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DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Validation of 266 nm UV Raman thermometry using the alpha-to-beta quartz transition

Ultraviolet Raman scattering is a promising diagnostic for temperature measurements relevant to dynamic compression experiments, where improved signal strength and reduced background are critical. In this work, we experimentally validate Raman thermometry at 266 nm using crystalline quartz heated through the α to β phase transition in a tube furnace. Quartz provides a useful benchmark because of its well-characterized transition temperature near 846 K at ambient pressure. Temperatures inferred from the Stokes to anti-Stokes intensity ratio are compared with thermocouple measurements and with the observed phase transition. Single-shot Raman temperatures track the thermocouple closely, with an empirical single-shot scatter of approximately ±15 K under the present conditions. Temporal averaging reduces shot-to-shot scatter and improves agreement between the Raman temperatures and thermocouple readings to within approximately 8 K, while the transition is identified within 5 K of the accepted value. Measurements are performed using the fourth harmonic of a nanosecond pulsed Nd:YAG laser at 266 nm. The shorter excitation wavelength provides enhanced Raman scattering efficiency and reduced visible background relative to conventional visible excitation. Comparison with 532 nm Raman measurements acquired in the same experimental geometry demonstrates substantially improved signal-to-noise ratio for the UV configuration. These results establish 266 nm Raman thermometry as a reliable and accurate temperature diagnostic under controlled heating conditions and provide a quantitative benchmark for future application in dynamic compression and shock physics experiments.

Chemistry - Chemical explosives↗
DOE OSTI2024

Direct Visualization of Defect‐Controlled Diffusion in van der Waals Gaps

Abstract Diffusion processes govern fundamental phenomena such as phase transformations, doping, and intercalation in van der Waals (vdW) bonded materials. Here, the diffusion dynamics of W atoms by visualizing the motion of individual atoms at three different vdW interfaces: hexagonal boron nitride (BN)/vacuum, BN/BN, and BN/WSe 2 , by recording scanning transmission electron microscopy movies is quantified. Supported by density functional theory (DFT) calculations, it is inferred that in all cases diffusion is governed by intermittent trapping at electron beam‐generated defect sites. This leads to diffusion properties that depend strongly on the number of defects. These results suggest that diffusion and intercalation processes in vdW materials are highly tunable and sensitive to crystal quality. The demonstration of imaging, with high spatial and temporal resolution, of layers and individual atoms inside vdW heterostructures offers possibilities for direct visualization of diffusion and atomic interactions, as well as for experiments exploring atomic structures, their in situ modification, and electrical property measurements of active devices combined with atomic resolution imaging.

Chemistry↗
DOE OSTI2026

Leaf Wax Hydrogen Isotopes Reflect Storm Track Position Over Western North America

Proxy records of past climates have yielded powerful insights into regional hydroclimate dynamics. Novel insights may be gained by reconstructing spatiotemporal changes in precipitation isotopologues in past climate states that cannot be gleaned from individual site‐level studies. In this paper, we ask whether latitudinal gradients in the stable hydrogen isotopic composition of precipitation, as inferred from sedimentary leaf wax biomarkers, reflect aspects of large‐scale climate conditions in western North America (WNA). Modern coretop samples from offshore WNA show that leaf wax hydrogen isotopes broadly track the hydrogen isotopic composition of rainfall between 20 and 40N, but with an offset corresponding to a relatively constant “apparent fractionation” value. Poleward of 40N, the leaf wax signal may be complicated by fluvial transport of leaf waxes from the continental interior. Leaf wax‐inferred precipitation hydrogen isotopes show a shift to more negative values between 30 and 40N. We use modern observational data to show that this latitudinal range marks a major transition between the subtropical arid zone and the location of the midlatitude storm tracks over the northeast Pacific. Nudged water isotope‐enabled models capture the location of the arid to mesic climate transition with fidelity. This modern data set suggests that reconstructions of the latitudinal gradient of precipitation hydrogen isotopes can constrain the sensitivity of the storm tracks to shifts in climatic boundary conditions in past climate states. This approach can yield novel insights into past, present, and future hydroclimate variability in this arid region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The cosmic waltz of Coma Berenices and Latyshev 2 (Group X)

