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At least 253 records · Page 14

Hydrogenation of calcite and change in chemical bonding at high pressure: Diamond formation above 100GPa

Synchrotron X-ray diffraction (XRD) and Raman spectroscopy in laser heated diamond anvil cells and first principles molecular dynamics (FPMD) calculations have been used to investigate the reactivity of calcite and molecular hydrogen (H 2 ) at high pressures up to 120 GPa. We find that hydrogen reacts with calcite starting below 0.5 GPa at room temperature forming chemical bonds with carbon and oxygen. This results in the unit cell volume expansion; the hydrogenation level is much higher for powdered samples. Single-crystal XRD measurements at 8–24 GPa reveal the presence of previously reported III, IIIb, and VI calcite phases; some crystallites show up to 4% expansion, which is consistent with the incorporation of ≤ 1 hydrogen atom per formula unit. At 40–102 GPa XRD patterns of hydrogenated calcite demonstrate broadened features consistent with the calcite VI structure with incorporated hydrogen atoms. Above 80 GPa, the C–O stretching mode of calcite splits suggesting a change in the coordination of C–O bonds. Laser heating at 110 GPa results in the formation of C–C bonds manifested in the crystallization of diamond recorded by in situ XRD at 300 K and 110 GPa and by Raman spectroscopy on recovered samples commenced with C 13 calcite. We explored several theoretical models, which show that incorporation of atomic hydrogen results in local distortions of CO 3 groups, formation of corner-shared C–O polyhedra, and chemical bonding of H to C and O, which leads to the lattice expansion and vibrational features consistent with the experiments. In conclusion, the experimental and theoretical results support recent reports on tetrahedral C coordination in high-pressure carbonate glasses and suggest a possible source of the origin of ultradeep diamonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identification of Auger mechanisms responsible for low energy electron emission from graphene on copper using Auger-gamma coincidence spectroscopy

We have applied positron annihilation induced Auger-gamma coincidence spectroscopy to identify important mechanisms responsible for the emission of low energy electrons following the sudden creation of holes in bilayer graphene on copper substrate. The novel surface spectroscopic method measures the energy of the Doppler shifted annihilation gamma photon in coincidence with the Auger electron emitted following the relaxation of the hole created by the annihilation of a surface electron with a surface trapped positron. By extracting and theoretically modelling the annihilation gamma spectra coincident with low energy electrons, we associate majority of the intensity in the low energy (7 eV–25 eV) region of the Auger spectrum to electron emission following Auger decays of 2s holes in adsorbed oxygen and deep valence holes in graphene. We provide additional support to this conclusion by showing that most of the Auger electrons with energy less than ~ 25 eV are coincident with gamma photons with small Doppler shift (511 keV–512 keV) indicating that the primary electron whose annihilation resulted in low energy Auger electron emission had small momentum parallel to the gamma emission direction. On the other hand, majority of the Auger electrons measured in coincidence with the photons having maximum Doppler shift (515 keV–521 keV) were emitted following the decay of core holes (C 1s and O 1s). Furthermore, by selecting annihilation gamma photons coincident only with the O KVV (from surface adsorbed oxygen), C KVV (graphene), and Cu MVV (copper substrate) Auger electrons, we have also experimentally derived the energy spectrum of Doppler shifted gamma photons resulting from the annihilation of positrons with 1s electrons of O, 1s electrons of C and 3p electrons of Cu respectively. Model Doppler broadened gamma spectra produced using ab-initio calculations agree well with the experimentally derived line shapes. This demonstrates the ability of Auger-gamma coincidence method to experimentally resolve the Doppler broadened annihilation gamma spectrum from surfaces into its veiled electronic level constituents which has, heretofore, relied solely on theoretical analysis. Our results also demonstrate that the line shape of the Doppler broadened annihilation gamma peak reflect the chemical composition of the topmost atomic layer and can thus be used to characterize both external and inaccessible surfaces of porous materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Revisiting Bayesian constraints on the transport coefficients of QCD

Multistage models based on relativistic viscous hydrodynamics have proven successful in describing hadron measurements from relativistic nuclear collisions. These measurements are sensitive to the shear and the bulk viscosities of QCD and provide a unique opportunity to constrain these transport coefficients. Bayesian analyses can be used to obtain systematic constraints on the viscosities of QCD, through methodical model-to-data comparisons. In this manuscript, we discuss recent developments in Bayesian analyses of heavy ion collision data. Furthermore, we highlight the essential role of closure tests in validating a Bayesian analysis before comparison with measurements. We discuss the role of the emulator that is used as proxy for the multistage theoretical model. We use an ongoing Bayesian analysis of soft hadron measurements by the JETSCAPE Collaboration as context for the discussion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Dynamic modeling for heavy-ion collisions

