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DOE OSTI2023

MaNGA DynPop – II. Global stellar population, gradients, and star-formation histories from integral-field spectroscopy of 10K galaxies: link with galaxy rotation, shape, and total-density gradients

ABSTRACT This is the second paper of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) Dynamics and stellar Population (DynPop) series, which analyses the global stellar population, radial gradients, and non-parametric star-formation history of ∼10K galaxies from the MaNGA Survey final data release 17 and relates them with dynamical properties of galaxies. We confirm the correlation between the stellar population properties and the stellar velocity dispersion σe, but also find that younger galaxies are more metal-poor at fixed σe. Stellar age, metallicity, and mass-to-light ratio (M*/L) all decrease with increasing galaxy rotation, while their radial gradients become more negative (i.e. lower value at the outskirts). The exception is the slow rotators, which also appear to have significantly negative metallicity gradients, confirming the mass–metallicity gradient correlation. Massive disc galaxies in the green valley, on the $(\sigma _{\rm e},\rm age)$ plane, show the most negative age and metallicity gradients, consistent with their old central bulges surrounded by young star-forming discs and metal-poor gas accretion. Galaxies with high σe, steep total mass-density slope, low dark matter fraction, high M*/L, and high metallicity have the highest star-formation rate at earlier times, and are currently quenched. We also discover a population of low-mass star-forming galaxies with low rotation but physically distinct from the massive slow rotators. A catalogue of these stellar population properties is provided publicly.

Astronomy & Astrophysics↗

DOE OSTI2025

Predicting the Galactic population of free-floating planets from realistic initial conditions

ABSTRACT We present the first prediction for the mass distribution function of Galactic free-floating planets (FFPs) that aims to accurately include the relative contributions of multiple formation pathways and stellar populations. We derive our predicted distribution from dedicated simulations of planet birth, growth, migration, and ejection around circumbinary systems and extend these results to also include the contributions from single and wide binary systems. Our resulting FFP mass distribution shows several distinct features, including a strong peak at ${\sim} 8\, {\rm M}_{\oplus }$ arising from the transition between pebble and gas accretion regimes and a trough at ${\sim} 1\, {\rm M}_{\oplus }$ due to the shift in the dominant ejection process from planet–planet scattering to ejection through interactions with stars in circumbinary systems. We find that interactions with the central binary in close circumbinary systems are likely the dominant progenitor for FFPs more massive than Earth, leading to a steep power-law dependence in mass that agrees well with existing observations. In contrast, we find planet–planet scattering events in single and wide binary systems likely produce the majority of planets at Mars mass and below, resulting in a shallower power-law dependence. Our results suggest that existing extrapolations into the sub-terrestrial mass range may significantly overestimate the true FFP abundance. The features we predict in the mass distribution of FFPs will be detectable by upcoming space-based microlensing surveys and, if observed, will provide key insight into the origins of FFPs and the environments in which they form.

Coleman, Gavin A. L. (ORCID:0000000151118963)↗

DOE OSTI2025

On the relationship between the cosmic web and the alignment of galaxies and AGN jets

ABSTRACT The impact of active galactic nuclei (AGNs) on the evolution of galaxies explains the steep decrease in the number density of the most massive galaxies in the Universe. However, the fuelling of the AGN and the efficiency of this feedback largely depend on their environment. We use data from the Low Frequency Array Two-metre Sky Survey Data Release 2 (DR2), the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys, and the Sloan Digital Sky Survey DR12 to make the first study of the orientations of radio jets and their optical counterpart in relation to the cosmic web environment. We find that close to filaments ($\lesssim \!\! 11 \ \rm Mpc$), galaxies tend to have their optical major axes aligned with the nearest filaments. On the other hand, radio jets, which are generally aligned perpendicularly to the optical major axis of the host galaxy, show more randomized orientations with respect to host galaxies within ${\lesssim} 8 \, \rm Mpc$ of filaments. These results support the scenario that massive galaxies in cosmic filaments grow by numerous mergers directed along the orientation of the filaments while experiencing chaotic accretion of gas on to the central black hole. The AGN-driven jets consequently have a strong impact preferentially along the minor axes of dark matter haloes within filaments. We discuss the implications of these results for large-scale radio jet alignments, intrinsic alignments between galaxies, and the azimuthal anisotropy of the distribution of circumgalactic medium and anisotropic quenching.

