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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23

Cosmological constraints from the cross-correlation of DESI Luminous Red Galaxies with CMB lensing from Planck PR4 and ACT DR6

Here, we infer the growth of large scale structure over the redshift range 0.4 ≲ z ≲ 1 from the cross-correlation of spectroscopically calibrated Luminous Red Galaxies (LRGs) selected from the Dark Energy Spectroscopic Instrument (DESI) legacy imaging survey with CMB lensing maps reconstructed from the latest Planck and ACT data. We adopt a hybrid effective field theory (HEFT) model that robustly regulates the cosmological information obtainable from smaller scales, such that our cosmological constraints are reliably derived from the (predominantly) linear regime. We perform an extensive set of bandpower- and parameter-level systematics checks to ensure the robustness of our results and to characterize the uniformity of the LRG sample. We demonstrate that our results are stable to a wide range of modeling assumptions, finding excellent agreement with a linear theory analysis performed on a restricted range of scales. From a tomographic analysis of the four LRG photometric redshift bins we find that the rate of structure growth is consistent with ΛCDM with an overall amplitude that is ≃ 5-7% lower than predicted by primary CMB measurements with modest (∼ 2σ) statistical significance. From the combined analysis of all four bins and their cross-correlations with Planck we obtain S 8 = 0.765 ± 0.023, which is less discrepant with primary CMB measurements than previous DESI LRG cross Planck CMB lensing results. From the cross-correlation with ACT we obtain S 8 = 0.790 +0.024 -0.027 , while when jointly analyzing Planck and ACT we find S 8 = 0.775 +0.019 -0.022 from our data alone and σ 8 = 0.772 +0.020 -0.023 with the addition of BAO data. These constraints are consistent with the latest Planck primary CMB analyses at the ≃ 1.6-2.2σ level, and are in excellent agreement with galaxy lensing surveys.

cosmological parameters from LSS↗

NSTX-U theory, modeling and analysis results

Here, the mission of the low aspect ratio spherical tokamak NSTX-U is to advance the physics basis and technical solutions required for optimizing the configuration of next-step steady-state tokamak fusion devices. NSTX-U will ultimately operate at up to 2 MA of plasma current and 1 T toroidal field on axis for 5 s, and has available up to 15 MW of neutral beam injection power at different tangency radii and 6 MW of high harmonic fast wave heating. With these capabilities NSTX-U will develop the physics understanding and control tools to ramp-up and sustain high performance fully non-inductive plasmas with large bootstrap fraction and enhanced confinement enabled via the low aspect ratio, high beta configuration. With its unique capabilities, NSTX-U research also supports ITER and other critical fusion development needs. Super-Alfvénic ions in beam-heated NSTX-U plasmas access energetic particle (EP) parameter space that is relevant for both α-heated conventional and low aspect ratio burning plasmas. NSTX-U can also generate very large target heat fluxes to test conventional and innovative plasma exhaust and plasma facing component solutions. This paper summarizes recent analysis, theory and modelling progress to advance the tokamak physics basis in the areas of macrostability and 3D fields, EP stability and fast ion transport, thermal transport and pedestal structure, boundary and plasma material interaction, RF heating, scenario optimization and real-time control.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Real-time signal detection for Cyclotron Radiation Emission Spectroscopy measurements using antenna arrays