Recent theory progress in (3+1)D dynamical descriptions of relativistic nuclear collisions at finite baryon density are reviewed. Heavy-ion collisions at different collision energies produce strongly coupled nuclear matter to probe the phase structure of Quantum Chromodynamics (QCD). Dynamical frameworks serve as a quantitative tool to study properties of hot QCD matter and map collisions to the QCD phase diagram. Outstanding challenges are highlighted when confronting theoretical models with the current and forthcoming experimental measurements from the RHIC beam energy scan program.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Optimization of the BDX experiment for Light Dark Matter searches at JLab

The Light Dark Matter (LDM) hypothesis postulates the existence of a new class of sub GeV particles, neutral under Standard Model (SM) interactions. In its simplest form, LDM consists of particles ¿ with masses below 1 GeV/c2, interacting with SM particles via a new force mediated by a light, spin-1 boson A0, commonly referred to as “Dark Photon”. This framework envisions a distinct “Dark Sector” with its own particles and interactions, offering a theoretically well motivated explanation for Dark Matter, consistent with astrophysical observations and a thermal production mechanism. The Beam Dump eXperiment (BDX) is an approved experiment at Jefferson Lab designed to search for Light Dark Matter. BDX will utilize an 11 GeV electron beam impinging on a thick target to produce a forward-boosted secondary beam of Light Dark Matter particles, which will then be detected by a dedicated downstream detector. Approved in 2018, BDX is expected to be commissioned in 2026 and run in 2027-2029. My thesis focuses on the preparatory work to deploy the BDX experiment. The detector design has been optimized to balance practicality with enhanced Light Dark Matter detection capabilities. Extensive characterization of detector components has been performed to ensure a precise understanding of detector response. A custom Monte Carlo framework has been developed to simulate Light Dark Matter signal and explore various theoretical models of interest. Additionally, a comprehensive data analysis framework has been developed to maximize the experiment sensitivity to Light Dark Matter, with optimizations based on expected detector performance. The ultimate goal of this thesis is to optimize BDX as a flagship experiment in Light Dark Matter searches, enabling it to probe different Dark Matter models.

Spreafico, M. [Univ. of Genova (Italy)]↗

Nuclear Data for Spallation Neutron Radioisotope Production (Final Technical Report)

Over 50 million nuclear medicine procedures are performed annually, leading to a multi-billion dollar market for radioisotope production. The demand for new medical and research isotopes is growing, and radioisotope supply is insufficient. Most radioisotope production today utilizes charged particle or low-energy neutron irradiation of a target. Isotope production with tens to hundred MeV incident energies is a relatively unexplored option. There is a tremendous opportunity associated with a growing number of suitable domestic and international facilities buttressed by hundred million dollar global investments (e.g., the Los Alamos and Brookhaven Isotope Production Facilities, the European Spallation Source in Lund, and the Korean Multi-purpose Accelerator Complex in Gyeongbuk). In part due to a lack of supporting nuclear data that would make modeling radioisotope yields and purities possible, these facilities do not utilize their high-energy neutron fluxes for isotope production. This project attempted to measure neutron reaction excitation functions relevant to the large-scale production of critical radioisotopes, enabling development of cost-efficient isotope production methods, contributing to the improvement of theoretical models, and enhancing the value of national isotope production facilities. Reactions which form 67 Cu, 32 Si, and alpha-emitting isotopes like 225 Ac were chosen for their consistent prioritization by expert panels, representation of diverse reaction mechanisms, and relative lack of supporting nuclear data. Accurate measurement of these data is presently made only using quasi-monoenergetic neutron beams, which are produced by bombarding thin lithium targets with protons at only a few laboratories in the world. Ultimately, the projects efforts were incompletely accomplished due to a combination of multi-year technical issues at the only laboratory in the world which can make the proposed measurements, iThemba Labs in South Africa, and the onset of a global pandemic, which precluded the significant effort and time required to develop an independent measurement capability in the United States.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