Jung, S. Lyla (ORCID:0000000155123735)↗

DOE OSTI2025

MolViewSpec: a Mol* extension for describing and sharing molecular visualizations

Data visualization is a pivotal component of a structural biologist’s arsenal. The Mol* Viewer makes molecular visualizations available to broader audiences via most web browsers. While Mol* provides a wide range of functionality, it has a steep learning curve and is only available via a JavaScript interface. To enhance the accessibility and usability of web-based molecular visualization, we introduce MolViewSpec (molstar.org/mol-view-spec), a standardized approach for defining molecular visualizations that decouples the definition of complex molecular scenes from their rendering. Scene definition can include references to commonly used structural, volumetric, and annotation data formats together with a description of how the data should be visualized and paired with optional annotations specifying colors, labels, measurements, and custom 3D geometries. Developed as an open standard, this solution paves the way for broader interoperability and support across different programming languages and molecular viewers, enabling more streamlined, standardized, and reproducible visual molecular analyses. MolViewSpec is freely available as a Mol* extension and a standalone Python package.

Midlik, Adam [European Bioinformatics Institute (U↗

DOE OSTI2024

Watching the Grand Ethiopian Renaissance Dam from a distance: Implications for sustainable water management of the Nile water

Increased demands for sustainable water and energy resources in densely populated basins have led to the construction of dams, which impound waters in artificial reservoirs. In many cases, scarce field data led to the development of models that underestimated the seepage losses from reservoirs and ignored the role of extensive fault networks as preferred pathways for groundwater flow. We adopt an integrated approach (remote sensing, hydrologic modeling, and field observations) to assess the magnitude and nature of seepage from such systems using the Grand Ethiopian Renaissance Dam (GERD), Africa's largest hydropower project, as a test site. The dam was constructed on the Blue Nile within steep, highly fractured, and weathered terrain in the western Ethiopian Highlands. The GERD Gravity Recovery and Climate Experiment Terrestrial Water Storage (GRACETWS), seasonal peak difference product, reveals significant mass accumulation (43 ± 5 BCM) in the reservoir and seepage in its surroundings with progressive south-southwest mass migration along mapped structures between 2019 and 2022. Seepage, but not a decrease in inflow or increase in outflow, could explain, at least in part, the observed drop in the reservoir's water level and volume following each of the three fillings. Using mass balance calculations and GRACETWS observations, we estimate significant seepage (19.8 ± 6 BCM) comparable to the reservoir's impounded waters (19.9 ± 1.2 BCM). Investigating and addressing the seepage from the GERD will ensure sustainable development and promote regional cooperation; overlooking the seepage would compromise hydrological modeling efforts on the Nile Basin and misinform ongoing negotiations on the Nile water management.

GRACE and GRACE-FO↗

DOE OSTI2026

Melting temperature of bismuth to 55 GPa using synchrotron X-ray phase contrast imaging

The melting temperature of elemental bismuth under high pressure has been measured to 55 GPa using synchrotron X-ray phase-contrast imaging in the laser-heated diamond anvil cell. Imaging of solid-liquid interface formation, combined with radiometric temperature and X-ray diffraction measurements, reveals a pronounced reduction in melting boundary slope in Bi-V with pressure. The unusually steep initial slope is attributed to low configurational entropy of melting, arising from structural ordering and coordination matching in the cool liquid, while slope reduction is driven by entropy increase correlated with significant liquid structure changes with rising pressure and temperature. Finally, the data rule out kinetic effects on melting in shock compression experiments and demonstrate the need for improved theoretical phase diagrams.