Context. Open clusters (OCs) are fundamental benchmarks where theories of star formation and stellar evolution can be tested and validated. Coma Berenices (Coma Ber) and Latyshev 2 (Group X) are the second and third OCs closest to the Sun, making them excellent targets to search for low-mass stars and ultra-cool dwarfs. In addition, this pair will experience a flyby in 10–16 Myr, making it a benchmark to test pair interactions of OCs. Aims. We aim to analyse the membership, luminosity, mass, phase-space (i.e. positions and velocities), and energy distributions for Coma Ber and Latyshev 2 and test the hypothesis of the mixing of their populations at the encounter time. Methods. We developed a new phase-space membership methodology and applied it to Gaia data. With the recovered members, we inferred the phase-space, luminosity, and mass distributions using publicly available Bayesian inference codes. Then, with a publicly available orbit integration code and members’ positions and velocities, we integrated their orbits 20 Myr into the future. Results. In Coma Ber, we identified 302 candidate members distributed in the core and tidal tails. The tails are dynamically cold and asymmetrically populated. The stellar system called Group X is made of two structures: the disrupted OC Latyshev 2 (186 candidate members) and a loose stellar association called Mecayotl 1 (146 candidate members), and both of them will fly by Coma Ber in 11.3 ± 0.5 Myr and 14.0 ± 0.6 Myr, respectively, and each other in 8.1 ± 1.3 Myr. Conclusions. We study the dynamical properties of the core and tails of Coma Ber and also confirm the existence of the OC Latyshev 2 and its neighbour stellar association Mecayotl 1. Although these three systems will experience encounters, we find no evidence supporting the mixing of their populations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The Cosmic Ultraviolet Baryon Survey (CUBS) – III. Physical properties and elemental abundances of Lyman-limit systems at z < 1

ABSTRACT We present a systematic investigation of physical conditions and elemental abundances in four optically thick Lyman-limit systems (LLSs) at z = 0.36–0.6 discovered within the Cosmic Ultraviolet Baryon Survey (CUBS). Because intervening LLSs at z < 1 suppress far-UV (ultraviolet) light from background QSOs, an unbiased search of these absorbers requires a near-UV-selected QSO sample, as achieved by CUBS. CUBS LLSs exhibit multicomponent kinematic structure and a complex mix of multiphase gas, with associated metal transitions from multiple ionization states such as C ii, C iii, N iii, Mg ii, Si ii, Si iii, O ii, O iii, O vi, and Fe ii absorption that span several hundred km s−1 in line-of-sight velocity. Specifically, higher column density components (log N(H i)/cm−2≳ 16) in all four absorbers comprise dynamically cool gas with $\langle T \rangle =(2\pm 1) \times 10^4\,$K and modest non-thermal broadening of $\langle b_\mathrm{nt} \rangle =5\pm 3\,$km s−1. The high quality of the QSO absorption spectra allows us to infer the physical conditions of the gas, using a detailed ionization modelling that takes into account the resolved component structures of H i and metal transitions. The range of inferred gas densities indicates that these absorbers consist of spatially compact clouds with a median line-of-sight thickness of $160^{+140}_{-50}$ pc. While obtaining robust metallicity constraints for the low density, highly ionized phase remains challenging due to the uncertain $N\mathrm{(H\, {\small I})}$, we demonstrate that the cool-phase gas in LLSs has a median metallicity of $\mathrm{[\alpha /H]_{1/2}}=-0.7^{+0.1}_{-0.2}$, with a 16–84 percentile range of [α/H] = (−1.3, −0.1). Furthermore, the wide range of inferred elemental abundance ratios ([C/α], [N/α], and [Fe/α]) indicate a diversity of chemical enrichment histories. Combining the absorption data with deep galaxy survey data characterizing the galaxy environment of these absorbers, we discuss the physical connection between star-forming regions in galaxies and diffuse gas associated with optically thick absorption systems in the z < 1 circumgalactic medium.