2020 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is essential for addressing the increasingly complex national workforce demands stemming from the growth of computational science and engineering challenges. Computational science and engineering (CSE) takes a multidisciplinary approach that utilizes scientific computing to tackle practical problems and provide technical tools across the spectrum of scientific discovery. The DOE CSGF specifically highlights high-performance computing (HPC) as a critical enabling technology in CSE, driving advancements in science and engineering that are vital to both the DOE and the broader economy. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines have been transformed through the augmentation of scientific observation via HPC. At government laboratories, academic institutions, and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, quantum information systems, fusion-reactor design, machine learning, additive manufacturing, nano materials for next-generation batteries and transistors, and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing. Computational biology, machine learning, and quantum computing are among the subjects that began to swell in the ranks of CSGF applicants before the labs were hiring as high a percentage of employees in these categories.” The explosion of scientific and technological data has heightened the demand for advanced high-performance computing (HPC) to transform these data into meaningful scientific insights. As access to vast amounts of data increases, the fields of Machine Learning and Artificial Intelligence are experiencing a resurgence, enhancing the established practices of computational modeling and simulation. In its September 2020 subcommittee report on "AI/ML, Data Intensive Science, and High-Performance Computing," the DOE Advanced Scientific Computing Advisory Committee (ASCAC) specifically called for a fellowship program to train computational and data scientists to address exascale and data-intensive computing challenges. This integration of empirical and theoretical modeling will increasingly guide federal policymakers in making decisions that impact American society and future generations. It demands a workforce of highly skilled and intellectually agile computational scientists capable of navigating the rapid advancements in scientific computing within the DOE National Laboratory research environment. The DOE CSGF program has consistently addressed this critical need.

97 MATHEMATICS AND COMPUTING↗

Detection of Aerosols at Microbar Pressures in an Exoplanet Atmosphere

The formation of hazes at microbar pressures has been explored by theoretical models of exoplanet atmospheres to explain Rayleigh scattering and/or featureless transmission spectra; however observational evidence of aerosols in the low-pressure formation environments has proved elusive. Here, we show direct evidence of aerosols existing at ~1 microbar pressures in the atmosphere of the warm sub-Saturn WASP-69b using observations taken with the Space Telescope Imaging Spectrograph and Wide Field Camera 3 instruments on the Hubble Space Telescope. The transmission spectrum shows a wavelength-dependent slope induced by aerosol scattering that covers 11 scale heights of spectral modulation. Drawing on the extensive studies of haze in our solar system, we model the transmission spectrum based on a scaled version of Jupiter’s haze-density profile to show that the WASP-69b transmission spectrum can be produced by scattering from an approximately constant density of particles extending throughout the atmospheric column from 40 millibar to microbar pressures. These results are consistent with theoretical expectations based on microphysics of the aerosol particles that have suggested haze can exist at microbar pressures in exoplanet atmospheres.

47 OTHER INSTRUMENTATION↗

Ectomycorrhizal effects on decomposition are highly dependent on fungal traits, climate, and litter properties: A model-based assessment

It has been proposed that competition between ectomycorrhizal (ECM) fungi and free-living saprotrophs for resources like nitrogen (N) slows decomposition and increases the soil carbon storage in ECM ecosystems compared to arbuscular (AM) ecosystems. However, empirical evidence for the generality of such ECM effects is equivocal, and confounding mechanisms have been proposed that affect the magnitude and direction of ECM effects on soil carbon. Here, for this work, we conduct a theoretical modeling experiment, where we explicitly incorporate mycorrhizal processes into the Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment (CORPSE) model. We use the model to explore the conditions under which ECM N acquisition processes can induce stronger saprotrophic N limitation and result in slower decomposition rates and greater soil organic carbon accumulation compared to AM processes. We found that the ECM fungi more strongly inhibited decomposition when litter inputs were N-depleted and relatively recalcitrant and when ECM fungi possessed a strong capacity to mine N from both recalcitrant soil organic matter and microbial necromass. Climate and seasonality also played a role as the ECM competition effect was strongest at low mean annual temperatures and when litterfall peaked seasonally. Priming effects driven by high root exudation rates in ECM-dominated systems could overwhelm the competition effect and reduce soil carbon under some circumstances. The ECM effect on decomposition in our simulations was highly context dependent. Based on our model results, we expect to see a strong ECM competition effect in temperate deciduous and boreal forests with relatively recalcitrant litter inputs, and with ECM fungi that produce oxidases and necromass-degrading enzymes. However, even a relatively strong ECM competition effect on decomposition only increased soil organic carbon accumulation by ~10%.