Materials science↗

DOE OSTI2024

High-volume tunable resonator for axion searches above 7 GHz

In this research, we present results from an experimental demonstration of a tunable thin-shell axion haloscope whose geometry decouples its overall volume from its resonant frequency, thereby evading the steep sensitivity degradation at high frequencies. An aluminum 2.6-l (41⁢λ 3 ) prototype, which tunes from 7.1 to 8.0 GHz, was fabricated and characterized at room temperature. An axion-sensitive, straightforwardly tunable TM 010 mode is clearly identified with a room-temperature quality factor, Q, of approximately 5000. The on-resonance E-field distribution is mapped and found to agree with numerical calculations. Anticipating future cryogenic operation, we develop an alignment protocol relying only on rf measurements of the cavity, maintaining a form factor of 0.57 across the full tuning range. These measurements demonstrate the feasibility of cavity-based haloscopes with operating volume V $\gg$ λ 3 . We discuss plans for future development and the parameters required for a thin-shell haloscope exploring the postinflationary axion parameter space (approximately 4 to 30 GHz) at Dine-Fischler-Srednicki-Zhitnitsky sensitivity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Neutron scattering study of fluctuating and static spin correlations in the anisotropic spin glass Fe 2 Ti O 5

The anisotropic spin-glass transition, in which spin freezing is observed only along the c axis in pseudobrookite Fe 2 TiO 5 , has long been perplexing because the Fe 3+ moments (d 5 ) are expected to be isotropic. Recently, neutron diffraction demonstrated that surfboard-shaped antiferromagnetic nanoregions coalesce above the glass transition temperature T g ≈55K, and a model was proposed in which the freezing of the surfboard magnetization fluctuations leads to the anisotropic spin-glass state. Given this model, we have carried out high-resolution inelastic neutron scattering measurements of the spin-spin correlations to understand the temperature dependence of the intrasurfboard spin dynamics on neutron (picosecond) timescales. Here, in this paper, we report on the temperature-dependence of the spin fluctuations measured from single-crystal Fe 2 TiO 5 . Strong quasi-elastic magnetic scattering, arising from intrasurfboard correlations, is observed well above T g . The spin fluctuations possess a steep energy–wave vector relation and are indicative of strong exchange interactions, consistent with the large Curie-Weiss temperature. As the temperature approaches T g from above, a shift in spectral weight from inelastic to elastic scattering is observed. At various temperatures between 4 and 300 K, a characteristic relaxation rate of the fluctuations is determined. Despite the freezing of most of the spin correlations, an inelastic contribution remains even at base temperature, signifying the presence of fluctuating intrasurfboard spin correlations to at least T/T g ≈0.1 , consistent with an energy landscape that is a hybrid between conventional and geometrically frustrated spin glasses.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Measurement of the beam-normal single-spin asymmetry for elastic electron scattering from 12 C and 27 Al

We report measurements of the parity-conserving beam-normal single-spin elastic scattering asymmetries B n on 12 C and 27 Al, obtained with an electron beam polarized transverse to its momentum direction. These measurements add an additional kinematic point to a series of previous measurements of B n on 12 C and provide a first measurement on 27 Al. The experiment utilized the Q weak apparatus at Jefferson Lab with a beam energy of 1.158 GeV. The average lab scattering angle for both targets was 7.7°, and the average Q 2 for both targets was 0.02437 GeV 2 (Q = 0.1561 GeV). The asymmetries are B n = -10.68 ± 0.90 (stat) ± 0.57 (syst) ppm 12 C and B n = -12.16 ± 0.58 (stat) ± 0.62 (syst) ppm for 27 Al. The results are consistent with theoretical predictions, and are compared to existing data. When scaled by Z/A, the Q dependence of all the far-forward angle (θ < 10°) data from 1 H to 27 Al can be described by the same slope out to Q ≈ 0.35 GeV. Larger-angle data from other experiments in the same Q range are consistent with a slope about twice as steep.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Three-flavor collective neutrino conversions with multi-azimuthal-angle instability in an electron-capture supernova model