Cyclotron Radiation Emission Spectroscopy (CRES) is a technique for precision measurement of the energies of charged particles, which is being developed by the Project 8 Collaboration to measure the neutrino mass using tritium beta-decay spectroscopy. Project 8 seeks to use the CRES technique to measure the neutrino mass with a sensitivity of 40 meV, requiring a large supply of tritium atoms stored in a multi-cubic meter detector volume. Antenna arrays are one potential technology compatible with an experiment of this scale, but the capability of an antenna-based CRES experiment to measure the neutrino mass depends on the efficiency of the signal detection algorithms. Here, in this paper, we develop efficiency models for three signal detection algorithms and compare them using simulations from a prototype antenna-based CRES experiment as a case-study. The algorithms include a power threshold, a matched filter template bank, and a neural network based machine learning approach, which are analyzed in terms of their average detection efficiency and relative computational cost. It is found that significant improvements in detection efficiency and, therefore, neutrino mass sensitivity are achievable, with only a moderate increase in computation cost, by utilizing either the matched filter or machine learning approach in place of a power threshold, which is the baseline signal detection algorithm used in previous CRES experiments by Project 8.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Continental-scale patterns of extracellular enzyme activity in the subsoil: an overlooked reservoir of microbial activity

Abstract Chemical stabilization of microbial-derived products such as extracellular enzymes (EE) onto mineral surfaces has gained attention as a possibly important mechanism leading to the persistence of soil organic carbon (SOC). While the controls on EE activities and their stabilization in the surface soil are reasonably well-understood, how these activities change with soil depth and possibly diverge from those at the soil surface due to distinct physical, chemical, and biotic conditions remains unclear. We assessed EE activity to a depth of 1 m (10 cm increments) in 19 soil profiles across the Critical Zone Observatory Network, which represents a wide range of climates, soil orders, and vegetation types. For all EEs, activities per mass of soil correlated positively with microbial biomass (MB) and SOC, and all three of these variables decreased logarithmically with depth ( p < 0.05). Across all sites, over half of the potential EE activities per mass soil consistently occurred below 20 cm for all measured EEs. Activities per unit MB or SOC were substantially higher at depth (soils below 20 cm accounted for 80% of whole-profile EE activity), suggesting an accumulation of stabilized (i.e. mineral sorbed) EEs in subsoil horizons. The pronounced enzyme stabilization in subsurface horizons was corroborated by mixed-effects models that showed a significant, positive relationship between clay concentration and MB-normalized EE activities in the subsoil. Furthermore, the negative relationships between soil C, N, and P and C-, N-, and P-acquiring EEs found in the surface soil decoupled below 20 cm, which could have also been caused by EE stabilization. This finding suggests that EEs may not reflect soil nutrient availabilities deeper in the soil profile. Taken together, our results suggest that deeper soil horizons hold a significant reservoir of EEs, and that the controls of subsoil EEs differ from their surface soil counterparts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Long-term trends of impacts of global gasoline and diesel emissions on ambient PM 2.5 and O 3 pollution and the related health burden for 2000–2015

Global economic development and urbanization during the past two decades have driven the increases in demand of personal and commercial vehicle fleets, especially in developing countries, which has likely resulted in changes in year-to-year vehicle tailpipe emissions associated with aerosols and trace gases. However, long-term trends of impacts of global gasoline and diesel emissions on air quality and human health are not clear. In this study, we employ the Community Earth System Model in conjunction with the newly developed Community Emissions Data System as anthropogenic emission inventory to quantify the long-term trends of impacts of global gasoline and diesel emissions on ambient air quality and human health for the period of 2000–2015. Global gasoline and diesel emissions contributed to regional increases in annual mean surface PM 2.5 (particulate matter with aerodynamic diameters ≤2.5 μm) concentrations by up to 17.5 and 13.7 µg m –3 , and surface ozone (O 3 ) concentrations by up to 7.1 and 7.2 ppbv, respectively, for 2000–2015. However, we also found substantial declines of surface PM 2.5 and O 3 concentrations over Europe, the US, Canada, and China for the same period, which suggested the co-benefits of air quality and human health from improving gasoline and diesel fuel quality and tightening vehicle emissions standards. Globally, we estimate the mean annual total PM 2.5- and O 3 -induced premature deaths are 139 700–170 700 for gasoline and 205 200–309 300 for diesel, with the corresponding years of life lost of 2.74–3.47 and 4.56–6.52 million years, respectively. Diesel and gasoline emissions create health-effect disparities between the developed and developing countries, which are likely to aggravate afterwards.