59 BASIC BIOLOGICAL SCIENCES↗

In situ recording of Mars soundscape

Abstract Before the Perseverance rover landing, the acoustic environment of Mars was unknown. Models predicted that: (1) atmospheric turbulence changes at centimetre scales or smaller at the point where molecular viscosity converts kinetic energy into heat 1 , (2) the speed of sound varies at the surface with frequency 2,3 and (3) high-frequency waves are strongly attenuated with distance in CO 2 (refs. 2–4 ). However, theoretical models were uncertain because of a lack of experimental data at low pressure and the difficulty to characterize turbulence or attenuation in a closed environment. Here, using Perseverance microphone recordings, we present the first characterization of the acoustic environment on Mars and pressure fluctuations in the audible range and beyond, from 20 Hz to 50 kHz. We find that atmospheric sounds extend measurements of pressure variations down to 1,000 times smaller scales than ever observed before, showing a dissipative regime extending over five orders of magnitude in energy. Using point sources of sound (Ingenuity rotorcraft, laser-induced sparks), we highlight two distinct values for the speed of sound that are about 10 m s −1 apart below and above 240 Hz, a unique characteristic of low-pressure CO 2 -dominated atmosphere. We also provide the acoustic attenuation with distance above 2 kHz, allowing us to explain the large contribution of the CO 2 vibrational relaxation in the audible range. These results establish a ground truth for the modelling of acoustic processes, which is critical for studies in atmospheres such as those of Mars and Venus.

79 ASTRONOMY AND ASTROPHYSICS↗

Development of Approaches to Model Excited State Charge and Energy Transfer in Solution

The development of next generation energy conversion and catalytic systems requires fundamental understanding of the interplay between photo-excitation and the resulting proton and electron transfer processes that occur in solution. To address these challenges requires accurate and efficient methods to compute ground and excited states, as well as the ability to treat the dynamics of energy transfer in the presence of solvent fluctuations. Our team is developing accurate and efficient theoretical models for solution phase reactions. These developments provide an improved understanding of photo-initiated excitations, electron transfer, and proton coupled electron transfer processes. Our research team brings together expertise in electron and nuclear dynamics (classical and quantum), electronic structure, and analysis of solvation networks. We are developing and validating techniques for modeling condensed phase charge and energy transfer and to simulate the methods to monitor them using optical and vibrational spectroscopy.

74 ATOMIC AND MOLECULAR PHYSICS↗

Estimates of the wavenumber wavelet power spectrum of magnetic fluctuations during magnetic reconnection

Fluctuation analyses of experimental observations generally lack high temporal resolution and are in frequency-space f, contrary to theoretical efforts in wavenumber-space k. This is due to the inherent limits of the Fourier transform, though it is prominent due to the ease of diagnostic implementation. Advances in wavelet-based analysis have provided relief due to its temporal resolution, but in its common use, is still hard to compare to theoretical models. By using the two-point correlation technique in conjunction with large data sets, a wavelet power spectrum in wavenumber-space can be created. Dubbed the wavenumber wavelet power spectrum, this spectrum relates wavenumber to power in time. Further, this analysis technique more closely connects characterizations of experimentally observed fluctuations with other system parameters and theoretical predictions. In this article, we develop the wavenumber wavelet power spectrum using magnetic fluctuations caused by tearing instability driven magnetic reconnection in reproducible, high temperature laboratory plasmas. These dynamic magnetic fluctuations generated in reversed field pinch plasmas are broadband, ranging from the low frequency, 10's of kHz, up to the ion gyroradii frequencies, 100's of kHz. The dominant fluctuations have poloidal and toroidal mode numbers (m,n)=(1,6−10) and can grow to 2%–3% of the mean magnetic field. During these reconnection events, ions, and electrons are energized, magnetic fluctuation amplitudes increase, plasma flow is halted, and the toroidal magnetic flux increases, all on a semi-periodic basis. The newly developed spectrum provides better temporal resolution of spectrum characteristics to correlate with these particle energization phenomena.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Bayesian Monte Carlo Evaluation Framework for Imperfect Data and Models [Abstract]