We investigate the multi-azimuthal angle (MAA) effect on collective neutrino oscillation by considering the three-dimensional neutrino momentum distribution in a realistic electron-capture supernova model with an 8.8 M ⊙ progenitor. We find that the MAA effect induces collective flavor conversions at epochs when it is completely suppressed under the axial-symmetric approximation. This novel activity is switched on/off by the growth of the MAA instability and imprints additional time evolution in the expected neutrino event rate. We validate our results by extending the linear stability analysis into the three-flavor scheme including mixing angles, and confirm that the onset of collective neutrino oscillation matches the steep growth of flavor instability. Furthermore, we discuss how the MAA effect alters neutrino detection at Super-Kamiokande and DUNE.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Mechanisms and models of the turbulent boundary layers at transcritical conditions

Computational models for high-pressure transcritical turbulence in wall-modeled large-eddy simulation typically rely on wall-function models to overcome the need for resolving the boundary layer structures. However, the mechanisms and models of turbulent boundary layer at transcritical conditions remain poorly understood since the near-wall flow and heat transfer are significantly affected by the enhanced fluctuations and steep gradients in thermodynamic properties. Here, to address this issue, we study the mechanisms of transcritical turbulent boundary layers and wall-attached models at transcritical conditions. It is shown that the real-fluid variable-property effects are associated with the coupling between the near-wall cycle and the wall-normal coherent motions in the outer layer, resulting in the amplification of turbulent energy in the outer layer and noticeable energy transfer between the log-layer and the outer layer; hence, turbulence in the log-layer is modulated by the outer layer. Based on this underlying physical principle, we propose the characteristic velocity and length scales for the attached eddy at transcritical conditions, and extend the attached eddy model to transcritical turbulent boundary layers by introducing a mixed scaling that incorporates both inner and outer scalings. We show that the new characteristic scales and extended attached-eddy model perform well in characterizing the structures in transcritical turbulent boundary layers.

Li, Fangbo↗

DOE OSTI2020

Anharmonicity and Phase Diagram of Magnesium Oxide in the Megabar Regime

With density functional molecular dynamics simulations, we computed the phase diagram of MgO from 50 to 2000 GPa up to 20000 K. Via thermodynamic integration (TDI), we derive the Gibbs free energies of the B1, B2, and liquid phases and determine their phase boundaries. With TDI and a pseudo-quasi-harmonic approach, we show that anharmonic effects are important and stabilize the B1 phase in particular. As a result, the B1-B2 transition boundary in the pressure-temperature plane exhibits a steep slope. We predict the B1-B2-liquid triple point to occur at approximately T= 10000 K and P = 370 GPa, which is higher in pressure than was inferred with quasi-harmonic methods alone. We predict the principal shock Hugoniot curve to enter the B2 phase stability domain but only over a very small range of parameters. Here, this may render it difficult to observe this phase with shock experiments because of kinetic effects.

