relevance of specific genomic features to B. pseudomallei metabolism and virulence. Functional analyses of metabolic networks, virulence and regulation shows promise for examining the effects of B. pseudomallei on host cell metabolism and will lay a foundation for future prediction of the virulence of emerging strains. Continued emphasis in this area will be critical for protection against melioidosis, as a better understanding of what constitutes a fully virulent Burkholderia isolate may provide for better diagnostic and medical countermeasure strategies.

59 BASIC BIOLOGICAL SCIENCES↗

Spatial and temporal metagenomics of river compartments reveals viral community dynamics in an urban impacted stream

Although river ecosystems constitute a small fraction of Earth’s total area, they are critical modulators of microbially and virally orchestrated global biogeochemical cycles. However, most studies either use data that is not spatially resolved or is collected at timepoints that do not reflect the short life cycles of microorganisms. To address this gap, we assessed how viral and microbial communities change over a 48-hour period by sampling surface water and pore water compartments of the wastewater-impacted River Erpe in Germany. We sampled every 3 hours resulting in 32 samples for which we obtained metagenomes along with geochemical and metabolite measurements. From our metagenomes, we identified 6,500 viral and 1,033 microbial metagenome assembled genomes (MAGs) and found distinct community membership and abundance associated with each river compartment (e.g., Competibacteraceae in surfacewater and Sulfurimonadaceae in pore water). We show that 17% of our viral MAGs clustered to viruses from other ecosystems like wastewater treatment plants and rivers. Our results also indicated that 70% of the viral community was persistent in surface waters, whereas only 13% were persistent in the pore waters taken from the hyporheic zone. Finally, we predicted linkages between 73 viral genomes and 38 microbial genomes. These putatively linked hosts included members of the Competibacteraceae, which we suggest are potential contributors to river carbon and nitrogen cycling via denitrification and nitrogen fixation. Together, these findings demonstrate that members of the surface water microbiome from this urban river are stable over multiple diurnal cycles. These temporal insights raise important considerations for ecosystem models attempting to constrain dynamics of river biogeochemical cycles.

54 ENVIRONMENTAL SCIENCES↗

Use of Arrott plots to identify Néel temperature (T{sub N}) in metamagnetic Ni{sub 48}Co{sub 6}Mn{sub 26}Al{sub 20} polycrystalline ribbons

(Ni{sub 48}Co{sub 6})Mn{sub 26}Al{sub 20} polycrystalline ribbons with B2 structure at room temperature are investigated. Considering the presence of competing magnetic interactions, Arrott-plot analysis gives T{sub N} ∼ 170 K. A broad ferromagnetic-paramagnetic transition (T{sub C}) is observed at ∼200 K. H-T phase-diagram is used to validate the presence of competing exchange interactions that persist till very close to T{sub C}. Based on Néel theory, a cluster model is used to explain the presence of ferromagnetic and antiferromagnetic clusters in the sample. Formation of ferromagnetic clusters can be understood in terms of positive exchange interactions among the Mn atoms that are neighboring Co atoms located at Ni sites.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Patch-Based Convolutional Neural Networks for Multiple Microstructural Features Detection in FIB-SEM Micrographs of Irradiated Nuclear Fuel

Focused ion beam scanning electron microscopy (FIB-SEM) tomography has increasingly been utilized for acquiring three-dimensional (3D) microstructure features at the sub-micron scale in irradiated nuclear materials. This technique involves sequential ion beam slicing followed by electron beam imaging and compositional mapping using energy dispersive spectroscopy (EDS). Despite its growing use, several challenges persist. These include the time-intensive nature of data collection of EDS data, difficulties in distinguishing between various microstructures, and issues with image alignment. These challenges currently limit the broader application of FIB-SEM tomography in the field. To overcome these limitations, we propose using convolutional neural networks (CNNs) to automate microstructure identification in SEM images. Our study introduces a new framework for identifying microstructures in irradiated U-10Zr (wt. %) metallic fuel with limited annotated data. The framework includes the creation of a reliable annotated dataset with paired SEM and ground truth data from EDS maps, the applications of CNNs for microstructure identification, and the validation of model performance. Specifically, we employed the Segment Anything Model (SAM) to align SEM images with corresponding EDS maps and focused ion beam (FIB) tomography SEM data. We evaluate several models, including Patch-based U-Net, Attention U-Net, and Residual U-Net, finding that patch-based U-Net exhibits superior segmentation performance and consistency. This approach reduces reliance on EDS detectors and aids in accelerating nuclear material analysis process, highlighting the potential of advanced deep learning techniques to improve microstructural understanding in nuclear material. This is the first framework to integrate SAM and Patch-based CNN models for semantic segmentation of irradiated nuclear materials, with potential applicability to other tomography datasets.

36 - MATERIALS SCIENCE↗

FAST STAR, SLOW STAR; OLD STAR, YOUNG STAR: SUBGIANT ROTATION AS A POPULATION AND STELLAR PHYSICS DIAGNOSTIC

Stellar rotation is a strong function of both mass and evolutionary state. Missions such as Kepler and CoRoT provide tens of thousands of rotation periods, drawn from stellar populations that contain objects at a range of masses, ages, and evolutionary states. Given a set of reasonable starting conditions and a prescription for angular momentum loss, we address the expected range of rotation periods for cool field stellar populations (∼0.4-2.0 M{sub ☉}). We find that cool stars fall into three distinct regimes in rotation. Rapid rotators with surface periods less than 10 days are either young low-mass main sequence (MS) stars, or higher mass subgiants which leave the MS with high rotation rates. Intermediate rotators (10-40 days) can be either cool MS dwarfs, suitable for gyrochronology, or crossing subgiants at a range of masses. Gyrochronology relations must therefore be applied cautiously, since there is an abundant population of subgiant contaminants. The slowest rotators, at periods greater than 40 days, are lower mass subgiants undergoing envelope expansion. We identify additional diagnostic uses of rotation periods. There exists a period-age relation for subgiants distinct from the MS period-age relations. There is also a period-radius relation that can be used as a constraint on the stellar radius, particularly in the interesting case of planet host stars. The high-mass/low-mass break in the rotation distribution on the MS persists onto the subgiant branch, and has potential as a diagnostic of stellar mass. Finally, this set of theoretical predictions can be compared to extensive datasets to motivate improved modeling.

79 ASTRONOMY AND ASTROPHYSICS↗