Nuclear data evaluation methods conventionally make the following assumptions: prior and posterior probability distribution functions (PDFs) of all model parameters and data are normal (Gaussian); the linear approximation is sufficiently accurate for minimization of a cost function (even for non-linear models); and that both the model (of, e.g., neutron cross section) and experimental data (including their covariance data) are perfect. These assumptions are inherent to the well-known generalized linear least squares (GLLS) minimization method commonly used for evaluations of resolved resonance region (RRR) neutron cross sections. However, these assumptions are often not justified due to the presence of non-normal PDFs, non-linear models (e.g. R -matrix formalism), and inherent imperfections in data and models (e.g. discrepant data sets, discrepancies between the previous evaluation and newly measured data, or imperfect covariance data). We remove the said assumptions in a mathematical framework of Bayes’ theorem, and implement it using the Metropolis-Hastings Monte Carlo method. Parameters of a new kind are introduced to parameterize inherent imperfections, e.g. , any discrepancies between the theoretical model and measured data. These new parameters enable evaluators to quantify their expert judgement about any discrepancies or imperfections in a reproducible manner. We demonstrate the framework with an ongoing evaluation of 233 U in the eV region using the ENDF-B/VIII library and transmission data measured by Guber, et al. , and compare the posterior parameters to those obtained by conventional evaluation methods.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

New vortex‐lift and tangential‐force models for HAWT aerodynamic load prediction

Abstract Horizontal axis wind turbines (HAWTs) experience three‐dimensional rotational and unsteady aerodynamic phenomena at the rotor blades sections. These highly unsteady three‐dimensional effects have a dramatic impact on the aerodynamic load distributions on the blades, in particular, when they occur at high angles of attack due to stall delay and dynamic stall. Unfortunately, there is no complete understanding of the flow physics yet at these unsteady 3D flow conditions, and hence, the existing published theoretical models are often incapable of modelling the impact on the turbine response realistically. The purpose of this paper is to provide an insight on the combined influence of the stall delay and dynamic stall on the blade load history of wind turbines in controlled and uncontrolled conditions. New dynamic stall vortex and nonlinear tangential force coefficient modules, which integrally take into account the three dimensional rotational effect, are also proposed in this paper. This module along with the unsteady influence of turbulent wind speed and tower shadow is implemented in a blade element momentum (BEM) model to estimate the aerodynamic loads on a rotating blade more accurately. This work presents an important step to help modelling the combined influence of the stall delay and dynamic stall on the load history of the rotating wind turbine blades which is vital to have lighter turbine blades and improved wind turbine design systems.

Elgammi, Moutaz↗

Stream and ocean hydrodynamics mediate partial migration strategies in an amphidromous Hawaiian goby

Abstract Partial migration strategies, in which some individuals migrate but others do not, are widely observed in populations of migratory animals. Such patterns could arise via variation in migratory behaviors made by individual animals, via genetic variation in migratory predisposition, or simply by variation in migration opportunities mediated by environmental conditions. Here we use spatiotemporal variation in partial migration across populations of an amphidromous Hawaiian goby to test whether stream or ocean conditions favor completing its life cycle entirely within freshwater streams rather than undergoing an oceanic larval migration. Across 35 watersheds, microchemical analysis of otoliths revealed that most adult Awaous stamineus were freshwater residents (62% of n = 316 in 2009, 83% of n = 274 in 2011), but we found considerable variation among watersheds. We then tested the hypothesis that the prevalence of freshwater residency increases with the stability of stream flows and decreases with the availability of dispersal pathways arising from ocean hydrodynamics. We found that streams with low variation of daily discharge were home to a higher incidence of freshwater residents in each survey year. The magnitude of the shift in freshwater residency between survey years was positively associated with predicted interannual variability in the success of larval settlement in streams on each island based on passive drift in ocean currents. We built on these findings by developing a theoretical model of goby life history to further evaluate whether mediation of migration outcomes by stream and ocean hydrodynamics could be sufficient to explain the range of partial migration frequency observed across populations. The model illustrates that the proportion of larvae entering the ocean and differential survival of freshwater‐resident versus ocean‐going larvae are plausible mechanisms for range‐wide shifts in migration strategies. Thus, we propose that hydrologic variation in both ocean and stream environments contributes to spatiotemporal variation in the prevalence of migration phenotypes in A. stamineus . Our empirical and theoretical results suggest that the capacity for partial migration could enhance the persistence of metapopulations of diadromous fish when confronted with variable ocean and stream conditions.