3-dimensional systems↗

DOE OSTI2025

Thermodynamic Theory of Proximity Ferroelectricity

Proximity ferroelectricity has recently been reported as a new design paradigm for inducing ferroelectricity, where a nonferroelectric polar material becomes a ferroelectric one by interfacing with a thin ferroelectric layer. Strongly polar materials, such as AlN and ZnO, which were previously unswitchable with an external field below their dielectric breakdown fields, can now be switched with practical coercive fields when they are in intimate proximity to a switchable ferroelectric. Here, we develop a general Landau-Ginzburg theory of proximity ferroelectricity in multilayers of nonferroelectrics and ferroelectrics to analyze their switchability and coercive fields. The theory predicts regimes of both “proximity switching,” where the multilayers collectively switch, and “proximity suppression,” where they collectively do not switch. The mechanism of the proximity ferroelectricity is an internal electric field determined by the polarization of the layers and their relative thickness in a self-consistent manner that renormalizes the double-well ferroelectric potential to lower the steepness of the switching barrier. Further reduction in the coercive field emerges from charged defects in the bulk that act as nucleation centers. The application of the theory to proximity ferroelectricity in Al x−1⁢ Sc x ⁢N/AlN and Zn 1−x ⁢Mg x ⁢O/ZnO bilayers is demonstrated. The theory further predicts that dielectric-ferroelectric and paraelectric-ferroelectric multilayers can potentially lead to induced ferroelectricity in the dielectric or paraelectric layers, resulting in the entire stack being switched, an exciting avenue for new discoveries. This thawing of “frozen ferroelectrics,” paraelectrics, and potentially dielectrics with high dielectric constants promises a large class of new ferroelectrics with exciting prospects for previously unrealizable domain-patterned optoelectronic and memory technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Tip-based proximity ferroelectric switching and piezoelectric response in wurtzite multilayers

Proximity ferroelectricity is a paradigm for inducing ferroelectricity when a nonferroelectric polar material (such as Al⁢ N), which is unswitchable with an external field below the dielectric breakdown field, becomes a practically switchable ferroelectric in direct contact with a thin switchable ferroelectric layer (such as Al 1−𝑥 ⁢Sc 𝑥 ⁢N). Here, we develop a Landau-Ginzburg-Devonshire approach to study the proximity effect of local piezoelectric response and polarization reversal in wurtzite ferroelectric multilayers under a sharp electrically biased tip. Using finite-element modeling, we analyze the probe-induced nucleation of nanodomains, the features of local polarization hysteresis loops and coercive fields in the Al 1−𝑥 ⁢Sc 𝑥 ⁢N/Al⁢ N bilayers and three-layers. Similar to the wurtzite multilayers sandwiched between two parallel electrodes, the regimes of “proximity switching” (when all layers collectively switch) and the regime of “proximity suppression” (when they collectively do not switch) are the only two possible regimes in the probe-electrode geometry. However, the parameters and asymmetry of the local piezoresponse and polarization hysteresis loops depend significantly on the sequence of the layers with respect to the probe. The physical mechanism of proximity ferroelectricity in the local probe geometry is a depolarizing electric field determined by the polarization of the layers and their relative thickness. The field, whose direction is opposite to the polarization vector in the layer(s) with the larger spontaneous polarization (such as Al⁢ N), renormalizes the double-well ferroelectric potential to lower the steepness of the switching barrier in the “otherwise unswitchable” polar layers. Tip-based control of domains in otherwise nonferroelectric layers using proximity ferroelectricity can provide nanoscale control of domain reversal in memory, actuation, sensing, and optical applications. The ability of the tip-induced proximity switching to differentially switch multilayers, based on the order of the layers, provides a powerful tool for selective domain engineering.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Distilling Knowledge from Ensembles of Cluster-Constrained-Attention Multiple-Instance Learners for Whole Slide Image Classification

The peculiar nature of whole slide imaging (WSI), digitizing conventional glass slides to obtain multiple high resolution images which capture microscopic details of a patient’s histopathological features, has garnered increased interest from the computer vision research community over the last two decades. Given the unique computational space and time complexity inherent to gigapixel-size whole slide image data, researchers have proposed novel machine learning algorithms to aid in the performance of diagnostic tasks in clinical pathology. One effective algorithm represents a Whole slide image as a bag of smaller image patches, which can be represented as low-dimension image patch embeddings. Weakly supervised deep-learning methods, such as cluster-constrained-attention multiple instance learning (CLAM), have shown promising results when combined with image patch embeddings. While traditional ensemble classifiers yield improved task performance, such methods come with a steep cost in model complexity. Through knowledge distillation, it is possible to retain some performance improvements from an ensemble, while minimizing costs to model complexity. In this work, we implement a weakly supervised ensemble using clustering-constrained-attention multiple-instance learners (CLAM), which uses attention and instance-level clustering to identify task salient regions and feature extraction in whole slides. By applying logit-based and attention-based knowledge distillation, we show it is possible to retain some performance improvements resulting from the ensemble at zero cost to model complexity.