54 ENVIRONMENTAL SCIENCES↗

Implications of climate change impacts for emission and land use scenario development

Scenarios of future emissions and land use produced by integrated assessment models have traditionally been developed without accounting for how climate change impacts could affect the emissions and land use trajectories themselves. This omission risks skewing our assessments of the plausible range of future emission pathways and associated Earth system changes. Beyond the salience for emission scenario development, a better integrated representation of human and Earth system changes and feedbacks would enable better anticipation of the implications of alternative socio-economic development pathways. We use the Global Change Analysis Model to investigate whether endogenizing several impacts when generating its baseline emission scenario is warranted. We do so by comparing the emissions and land use change that result from the baseline scenario with and without impacts, where impacts are implemented as exogenous changes to water availability, crop and labor productivity, and energy demand and supply. Our results indicate that the effect on global emissions leads to less than 0.1 °C increase in warming by 2100 and therefore do not support endogenizing impacts. This conclusion is conditional on our modeling framework and the specific impact channels represented but is consistent with other studies that have addressed the magnitude of feedbacks by implementing a two-way coupling. However, we do find regional impacts indicating that local economies and well-being measures may be affected significantly.

climate impacts↗

Matter-wave Atomic Gradiometer Interferometric Sensor (MAGIS-100)

MAGIS-100 is a next-generation quantum sensor under construction at Fermilab that aims to explore fundamental physics with atom interferometry over a 100 m baseline. This novel detector will search for ultralight dark matter, test quantum mechanics in new regimes, and serve as a technology pathfinder for future gravitational wave detectors in a previously unexplored frequency band. It combines techniques demonstrated in state-of-the-art 10-meter-scale atom interferometers with the latest technological advances of the world’s best atomic clocks. MAGIS-100 will provide a development platform for a future kilometer-scale detector that would be sufficiently sensitive to detect gravitational waves from known sources. Here we present the science case for the MAGIS concept, review the operating principles of the detector, describe the instrument design, and study the detector systematics.

47 OTHER INSTRUMENTATION↗

A comparative analysis of US state-level policies and programs to advance energy justice

Abstract The US energy system is undergoing massive changes that have environmental, technological, and societal implications. Decisions and actions taken now will dramatically alter the trajectory of our future energy system. Though new technologies can lessen the dangers of anthropogenic climate change, an effective and sustainable transition requires addressing social justice issues as a priority. To this end, many states have implemented policies and programs that address energy justice. A formal survey of state-level energy justice policies and programs is needed to better understand the methods used to assist communities targeted and the impacts of these efforts. Such an analysis should include an analysis of the metrics used to judge the effectiveness of the enacted policies and programs. In this paper, we analyze the energy justice policies and programs of seven different US states. From this analysis, we identify three important aspects of state energy policies. First, most policies and programs do not articulate their goals, nor cite metrics to judge their successes. This lack of transparency and accountability is a major roadblock to truly just solutions. Second, states focus on a very narrow range of solutions for energy justice issues. The most prevalent being utility bill assistance, which does not address the systemic and enduring challenges faced by many low-income or historically marginalized communities. Lastly, comprehensive energy policy does not acknowledge and address housing, employment, education, and healthcare inequities that exacerbate energy system inequities. The work presented in this paper sheds light on the progress of state-level energy justice policies and programs across the United States, and we argue more work needs to be done to understand best practices in energy justice policymaking.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

VISION: a modular AI assistant for natural human-instrument interaction at scientific user facilities

Scientific user facilities, such as synchrotron beamlines, are equipped with a wide array of hardware and software tools that require a codebase for human-computer-interaction. This often necessitates developers to be involved to establish connection between users/researchers and the complex instrumentation. The advent of generative AI presents an opportunity to bridge this knowledge gap, enabling seamless communication and efficient experimental workflows. Here we present a modular architecture for the Virtual Scientific Companion by assembling multiple AI-enabled cognitive blocks that each scaffolds large language models (LLMs) for a specialized task. With VISION, we performed LLM-based operation on the beamline workstation with low latency and demonstrated the first voice-controlled experiment at an x-ray scattering beamline. The modular and scalable architecture allows for easy adaptation to new instruments and capabilities. Development on natural language-based scientific experimentation is a building block for an impending future where a science exocortex—a synthetic extension to the cognition of scientists—may radically transform scientific practice and discovery.