Zahedy, Fakhri S. (ORCID:0000000178692551)↗
DOE OSTI2021

Using an Atom Interferometer to Infer Gravitational Entanglement Generation

If gravitational perturbations are quantized into gravitons in analogy with the electromagnetic field and photons, the resulting graviton interactions should lead to an entangling interaction between massive objects. We suggest a test of this prediction. To do this, we introduce the concept of interactive quantum information sensing. This novel sensing protocol is tailored to provable verification of weak dynamical entanglement generation between a pair of systems. We show that this protocol is highly robust to typical thermal noise sources. The sensitivity can moreover be increased both using an initial thermal state and/or an initial phase of entangling via a non-gravitational interaction. We outline a concrete implementation testing the ability of the gravitational field to generate entanglement between an atomic interferometer and mechanical oscillator. Preliminary numerical estimates suggest that near-term devices could feasibly be used to perform the experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

ELG×LRG Distribution through Dark Matter Halo Dynamics

We investigate the clustering and halo occupation distribution (HOD) of DESI Y1 emission-line (ELGs) and luminous red (LRGs) galaxies at 0.8 < z < 1.1, including their cross-correlation (ELG×LRG), using the A BACUS S UMMIT suite and a new Halo Occupation Model (H OME ) for galaxy multitracers. This integrates intrahalo dynamics, halo exclusion, and quenching, bridging insights from hydrodynamical, HOD, abundance-matching, and semianalytic studies. Leveraging full phase-space information from the Uchuu N-body simulation, and sampling satellites from dark-matter particle positions via physically motivated prescriptions, Home reproduces the anisotropic clustering down to s = 200 h −1 kpc with unprecedented accuracy. Model parameters are inferred solely from two-point statistics using a two-level Bayesian framework, yielding high-fidelity ELG, LRG, and cross-reference catalogs. We find that satellite ELGs behave as incoherent flows within their parent halos, dominating the clustering below 4 h −1 Mpc. The HOD from the best-fit Home has the following properties: (i) 90.50% (85.91%) of ELGs (LRGs) are central galaxies without satellites, residing in halos of M vir ∼ 6.6 × 10 11 (1.2 × 10 13 ) h −1 M ⊙ ; (ii) the ELG×LRG cross-correlation is governed by central-central pairs and shaped by halo exclusion on 2–5 h −1 Mpc scales; (iii) 9.50% (14.09%) of ELGs (LRGs) are satellites, of which 1.09% (3.52%) inhabit halos with a central galaxy of the same species in a maximally conformal configuration, 7.02% (0.005%) orbit complementary hosts in a minimally conformal state, and 0.58% (10.57%) are orphans. The high sensitivity of Home precisely captures the dynamics of satellites in different host environments, opening a promising avenue for understanding systematics and the dynamical nature of dark matter, potentially distinguishing gravity models.

Favole, Ginevra [Universidad de La Laguna (Spain);↗
DOE OSTI2024

Disentangling top-down drivers of mortality underlying diel population dynamics of Prochlorococcus in the North Pacific Subtropical Gyre

Photosynthesis fuels primary production at the base of marine food webs. Yet, in many surface ocean ecosystems, diel-driven primary production is tightly coupled to daily loss. This tight coupling raises the question: which top-down drivers predominate in maintaining persistently stable picocyanobacterial populations over longer time scales? Motivated by high-frequency surface water measurements taken in the North Pacific Subtropical Gyre (NPSG), we developed multitrophic models to investigate bottom-up and top-down mechanisms underlying the balanced control of Prochlorococcus populations. Here, we find that incorporating photosynthetic growth with viral- and predator-induced mortality is sufficient to recapitulate daily oscillations of Prochlorococcus abundances with baseline community abundances. In doing so, we infer that grazers in this environment function as the predominant top-down factor despite high standing viral particle densities. The model-data fits also reveal the ecological relevance of light-dependent viral traits and non-canonical factors to cellular loss. Finally, we leverage sensitivity analyses to demonstrate how variation in life history traits across distinct oceanic contexts, including variation in viral adsorption and grazer clearance rates, can transform the quantitative and even qualitative importance of top-down controls in shaping Prochlorococcus population dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Topology-Dependent Polymer Stretching and Scission in Solution at Extreme Shear Rates