Alamudun, Folami↗

DOE OSTI2024

Long-Range Biometric Identification in Real World Scenarios: A Comprehensive Evaluation Framework Based on Missions

The considerable body of data available for evaluating biometric recognition systems in Research and Development (R&D) environments has contributed to the increasingly common problem of target performance mismatch. Biometric algorithms are frequently tested against data that may not reflect the real world applications they target. From a Testing and Evaluation (T&E) standpoint, this domain mismatch causes difficulty assessing when improvements in State-of-the-Art (SOTA) research actually translate to improved applied outcomes. This problem can be addressed with thoughtful preparation of data and experimental methods to reflect specific use-cases and scenarios.To that end, this paper evaluates research solutions for identifying individuals at ranges and altitudes, which could support various application areas such as counterterrorism, protection of critical infrastructure facilities, military force protection, and border security. We address challenges including image quality issues and reliance on face recognition as the sole biometric modality. By fusing face and body features, we propose developing robust biometric systems for effective long-range identification from both the ground and steep pitch angles. Preliminary results show promising progress in whole-body recognition. This paper presents these early findings and discusses potential future directions for advancing long-range biometric identification systems based on mission-driven metrics.

Aykac, Deniz↗

DOE OSTI2020

Tunnel-FET Switching Is Governed by Non-Lorentzian Spectral Line Shape

In tunnel field-effect transistors (tFETs), the preferred mechanism for switching occurs by alignment (on) or misalignment (off) of two energy levels or band edges. Unfortunately, energy levels are never perfectly sharp. When a quantum dot interacts with a wire, its energy is broadened. Its actual spectral shape controls the current/voltage response of such transistor switches, from on (aligned) to off (misaligned). The most common model of spectral line shape is the Lorentzian, which falls off as reciprocal energy offset squared. Unfortunately, this is too slow a turnoff, algebraically, to be useful as a transistor switch. Electronic switches generally demand an on/off ratio of at least a million. Steep exponentially falling spectral tails would be needed for rapid off-state switching. This requires a new electronic feature, not previously recognized: narrowband, heavy-effective mass, quantum wire electrical contacts, to the tunneling quantum states. These are a necessity for spectrally sharp switching.

42 ENGINEERING↗

DOE OSTI2025

Deep Reinforcement Learning for Distribution System Operations: A Tutorial and Survey

Here, the rapid evolution of modern electric power distribution systems into complex networks of interconnected active devices, distributed generation (DG), and storage poses increasing difficulties for system operators. The large-scale integration of distributed energy resources (DERs) and the rapid exchange of measurement data via communication networks present major opportunities for advancing grid operations but also introduce greater uncertainty, higher data dimensionality, more complex network and device models, and challenging control and optimization problems. Deep reinforcement learning (DRL) algorithms are promising in addressing these challenges. However, they have not been effectively adapted for power systems applications, requiring extensive customization for implementation and evaluation. This has resulted in reproducibility challenges and a steep learning curve for researchers new to applying DRL algorithms to the power systems domain. To bridge these gaps, this tutorial aims to serve as a valuable resource for researchers interested in exploring learning-based algorithms to operate active power distribution networks. Specifically, this work presents a generalized process for translating sequential decision-making problems in power distribution systems into Markov decision process (MDP) formulations, illustrated through concrete grid service examples. Additionally, we introduce a simple environment design strategy to develop and evaluate example DRL algorithms for distribution system applications, complete with an included code repository to guide users through environment construction.

24 POWER TRANSMISSION AND DISTRIBUTION↗