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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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NASA NTRS1998

RH1020 Single Event Clock Upset Summary Report

This report summarizes the testing and analysis of "single event clock upset' in the RH1020. Also included are SEU-rate predictions and design recommendations for risk analysis and reduction. The subject of "upsets" in the RH1020 is best understood by using a model consisting of a global clock buffer and a D-type flip-flop as the basic memory unit. The RH1020 is built on the ACT 1 family architecture. As such, it has one low-skew global clock buffer with a TTL-level input threshold that is accessed via a single dedicated pin. The clock signal is driven to full CMOS levels, buffered, and sent to individual row buffers with one buffer per channel. For low-skew performance, the outputs of all of the RH1020 row buffers are shorted together via metal lines, as is done in the A1020B. All storage in the RH1020 consists of routed flip-flops, constructed with multiplexors and feedback through the routing segments. A simple latch can be constructed from a single (combinatorial or C) module; an edge-triggered flip-flop is constructed using two concatenated latches. There is no storage in the I/O modules. The front end of the clock buffering circuitry, at a common point relative to the row buffer, is a sub-circuit that was determined to be the most susceptible to heavy ions. This is due, in part, to its smaller transistors compared to the rest of the circuitry. This conclusion is also supported by SPICE simulations and an analysis of the heavy ion data, described in this report. The edge triggered D flip-flop has two single-event-upset modes. Mode one, called C-module upset, is caused by a heavy ion striking the C-module's sensitive area on the silicon and produces a soft single bit error at the output of the flip-flop. Mode two, called clock upset, is caused by a heavy ion strike on the clock buffer, generating a runt pulse interpreted as a false clock signal and consequently producing errors at the flip-flop outputs. C-module upset sensitivity in the RH1020 is essentially the same as that of its ACT 1 siblings (A1020, A1020A and A1020B), which were well tested, analyzed, and documented in the literature.

Katz, Richard B.↗
DOE OSTI2021

Global electroweak symmetric vacuum

Although the Higgs potential in the Standard Model (SM) contains only a simple electroweak symmetry breaking vacuum in the small field region, additional metastable or global vacua could exist in models beyond the SM. In this paper, we study one intriguing scenario with an additional electroweak symmetric vacuum that could be the global one. For the thermal universe ending at the current metastable vacuum, the electroweak symmetry should stay non-restored at high temperatures. We realize the scenario in a model with Higgs-portal couplings to SM singlet scalars with approximately global O(N) symmetries with a large N. For a large portion of model parameter space, both the quantum and thermal tunneling rates are suppressed such that our current metastable vacuum is long-lived enough. Our scenario predicts order-one changes for the Higgs self-couplings and a large contribution to the signal of the off-shell Higgs invisible decay. It can be partly probed at the LHC Run 3 and well tested at the high luminosity LHC. We also discuss the subcritical (anti-de Sitter) bubbles from the thermal tunneling that could have a large population and interesting cosmological implications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

express: Extensible, high-level workflows for swifter ab initio materials modeling

In this work, we introduce an open-source Julia project, express, an extensible, lightweight, high-throughput, high-level workflow framework that aims to automate ab initio calculations for the materials science community. express is shipped with well-tested workflow templates, including structure optimization, equation of state (EOS) fitting, phonon spectrum (lattice dynamics) calculation, and thermodynamic property calculation in the framework of the quasi-harmonic approximation (QHA). It is designed to be highly modularized so that its components can be reused across various occasions, and customized workflows can be built on top of that. Users can also track the status of workflows in real-time, and rerun failed jobs thanks to the data lineage feature express provides. Finally, two working examples, i.e., all workflows applied to lime and akimotoite, are also presented in the code and this paper.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Gigaton commercial-scale carbon storage and mineralization potential in stacked Columbia River basalt reservoirs