36 MATERIALS SCIENCE↗

A comprehensive chemical abundance analysis of the extremely metal poor Leoncino Dwarf galaxy (AGC 198691)

ABSTRACT We re-examine the extremely metal-poor dwarf galaxy AGC 198691 using a high quality spectrum obtained by the LBT’s MODS instrument. Previous spectral observations obtained from KOSMOS on the Mayall 4-m and the Blue channel spectrograph on the MMT 6.5-m telescope did not allow for the determination of sulfur, argon, or helium abundances. We report an updated and full chemical abundance analysis for AGC 198691, including confirmation of the extremely low “direct” oxygen abundance with a value of 12 + log (O/H) = 7.06 ± 0.03. AGC 198691’s low metallicity potentially makes it a high value target for helping determine the primordial helium abundance (Yp). Though complicated by a Na i night sky line partially overlaying the He i λ5876 emission line, the LBT/MODS spectrum proved adequate for determining AGC 198691’s helium abundance. We employ the recently expanded and improved model of Aver et al., incorporating higher Balmer and Paschen lines, augmented by the observation of the infrared helium emission line He i λ10830 obtained by Hsyu et al. Applying our full model produced a reliable helium abundance determination, consistent with the expectation for its metallicity. Although this is the lowest metallicity object with a detailed helium abundance, unfortunately, due to its faintness [EW(Hβ) < 100 Å] and the compromised He i λ5876, the resultant uncertainty on the helium abundance is too large to allow a significant improvement on the measurement of Yp.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Mitigating contamination in LSS surveys: a comparison of methods

ABSTRACT Future large-scale structure surveys will measure the locations and shapes of billions of galaxies. The precision of such catalogues will require meticulous treatment of systematic contamination of the observed fields. We compare several existing methods for removing such systematics from galaxy clustering measurements. We show how all the methods, including the popular pseudo-Cℓ Mode Projection and Template Subtraction methods, can be interpreted under a common regression framework and use this to suggest improved estimators. We show how methods designed to mitigate systematics in the power spectrum can be used to produce clean maps, which are necessary for cosmological analyses beyond the power spectrum, and we extend current methods to treat the next-order multiplicative contamination in observed maps and power spectra, which reduced power spectrum errors from $\Delta \chi ^2_{\rm C_\ell }\simeq 10$ to ≃ 1 in simulated analyses. Two new mitigation methods are proposed, which incorporate desirable features of current state-of-the-art methods while being simpler to implement. Investigating the performance of all the methods on a common set of simulated measurements from Year 5 of the Dark Energy Survey, we test their robustness to various analysis cases. Our proposed methods produce improved maps and power spectra when compared to current methods, while requiring almost no user tuning. We end with recommendations for systematics mitigation in future surveys, and note that the methods presented are generally applicable beyond the galaxy distribution to any field with spatial systematics.