There has been significant interest in the engineering of polymer topology to control rheology and mechanical stability in dilute solutions for applications involving extreme shear rate flows. However, methods to experimentally probe properties at relevant shear rates (≈ 10 4 –10 6 s –1 ) have remained ex situ, obscuring access to measures of polymer deformation and rheology that would otherwise provide mechanistic insight into the topology-dependent properties that control their behavior in extreme shear flows. In this study, we used novel in situ small angle neutron scattering measurements in a capillary rheometer (capillary rheo-SANS) to simultaneously measure solution viscosities and polymer deformations in high shear on a series of chemically homologous topology-defined polymers including linear, randomly branched, and star-shaped molecules. We demonstrate that differences in the onset of chain stretching and shear thinning of these polymers in dilute solution are controlled primarily by differences in their molecular relaxation time. These differences correlate with differences in chain scission inferred from ex situ measurements at more extreme shear rates. Together, the results demonstrate a direct coupling between chain deformation and scission, and suggest that the dominant effect of branching as a means to impart resilience against mechanical degradation is through differences in relaxation dynamics due to branching. We anticipate that these results will provide key insights to engineer topology-controlled polymers for rheological modification, mechanical stability, and controlled mechano-chemistry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Evidence and modeling of turbulence bifurcation in L-mode confinement transitions on Alcator C-Mod

Analysis and modeling of rotation reversal hysteresis experiments show that a single turbulent bifurcation is responsible for the Linear to Saturated Ohmic Confinement (LOC/SOC) transition and concomitant intrinsic rotation reversal on Alcator C-Mod. Plasmas on either side of the reversal exhibit different toroidal rotation profiles and therefore different turbulence characteristics despite the profiles of density and temperature, which are indistinguishable within measurement uncertainty. Elements of this bifurcation are also shown to persist for auxiliary heated L-modes. The deactivation of subdominant (in the linear growth rate and contribution to heat transport) ion temperature gradient and trapped electron mode instabilities is identified as the only possible change in turbulence within a reduced quasilinear transport model across the reversal, which is consistent with the measured profiles and inferred heat and particle fluxes. Experimental constraints on a possible change from strong to weak turbulence, outside the description of the quasilinear model, are also discussed. These results indicate an explanation for the LOC/SOC transition that provides a mechanism for the hysteresis through the dynamics of subdominant modes and changes in their relative populations and does not involve a change in the most linearly unstable ion-scale drift-wave instability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Quantification of early nonpharmaceutical interventions aimed at slowing transmission of Coronavirus Disease 2019 in the Navajo Nation and surrounding states (Arizona, Colorado, New Mexico, and Utah)

During an early period of the Coronavirus Disease 2019 (COVID-19) pandemic, the Navajo Nation, much like New York City, experienced a relatively high rate of disease transmission. Yet, between January and October 2020, it experienced only a single period of growth in new COVID-19 cases, which ended when cases peaked in May 2020. The daily number of new cases slowly decayed in the summer of 2020 until late September 2020. In contrast, the surrounding states of Arizona, Colorado, New Mexico, and Utah all experienced at least two periods of growth in the same time frame, with second surges beginning in late May to early June. Here, we investigated these differences in disease transmission dynamics with the objective of quantifying the contributions of non-pharmaceutical interventions (NPIs) (e.g., behaviors that limit disease transmission). We considered a compartmental model accounting for distinct periods of NPIs to analyze the epidemic in each of the five regions. We used Bayesian inference to estimate region-specific model parameters from regional surveillance data (daily reports of new COVID-19 cases) and to quantify uncertainty in parameter estimates and model predictions. Our results suggest that NPIs in the Navajo Nation were sustained over the period of interest, whereas in the surrounding states, NPIs were relaxed, which allowed for subsequent surges in cases. Our region-specific model parameterizations allow us to quantify the impacts of NPIs on disease incidence in the regions of interest.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Dynamic Equivalence of Large-Scale Power Systems Based on Boundary Measurements