This work presents a detailed supercritical CO 2 storage resource estimation for the stacked basalt reservoirs in the Grande Ronde Basalt of the Columbia River Basalt Group in eastern Washington and Oregon. The assessment aims to derisk the commercialization potential of geologic carbon storage in basalt by leveraging both structural and mineralization trapping of CO 2 in basalt. The structural closures formed by anticlinal ridges and synclinal valleys in Yakima Fold Belt are excellent physical traps to accommodate injected supercritical CO 2 . Rigorous hydraulic testing, well logs and simulation results from the Wallula Basalt Pilot #1 well showed the occurrence of 17 suitable permeable injection zones (up to 2,496 mD) intercalated with dense seals (~2.6E-10 mD) in the Grand Ronde Basalt. In addition, geochemical studies showed fast reactions between supercritical CO 2 and dissolved basalt minerals to form stable carbonates. In conclusion, our calculation indicates up to 40 gigatons (P90) of mineralization storage resources exist in the Grande Ronde Basalt reservoirs.

58 GEOSCIENCES↗
DOE OSTI2023

ExactPack: A python library of exact analytic solutions

Verification of multi-physics simulation software against problems with known analytic or semi-analytic solutions is an important aspect of research into a wide variety of fields involving the motion of fluids, shock physics and other dynamic material properties. Previous work comparing simulation results against analytic solutions has been ad-hoc, with developers frequently writing their own analytic solvers. This has resulted in a large amount of duplicated effort. The python library ExactPack has been developed as a collection of analytic and semi-analytic solvers to a variety of multi-physics problems, providing a consistent API to a set of well-tested solver implementations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Modeling Holocene Peatland Carbon Accumulation in North America

Peatlands are a large carbon reservoir. Yet the quantification of their carbon stock still has a large uncertainty due to lacking observational data and well-tested peatland biogeochemistry models. Here, a process-based peatland model was calibrated using long-term peat carbon accumulation data at multiple sites in North America. The model was then applied to quantify the peat carbon accumulation rates and stocks within North America over the last 12,000 years. We estimated that 85–174 Pg carbon was accumulated in North American peatlands over the study period including 0.37–0.76 Pg carbon in subtropical peatlands. During the period from 10,000 to 8,000 years ago, the warmer and wetter conditions might have played an important role in stimulating peat carbon accumulation by enhancing plant photosynthesis. Enhanced peat decomposition due to warming slowed the carbon accumulation through the rest of the Holocene. While recent modeling studies indicate that the northern peatlands will continue to act as a carbon sink in this century, our studies suggest that future enhanced peat decomposition accompanied by peatland areal changes induced by permafrost degradation and other disturbances shall confound the sink and source analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Impoverishing Roots Will Improve Wheat Yield and Profitability Through Increased Water and Nitrogen Use Efficiencies

We report that more than a 60% increase in crop production is required by the 2050's to feed a growing world population. Understanding how plant functional traits and field management affect crop yields has the potential to improve agricultural productivity, minimize economic and environmental losses, and maximize food security. We explored the influence of winter wheat root characteristics and management on winter wheat growth, yield, and profit using a mechanistic and well-tested ecosystem and crop model, ecosys. We applied and further tested ecosys at an agricultural farm growing winter wheat in Ardmore, Oklahoma, United States. The model accurately predicted observed shoot carbon (R 2 = 0.95), soil moisture (R 2 = 0.67), soil temperature (R 2 = 0.91), and yield (percent error = 17%). Numerical optimization experiments were conducted to explore potential improvements of winter wheat yield and profit by modifying root characteristics, including root radius and root:shoot carbon transfer conductance, and fertilizer inputs. Our results show the potential for simultaneously improving winter wheat yields and profits. The optimum conditions were found to be in the range of root radius between 0.1 and 0.3 mm, carbon transfer conductance between 0.004 and 0.01 h -1 , and the currently applied fertilizer rate of 112 kg ha -1 . Under these conditions, improvements in yields and profits of up to approximately 25% and 110%, respectively, were modeled compared to those under baseline root traits. These improvements were achieved by impoverishing root structures, thereby increasing nutrient allocation to grains. Our results also demonstrate and motivate model structures that integrate the complex network of plant physiology, soil nutrient biogeochemistry, hydrology, and management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Alaskan carbon-climate feedbacks will be weaker than inferred from short-term experiments