79 ASTRONOMY AND ASTROPHYSICS↗

Linear systematics mitigation in galaxy clustering in the Dark Energy Survey Year 1 Data

ABSTRACT We implement a linear model for mitigating the effect of observing conditions and other sources of contamination in galaxy clustering analyses. Our treatment improves upon the fiducial systematics treatment of the Dark Energy Survey (DES) Year 1 (Y1) cosmology analysis in four crucial ways. Specifically, our treatment (1) does not require decisions as to which observable systematics are significant and which are not, allowing for the possibility of multiple maps adding coherently to give rise to significant bias even if no single map leads to a significant bias by itself, (2) characterizes both the statistical and systematic uncertainty in our mitigation procedure, allowing us to propagate said uncertainties into the reported cosmological constraints, (3) explicitly exploits the full spatial structure of the galaxy density field to differentiate between cosmology-sourced and systematics-sourced fluctuations within the galaxy density field, and (4) is fully automated, and can therefore be trivially applied to any data set. The updated correlation function for the DES Y1 redMaGiC catalogue minimally impacts the cosmological posteriors from that analysis. Encouragingly, our analysis does improve the goodness-of-fit statistic of the DES Y1 3 × 2pt data set (Δχ2 = −6.5 with no additional parameters). This improvement is due in nearly equal parts to both the change in the correlation function and the added statistical and systematic uncertainties associated with our method. We expect the difference in mitigation techniques to become more important in future work as the size of cosmological data sets grows.

79 ASTRONOMY AND ASTROPHYSICS↗

The haloes and environments of nearby galaxies ( HERON ) – III. A 45-kpc spiral structure in the GLSB galaxy UGC 4599

ABSTRACT We use a 0.7-m telescope in the framework of the Halos and Environments of Nearby Galaxies (HERON) survey to probe low surface brightness (LSB) structures in nearby galaxies. One of our targets, UGC 4599, is usually classified as an early-type galaxy surrounded by a blue ring making it a potential Hoag’s Object analogue. Prior photometric studies of UGC 4599 were focused on its bright core and the blue ring. However, the HERON survey allows us to study its faint extended regions. With an 8-h integration, we detect an extremely faint outer disc with an extrapolated central surface brightness of μ0, d(r) = 25.5 mag arcsec−2 down to 31 mag arcsec−2 and a scale length of 15 kpc. We identify two distinct spiral arms of pitch angle ∼6○ surrounding the ring. The spiral arms are detected out to ∼45 kpc in radius and the faint disc continues to ∼70 kpc. These features are also seen in the GALEX far- and near-ultraviolet bands, in a deep u-band image from the 4.3-m Lowell Discovery Telescope (which reveals inner spiral structure emerging from the core), and in H i. We compare this galaxy to ordinary spiral and elliptical galaxies, giant low surface brightness (GLSB) galaxies, and Hoag’s Object itself using several standard galaxy scaling relations. We conclude that the pseudo-bulge and disc properties of UGC 4599 significantly differ from those of Hoag’s Object and of normal galaxies, pointing toward a GLSB galaxy nature and filamentary accretion of gas to generate its outer disc.

Astronomy & Astrophysics↗

Viral Load Kinetics of Severe Acute Respiratory Syndrome Coronavirus 2 in Hospitalized Individuals With Coronavirus Disease 2019

Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) kinetics remain understudied, including the impact of remdesivir. In hospitalized individuals, peak sputum viral load occurred in week 2 of symptoms, whereas viremia peaked within 1 week of symptom-onset, suggesting early systemic seeding of SARS-CoV-2. Remdesivir treatment was associated with faster viral decay.

60 APPLIED LIFE SCIENCES↗

On the parameter combinations that matter and on those that do not: data-driven studies of parameter (non)identifiability

Abstract We present a data-driven approach to characterizing nonidentifiability of a model’s parameters and illustrate it through dynamic as well as steady kinetic models. By employing Diffusion Maps and their extensions, we discover the minimal combinations of parameters required to characterize the output behavior of a chemical system: a set of effective parameters for the model. Furthermore, we introduce and use a Conformal Autoencoder Neural Network technique, as well as a kernel-based Jointly Smooth Function technique, to disentangle the redundant parameter combinations that do not affect the output behavior from the ones that do. We discuss the interpretability of our data-driven effective parameters, and demonstrate the utility of the approach both for behavior prediction and parameter estimation. In the latter task, it becomes important to describe level sets in parameter space that are consistent with a particular output behavior. We validate our approach on a model of multisite phosphorylation, where a reduced set of effective parameters (nonlinear combinations of the physical ones) has previously been established analytically.