54 ENVIRONMENTAL SCIENCES↗

Generalized framework for likelihood-based field-level inference of growth rate from velocity and density fields

Measuring the growth rate of large-scale structures ( f ) as a function of redshift has the potential to break degeneracies between modified gravity and dark energy models, when combined with expansion-rate probes. Direct estimates of peculiar velocities of galaxies have attracted interest as a means of estimating fσ 8 . In particular, field-level methods can be used to fit the field nuisance parameter along with cosmological parameters simultaneously. This article aims to provide the community with a unified framework for the theoretical modeling of the likelihood-based field-level inference by performing fast field covariance calculations for velocity and density fields. Our purpose is to lay the foundations for a nonlinear extension of the likelihood-based method at the field level. We have developed a generalized framework, implemented in the dedicated software flip to perform a likelihood-based inference of fσ 8 . We derived a new field covariance model, which includes wide-angle corrections. We also included the models previously described in the literature inside our framework. We compared their performance against ours, and we validated our model by comparing it with the two-point statistics of a recent N-body simulation. The tests we performed have allowed us to validate our software and determine the appropriate wavenumber range to integrate our covariance model and its validity in terms of separation. Our framework allows for a wider wavenumber coverage to be used in our calculations than in previous works, which is particularly interesting for nonlinear model extensions. Finally, our generalized framework allows us to efficiently perform a survey geometry-dependent Fisher forecast of the fσ 8 parameter. We show that the Fisher forecast method we developed gives an error bar that is 30% closer to a full likelihood-based estimation than a standard volume Fisher forecast.

Ravoux, Corentin↗

Discovery and characterization of five new eclipsing AM CVn systems

ABSTRACT AM CVn systems are ultra-compact, hydrogen-depleted, and helium-rich, accreting binaries with degenerate or semidegenerate donors. We report the discovery of five new eclipsing AM CVn systems with orbital periods of 61.5, 55.5, 53.3, 37.4, and 35.4 min. These systems were discovered by searching for deep eclipses in the Zwicky Transient Facility (ZTF) light curves of white dwarfs selected using Gaia parallaxes. We obtained phase-resolved spectroscopy to confirm that all systems are AM CVn binaries, and we obtained high-speed photometry to confirm the eclipse and characterize the systems. The spectra show double-peaked H e lines but also show metals, including K and Zn, elements that have never been detected in AM CVn systems before. By modelling the high-speed photometry, we measured the mass and radius of the donor star, potentially constraining the evolutionary channel that formed these AM CVn systems. We determined that the average mass of the accreting white dwarf is ≈0.8 M⊙, and that the white dwarfs in long-period systems are hotter than predicted by recently updated theoretical models. The donors have a high entropy and are a factor of ≈2 more massive compared to zero-entropy donors at the same orbital period. The large donor radius is most consistent with H e-star progenitors, although the observed spectral features seem to contradict this. The discovery of five new eclipsing AM CVn systems is consistent with the known observed AM CVn space density and estimated ZTF recovery efficiency.

79 ASTRONOMY AND ASTROPHYSICS↗

Scalable Unit Commitment with Security Constrained AC Power Flow via ADMM and Hybrid Modeling Strategies

This research introduces a more efficient way to optimize power grid operations, breaking the problem into manageable steps and using advanced mathematical techniques to speed up calculations. By incorporating smart heuristics, improved preprocessing, and contingency analysis, the approach allows operators to make better decisions faster. These innovations enhance our understanding of how to optimize energy generation, making it possible to anticipate failures before they happen, reduce system costs, and improve overall grid performance. Ultimately, this research helps bridge the gap between theoretical models and real-world applications, paving the way for a smarter, more resilient power grid. This research directly benefits the public by making electricity more affordable, reliable, and sustainable. By improving how power grids schedule and distribute electricity, the project helps energy providers reduce operational costs, which can lead to lower electricity prices for consumers. Additionally, the ability to predict and prevent power system failures enhances grid reliability, reducing the likelihood of blackouts that can disrupt homes, businesses, and critical infrastructure such as hospitals. From an environmental perspective, optimizing power generation reduces energy waste and lowers carbon emissions, contributing to cleaner air and a more sustainable energy system. Furthermore, with extreme weather events becoming more frequent, these advancements make the power grid more resilient, ensuring communities are better prepared for emergencies and natural disasters. By strengthening the nation's energy infrastructure, this research plays a crucial role in improving economic stability, public safety, and environmental sustainability.

24 POWER TRANSMISSION AND DISTRIBUTION↗