Climate warming is occurring fastest at high latitudes. Based on short-term field experiments, this warming is projected to stimulate soil organic matter decomposition, and promote a positive feedback to climate change. We show here that the tightly coupled, nonlinear nature of high-latitude ecosystems implies that short-term (<10 year) warming experiments produce emergent ecosystem carbon stock temperature sensitivities inconsistent with emergent multi-decadal responses. We first demonstrate that a well-tested mechanistic ecosystem model accurately represents observed carbon cycle and active layer depth responses to short-term summer warming in four diverse Alaskan sites. We then show that short-term warming manipulations do not capture the non-linear, long-term dynamics of vegetation, and thereby soil organic matter, that occur in response to thermal, hydrological, and nutrient transformations belowground. Our results demonstrate significant spatial heterogeneity in multi-decadal Arctic carbon cycle trajectories and argue for more mechanistic models to improve predictive capabilities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Attributing human mortality from fire PM 2.5 to climate change

Climate change intensifies fire smoke, emitting hazardous air pollutants that impact human health. However, the global influence of climate change on fire-induced health impacts remains unquantified. Here, in this study, we used three well-tested fire-vegetation models in combination with a chemical transport model and health risk assessment framework to attribute global human mortality from fire fine particulate matter (PM 2.5 ) emissions to climate change. Of the 46401 (1960s) –to 98748 (2010s) annual fire PM 2.5 mortalities, 669 (1.2%, 1960s) –to 12566 (12.8%, 2010s) were attributed to climate change. The most substantial influence of climate change on fire mortality occurred in South America, Australia, and Europe, coinciding with decreased relative humidity, and in boreal forests with increased air temperature. Increasing relative humidity lowered fire mortality in other regions, like South Asia. Our study highlights the role of climate change in fire mortality, aiding public health authorities in spatial targeting adaptation measures for sensitive fire-prone areas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Direct implicit and explicit energy-conserving particle-in-cell methods for modeling of capacitively coupled plasma devices

Achieving large-scale kinetic modeling is a crucial task for the development and optimization of modern plasma devices. With the trend of decreasing pressure in applications, such as plasma etching, kinetic simulations are necessary to self-consistently capture the particle dynamics. The standard, explicit, electrostatic, momentum-conserving particle-in-cell method suffers from restrictive stability constraints on spatial cell size and temporal time step, requiring resolution of the electron Debye length and electron plasma period, respectively. This results in a very high computational cost, making the technique prohibitive for large volume device modeling. We investigate the direct implicit algorithm and the explicit energy conserving algorithm as alternatives to the standard approach, both of which can reduce computational cost with a minimal (or controllable) impact on results. These algorithms are implemented into the well-tested EDIPIC-2D and LTP-PIC codes, and their performance is evaluated via 2D capacitively coupled plasma discharge simulations. The investigation reveals that both approaches enable the utilization of cell sizes larger than the Debye length, resulting in a reduced runtime, while incurring only minor inaccuracies in plasma parameters. The direct implicit method also allows for time steps larger than the electron plasma period; however, care must be taken to avoid numerical heating or cooling. It is demonstrated that by appropriately adjusting the ratio of cell size to time step, it is possible to mitigate this effect to an acceptable level.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Benchmark between antenna code TOPICA, RAPLICASOL and Petra-M for the ICRH ITER antenna

ITER will be equipped with three plasma heating systems: neutral beam (NB), electron cyclotron (EC), and ion cy-clotron resonance heating (ICRH). The latter consists of two identical ICRH antennas to deliver 20 MW to the plasma (baseline, upgradable to 40 MW). ICRH will play a crucial role in the ignition and sustainment of burning plasmas in ITER. A high fidelity and robust modeling effort to understand the interaction of the IC waves with the scrape-off-layer (SOL) plasma is a very important aspect. Among the main important research topics, we have the assessment of the antenna loading for different plasma scenarios, the role of the lower hybrid resonance in front of the antenna and how to include it in our models, and the RF sheath boundary conditions to evaluate the antenna impurity generation. In this work, we tackle the first of these by reporting on ICRF simulations employing the Petra-M code, which is an electromagnetic simulation tool for modeling RF wave propagation based on MFEM [http://mfem.org] for the ITER ICRH antenna. Moreover, a benchmark between the well tested antenna codes TOPICA, RAPLI-CASOL, which is based on COMSOL [www.comsol.com], and the Petra-M code is also presented. In conclusion, S- and Z-matrices and wave electric field are compared showing an excellent agreement among these codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Development and Test Results of Thermocouples Used in the TRISO-Fuel Irradiation Experiment AGR-5/6/7