Parallel computing helped speed up many tasks that can be done independently. The advance in gaming industry did not produce a technology that helps the power industry to reduce the computation time for dynamic simulation in individual cases. To perform faster than real-time simulation for the purpose of predicting power system dynamic trajectory, power industry continues to struggle to reduce the system size and simulation time of large-scale power systems while keeping its dynamic behavior under various disturbances. There is also an acute need for real-time dynamic model reduction as more renewables enter the generation mix with dramatic changes in the generation outputs. All existing model reduction solutions are based on having access to a detailed dynamic model of the system. The system changes by the minutes, dynamic models are only updated annually. To solve this problem, wide-area measurements obtained by the phasor measurement unit (PMU) at the boundaries between the reduced system and the study system is used to represent the external area. An artificial neuro-fuzzy inference system (ANFIS) is established to perform the mapping of the measurement to the external equivalent model. Here the external area is regarded as a black-box. Model reduction studies are conducted on the Northeast Power Coordinating Council (NPCC) under various types of contingencies, by using a co-simulation approach between PSS/E and MATLAB. The results look very promising and will be discussed in this paper.

Tong, Ning↗
DOE OSTI2025

Bubbler Design Updates for Nuclear Safeguards Applications

The accurate monitoring of molten salt compositions is crucial for nuclear safeguards, particularly in the context of mixtures used in molten salt reactors as well as pyroprocessing. However, for nuclear material accountancy in actinide bearing molten salts, the solution volume is also needed to determine the total mass of material in the salt. This study explores the effectiveness of two bubbler configurations, triple and single, for density and level measurements within these molten salts for salt volume determinations. The triple bubbler system utilizes three gas dip-tubes strategically positioned at different heights within the molten salt. With this design, the molten salt level, density, and surface tension can be determined simultaneously. The single bubbler configuration, on the other hand, relies on a dynamic single dip-tube to determine the density and level. Both configurations will be tested in aqueous solutions as well as in LiCl-KCl and NaCl-MgCl2 molten salts between 450°C and 750°C. Dip-tube diameters and bubbler inferences will also be explored. A new bubbler is being designed based on results. The findings of this study will provide valuable insights into the optimal bubbler design and configuration for ensuring representative sampling of molten salt compositions in nuclear safeguards applications. This will contribute to enhanced accountability and transparency in the monitoring of actinide bearing molten salts, promoting nuclear safeguards objectives.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Tunable Microwave Conductance of Nanodomains in Ferroelectric PbZr 0.2 Ti 0.8 O 3 Thin Film

Ferroelectric materials exhibit spontaneous polarization that can be switched by electric field. Beyond traditional applications as nonvolatile capacitive elements, the interplay between polarization and electronic transport in ferroelectric thin films has enabled a path to neuromorphic device applications involving resistive switching. A fundamental challenge, however, is that finite electronic conductivity may introduce considerable power dissipation and perhaps destabilize ferroelectricity itself. In this work, tunable microwave frequency electronic response of domain walls injected into ferroelectric lead zirconate titanate (PbZr 0.2 Ti 0.8 O 3 ) on the level of a single nanodomain is revealed. Tunable microwave response is detected through first-order reversal curve spectroscopy combined with scanning microwave impedance microscopy measurements taken near 3 GHz. Contributions of film interfaces to the measured AC conduction through subtractive milling, where the film exhibited improved conduction properties after removal of surface layers, are investigated. Using statistical analysis and finite element modeling, we inferred that the mechanism of tunable microwave conductance is the variable area of the domain wall in the switching volume. These observations open the possibilities for ferroelectric memristors or volatile resistive switches, localized to several tens of nanometers and operating according to well-defined dynamics under an applied field.