Evangelou, Nikolaos↗

Uniaxial tensile mechanical properties from a scratch on ultra-fine grained tungsten

We demonstrate that surface-based mechanical testing can be used to quantify a wide range of mechanical properties determined using traditional uniaxial tension experiments. These include mapping of dynamic stress–strain behaviour, which can be used as a screening tool for uniaxial tensile ductility (uniform elongation), fracture toughness (K C ), which is shown to be in good agreement with reported plane-strain K IC , as well work-hardening exponents (n), activation volumes (V) energies (Q) and strain-rate sensitivity (m) exponents as a function of temperature. Advantages of the surface-based approach are the ability to work with significantly smaller volumes and accommodate processing defects like pores, voids and cracks. These methods are applied to ultra-fine grained tungsten (average grain size of 650 nm), as it is an ideal candidate for alloy development efforts in advanced energy systems. Tungsten is a useful baseline as it exhibits a near-ambient temperature (approx. 200°C) ductile-to-brittle transition temperature (DBTT), enabling validation efforts for the proposed methods, and extraordinary material properties, including the highest melting temperature of any metal and complex temperature and strain-rate dependencies linked to transitions in dislocation mechanisms.

36 MATERIALS SCIENCE↗

Single pion production and pion propagation in A chilles

We extend the applicability of A chilles (A CHIcagoLand Lepton Event Simulator) by incorporating the single pion production mechanism in a fully exclusive fashion. The electroweak interaction vertex is modeled by combining the state-of-the-art dynamical coupled-channels approach with realistic hole spectral functions, which account for correlations in both the initial target state and the residual spectator system. Final-state interactions are treated using a semiclassical intranuclear cascade that leverages nuclear configurations to determine the correlated spatial distribution of protons and neutrons. The meson-baryon scattering amplitudes used in the cascade are computed within the dynamical coupled-channels framework, consistent with the electroweak vertex. To model pion absorption, we employ the optical potential approach of Oset and Salcedo [Nucl. Phys. A484, 557 (1988).]. As an alternative approach, we explicitly model the production and propagation of resonances which mediate pion-nucleon scattering and pion absorption. We validate our approach against pion-nucleon and pion-nucleus scattering data, and present comparisons with electron- and neutrino-nucleus measurements from e⁢4⁢𝜈, T2K, MINER⁢𝜈⁢A, and MicroBooNE.

Isaacson, Joshua [Michigan State Univ., East Lansi↗

Realizing the scientific program with polarized ion beams at the future BNL Electron Ion Collider

Polarized ion beams at the Electron Ion Collider (EIC) are essential to address some of the most important open questions at the twenty-first century frontiers of understanding of the fundamental structure of matter. Here, in this work, we summarize the science case and identify polarized 2 H, 3 He, 6 Li, and 7 Li ion beams as critical technology that will enable experiments which address the most important science. Furthermore, we discuss the required ion polarimetry and spin manipulation at the EIC. The current EIC accelerator design is presented. We identify a significant research and development effort across national and international laboratories and universities that is required over about a decade to realize the polarized ion beams and estimate (based on previous experience) that it will require about 20 full-time equivalent (FTE) over 10 years (or a total of about 200 FTE-years) of personnel, including graduate students, postdoctoral researchers, technicians, and engineers. Attracting, educating, and training a new generation of physicists in experimental spin techniques will be essential for the successful realization. Artificial intelligence and machine learning are seen as having significant potential for both acceleration of research and development and amplification of discovery in the optimal realization of this unique quantum technology on a cutting-edge collider. The research and development effort is synergistic with research in atomic physics and fusion energy science.

43 PARTICLE ACCELERATORS↗