High-temperature gas reactor irradiation experiments create unique challenges for thermocouple-based temperature measurements. High-temperature industrial thermocouples suffer rapid decalibration due to transmutation of the thermoelements from neutron absorption. For lower-temperature applications, Type K and Type N thermocouples are affected by neutron irradiation only to a limited extent. But until recently, the use of these nickel-based thermocouples was limited when the temperature exceeded 1050°C due to drift related to phenomena other than nuclear irradiation. Certain portions of the AGR-5/6/7 experiment experienced temperatures higher than any of the previous AGR tests, up to 1500°C. Recognizing the limitations of existing thermometry to measure such high temperatures, the sponsor of the AGR-5/6/7 test supported a development and testing program for thermocouples capable of low-drift operation at temperatures above 1100°C. This program included additional development of high-temperature irradiation-resistant thermocouples based on molybdenum/niobium thermoelements, which have been studied at Idaho National Laboratory since circa 2004. A step change in accuracy and long-term stability of this thermocouple type was achieved as part of the AGR-5/6/7 thermometry development program. Additionally, long-term testing (7000+ h) at 1250°C of Type N thermocouples utilizing a customized sheath developed at the University of Cambridge has been completed with excellent low-drift results. The results of this testing as well as testing of the improved high-temperature irradiation-resistant design are reported herein. Both the improved high-temperature irradiation-resistant and the Cambridge Type N thermocouple types were incorporated into the AGR-5/6/7 test, which began irradiation in February 2018 and was completed in July 2020. Finally, a summary of the performance of the thermocouples incorporated into the AGR-5/6/7 test is included herein.

In-pile instrumentation↗
DOE OSTI2021

Non-growing season plant nutrient uptake controls Arctic tundra vegetation composition under future climate

Abstract Plant growth and distribution in high-latitude tundra ecosystems is strongly limited by nutrient availability and is critical for quantifying centennial-scale carbon-climate interactions. However, land model representations of plant–nutrient interactions are uncertain, leading to poor comparisons with high-latitude observations. Although it has been recognized for decades in the observational community that plants continue to acquire nutrients well past when aboveground activity has ceased, most large-scale land models ignore this process. Here we address the role tundra plant nutrient acquisition during the non-growing season (NGS) has on centennial-scale vegetation growth and dynamics, with a focus on shrub expansion. We apply a well-tested mechanistic model of coupled plant, microbial, hydrological, and thermal dynamics that explicitly represents nutrient acquisition based on plant and microbial traits, thereby allowing a prognostic assessment of NGS nutrient uptake. We first show that the model accurately represents observed seasonality of NGS plant nutrient uptake in a northern Alaskan tundra site. Applying the model across the North America tundra indicates that NGS nutrient uptake is consistent with observations and ranges between ∼5% and 50% of annual uptake, with large spatial variability and dependence on plant functional type. We show that NGS plant nutrient acquisition strongly enhances modeled 21 st century tundra shrub growth and expansion rates. Our results suggest that without NGS nutrient uptake, total shrub aboveground dominance would be ∼50% lower, limited primarily by their inability to grow tall enough to maximize their inherent capacity for light competition. Evergreen shrubs would be more strongly affected because of their relatively lower capacity for nutrient remobilization and acquisition compared to deciduous shrubs. Our results highlight the importance of NGS plant and soil processes on high-latitude biogeochemistry and vegetation dynamics and motivate new observations and model structures to represent these dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Rapidly changing high-latitude seasonality: implications for the 21st century carbon cycle in Alaska