36 MATERIALS SCIENCE↗
DOE OSTI2026

In-situ sensor monitoring of multi-class gas porosity formation in laser powder bed fusion using convolutional neural network

In-situ monitoring of defect formation remains a significant challenge in the laser powder bed fusion (LPBF) process. Recent advances have enabled real-time defect detection with machine learning and in-situ sensing technologies; however, most studies focus on binary classification of keyhole pores, limiting nuanced multi-class pore differentiation and formation mechanisms. This work introduces a multi-class pore detection framework (no pore, small pores < 15 µm, and large pores > 15 µm) by leveraging photodiode sensor data alongside high-fidelity synchrotron X-ray imaging. The 15 µm threshold is selected to distinguish between two fundamentally different defect mechanisms, following the physical size-mechanism boundary established by prior high-resolution synchrotron X-ray characterization of Al6061 LPBF. Distinguishing these classes is critical because large keyhole pores are structurally detrimental, whereas small gas pores are often benign, requiring different process control strategies. Thermal emission monitoring data collected simultaneously with high-speed X-ray imaging at the Stanford Synchrotron Radiation Lightsource (SSRL), are correlated with subsurface melt pool dynamics to establish ground truth. Continuous Wavelet Transform (CWT) with optimized parameters converts the photodiode time-series signals into time–frequency images, facilitating feature extraction. Convolutional Neural Networks (CNN) are then applied for real-time multi-class pore classification in an average inference time of 1 ms per signal window. It achieves 79% accuracy and an Area Under the Receiver Operating Characteristic curve (AUC ROC) score of 0.89 with five-fold cross-validation. The results demonstrate that coupling CWT-based feature engineering with CNN architecture enables reliable multi-class pore detection in Al6061 builds using affordable in-situ sensors. This approach advances scalable and affordable quality assurance in additive manufacturing by moving beyond binary defect detection toward more nuanced classification of porosity mechanisms with in-situ sensors and machine learning.

Laser powder bed fusion, Multi-class pores, In-sit↗
DOE OSTI2020

Structural disorder, sublattice melting, and thermo-elastic properties of anti-perovskite Li 3 OBr under high pressure and temperature

Here, in situ synchrotron x-ray diffraction experiments were conducted in the system Li-O-Br at pressures up to 6.5 GPa and temperatures up to the melting points. The thermal equation of state determined from the P–V–T measurements indicates that crystalline anti-perovskite Li 3 OBr exhibits similar thermo-elastic properties to common salts. At temperatures that are 50–75 °C below the crystal melting, a pre-melting behavior was inferred based on weakened Bragg intensity and a substantial increase in the diffuse scattering. Concurrent with the onset of pre-melting, an anomalous increase in the lattice volume was observed and is interpreted as anion sublattice disorder. These findings support previous ab initio molecular dynamics simulations based on a simple anion interchange mechanism, indicating that structural disorder below crystal melting temperature can be a main driving force for Li-sublattice melting and superionic transition in the Li 3 OBr anti-perovskite.

36 MATERIALS SCIENCE↗
DOE OSTI2021

UniverseMachine: Predicting Galaxy Star Formation over Seven Decades of Halo Mass with Zoom-in Simulations

In this work, we apply the empirical galaxy–halo connection model UniverseMachine to dark-matter-only zoom-in simulations of isolated Milky Way (MW)–mass halos, along with their parent cosmological simulations. This application extends UniverseMachine predictions into the ultrafaint dwarf galaxy regime (10 2 M ⊙ ≤ M * ≤ 10 5 M ⊙) and yields a well-resolved stellar mass–halo mass (SMHM) relation over the peak halo mass range of 10 8 –10 15 M ⊙. The extensive dynamic range provided by the zoom-in simulations allows us to assess specific aspects of dwarf galaxy evolution predicted by UniverseMachine. In particular, although UniverseMachine is not constrained for dwarf galaxies with M * ≲ 10 8 M ⊙, our predicted SMHM relation is consistent with that inferred for MW satellite galaxies at z = 0 using abundance matching. However, UniverseMachine predicts that nearly all galaxies are actively star-forming below M * ~ 10 7 M ⊙ and that these systems typically form more than half of their stars at z ≲ 4, which is discrepant with the star formation histories of Local Group dwarf galaxies that favor early quenching.

79 ASTRONOMY AND ASTROPHYSICS↗