Seasonal variations in high-latitude terrestrial carbon (C) fluxes are predominantly driven by air temperature and radiation. At present, high-latitude net C uptake is largest during the summer. Recent observations and modeling studies have demonstrated that ongoing and projected climate change will increase plant productivity, microbial respiration, and growing season lengths at high-latitudes, but impacts on high-latitude C cycle seasonality (and potential feedbacks to the climate system) remain uncertain. Here we use ecosys, a well-tested and process-rich mechanistic ecosystem model that we evaluate further in this study, to explore how climate warming under an RCP8.5 scenario will shift C cycle seasonality in Alaska throughout the 21st century. The model successfully reproduced recently reported large high-latitude C losses during the fall and winter and yet still predicts a high-latitude C sink, pointing to a resolution of the current conflict between process-model and observation-based estimates of high-latitude C balance. We find that warming will result in surprisingly large changes in net ecosystem exchange (NEE; defined as negative for uptake) seasonality, with spring net C uptake overtaking summer net C uptake by year 2100. This shift is driven by a factor of 3 relaxation of spring temperature limitation to plant productivity that results in earlier C uptake and a corresponding increase in magnitude of spring NEE from –19 to –144 gC m –2 season –1 by the end of the century. Although a similar relaxation of temperature limitation will occur in the fall, radiation limitation during those months will limit increases in C fixation. Additionally, warmer soil temperatures and increased carbon inputs from plants lead to combined fall and winter C losses (163 gC m –2 ) that are larger than summer net uptake (123 gC m –2 season –1 ) by year 2100. However, this increase in microbial activity leads to more rapid N cycling and increased plant N uptake during the fall and winter months that supports large increases in spring NPP. Due to the large increases in spring net C uptake, the high-latitude atmospheric C sink is projected to sustain throughout this century. Our analysis disentangles the effects of key environmental drivers of high-latitude seasonal C balances as climate changes over the 21st century.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Soil incubation methods lead to large differences in inferred methane production temperature sensitivity

Abstract Quantifying the temperature sensitivity of methane (CH 4 ) production is crucial for predicting how wetland ecosystems will respond to climate warming. Typically, the temperature sensitivity (often quantified as a Q 10 value) is derived from laboratory incubation studies and then used in biogeochemical models. However, studies report wide variation in incubation-inferred Q 10 values, with a large portion of this variation remaining unexplained. Here we applied observations in a thawing permafrost peatland (Stordalen Mire) and a well-tested process-rich model ( ecosys ) to interpret incubation observations and investigate controls on inferred CH 4 production temperature sensitivity. We developed a field-storage-incubation modeling approach to mimic the full incubation sequence, including field sampling at a particular time in the growing season, refrigerated storage, and laboratory incubation, followed by model evaluation. We found that CH 4 production rates during incubation are regulated by substrate availability and active microbial biomass of key microbial functional groups, which are affected by soil storage duration and temperature. Seasonal variation in substrate availability and active microbial biomass of key microbial functional groups led to strong time-of-sampling impacts on CH 4 production. CH 4 production is higher with less perturbation post-sampling, i.e. shorter storage duration and lower storage temperature. We found a wide range of inferred Q 10 values (1.2–3.5), which we attribute to incubation temperatures, incubation duration, storage duration, and sampling time. We also show that Q 10 values of CH 4 production are controlled by interacting biological, biochemical, and physical processes, which cause the inferred Q 10 values to differ substantially from those of the component processes. Terrestrial ecosystem models that use a constant Q 10 value to represent temperature responses may therefore predict biased soil carbon cycling under future climate scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Changes in high-latitude surface energy balance driven by snowpack and vegetation dynamics under warmer climate

With rapid climate warming, expected changes in snowpack and vegetation will alter the seasonal surface albedo of high-latitude ecosystems. The extent to which these albedo changes may affect surface energy balances and thus soil temperatures is uncertain, but represents a potentially important component of ecosystem feedbacks to climate change. Here, we apply a well-tested process-rich ecosystem model, ecosys , to examine changes in seasonal surface albedo and soil temperature driven by climate-induced snowpack and vegetation changes across Alaska under a warmer twenty-first century climate. Under the Representative Concentration Pathway 8.5 climate change scenario, the modeled changes in surface albedo exhibited large seasonal and spatial variations. We found spring albedo decreases driven by increases in snow-free periods (>20 d) and an extended growing season length that resulted in greater gains in leaf area index (LAI) in most parts of Alaska. In contrast, we modeled increases in summer and winter albedo (despite modeled increases in LAI) across much of the boreal forest due to an increased proportion of aspen, which has a higher leaf albedo than the currently dominant black spruce. Modeled latent heat fluxes generally increase across the twenty-first century, particularly during the spring and summer. Overall, climate warming and changes in surface energy fluxes resulted in a 3.5 ± 0.50 °C increase in spatial- and annual-averaged top 10 cm surface soil temperatures across Alaskan ecosystems by the year 2100, with larger increases in tundra than boreal forest regions. We conclude that under warmer climates, seasonal variations in albedo and surface energy fluxes are particularly pronounced during the spring and summer, driven by changes in snowpack and vegetation dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Non-Gaussianity constraints with anisotropic μ distortion measurements from Planck

ABSTRACT Primordial non-Gaussianity can source μ-distortion anisotropies that are correlated with the large-scale temperature and polarization signals of the cosmic microwave background (CMB). A measurement of μT and μE correlations can therefore be used to constrain it on wavelengths of perturbations not directly probed by the standard CMB anisotropies. We carry out a first rigorous search for μ-distortion anisotropies with Planck data, applying the well-tested constrained ILC component-separation method combined with the needlet framework. We correlate the reconstructed μ map with the CMB anisotropies to derive constraints on the amplitude fNL of the local form bispectrum, specifically on the squeezed configurations with effective wavenumbers $k_s \simeq {740}\, \mathrm{Mpc^{-1}}$ and $k_L \simeq {0.05}\, \mathrm{Mpc^{-1}}$, improving previously estimated constraints by more than an order of magnitude. This enhancement is owing to the fact that we are able to use the full multipole information by carefully controlling biases and systematic effects in the analysis. We also for the first time incorporate constraints from measurements of μE correlations, which further tighten the limits. A combination of the derived Planck μT and μE power spectra yields |fNL| ≲ 6800 (95 per cent c.l.) on this highly squeezed bispectrum. This is only ≃3 times weaker than the anticipated constraint from Litebird. Furthermore we show that a combination of Litebird with Planck can improve the expected future constraint by ${\simeq}20{{\%}}$. These limits can be used to constrain multifield inflation models and primordial black hole formation scenarios, thus providing a promising novel avenue forward in CMB cosmology.

Rotti, Aditya (ORCID:0000000341245226)↗
DOE OSTI2022

Image feature extraction and galaxy classification: a novel and efficient approach with automated machine learning

ABSTRACT In this work, we explore the possibility of applying machine learning methods designed for 1D problems to the task of galaxy image classification. The algorithms used for image classification typically rely on multiple costly steps, such as the point spread function deconvolution and the training and application of complex Convolutional Neural Networks of thousands or even millions of parameters. In our approach, we extract features from the galaxy images by analysing the elliptical isophotes in their light distribution and collect the information in a sequence. The sequences obtained with this method present definite features allowing a direct distinction between galaxy types. Then, we train and classify the sequences with machine learning algorithms, designed through the platform Modulos AutoML. As a demonstration of this method, we use the second public release of the Dark Energy Survey (DES DR2). We show that we are able to successfully distinguish between early-type and late-type galaxies, for images with signal-to-noise ratio greater than 300. This yields an accuracy of $86{{\ \rm per\ cent}}$ for the early-type galaxies and $93{{\ \rm per\ cent}}$ for the late-type galaxies, which is on par with most contemporary automated image classification approaches. The data dimensionality reduction of our novel method implies a significant lowering in computational cost of classification. In the perspective of future data sets obtained with e.g. Euclid and the Vera Rubin Observatory, this work represents a path towards using a well-tested and widely used platform from industry in efficiently tackling galaxy classification problems at the peta-byte scale.

79 ASTRONOMY AND ASTROPHYSICS↗