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At least 775 records · Page 43

Mapping causal patterns in crystalline solids

The evolution of the atomic structures of the combinatorial library of Sm-substituted thin film BiFeO 3 along the phase transition boundary from the ferroelectric rhombohedral phase to the non-ferroelectric orthorhombic phase is explored using scanning transmission electron microscopy. Localized properties, including polarization, lattice parameter, and chemical composition, are parameterized from atomic-scale imaging, and their causal relationships are reconstructed using a linear non-Gaussian acyclic model. This approach is further extended to explore the spatial variability of the causal coupling using the sliding window transform method, which revealed that new causal relationships emerged at both the expected locations, such as domain walls and interfaces, and at additional regions forming clusters in the vicinity of the walls or spatially distributed features. While the exact physical origins of these relationships are unclear, they likely represent nanophase-separated regions in the morphotropic phase boundaries. Overall, we posit that an in-depth understanding of complex disordered materials away from thermodynamic equilibrium necessitates understanding not only the generative processes that can lead to observed microscopic states but also the causal links between multiple interacting subsystems.

Causal inference↗

Coupling Shared E-scooters and Public Transit: A Spatial and Temporal Analysis

The integration of shared e-scooters with public transit is a promising solution for urban mobility's first/last-mile challenge. This study explores spatiotemporal factors influencing this integration, using 35-day e-scooter trip data from Chicago. Employing a random-effect negative binomial approach, we modeled the frequency of e-scooter trips to access/egress to/from bus stops and train stations. Results indicate that weather conditions, design features like intersection density, and multimodal network density significantly influence usage. The transit system characteristics such as service frequency have a positive effect on the integration of e-scooters and trains while a similar effect for bus and e-scooter integration was not significant. Furthermore, safety-related variables such as accident and crime rates as well as demographic characteristics were also revealed to be significant factors in our study. These findings offer vital insights to urban planners and policymakers for infrastructure, safety enhancements, and interventions to encourage efficient e-scooter-public transit integration.

Chicago↗

Magnon damping and mode softening in quantum double-exchange ferromagnets

We present a comprehensive analysis of the magnetic excitations and electronic properties of fully quantum double-exchange ferromagnets, i.e. systems where ferromagnetic (FM) ordering emerges from the competition between spin, charge, and orbital degrees of freedom, but without the canonical approximation of using classical localized spins. Specifically, we investigate spin excitations within the Kondo lattice-like model, as well as a two-orbital Hubbard Hamiltonian in proximity to the orbital-selective Mott phase. Computational analysis of the magnon dispersion, damping, and spectral weight within these models reveals unexpected phenomena, such as magnon mode softening and the anomalous decoherence of magnetic excitations as observed in earlier experimental efforts, but explained here without the use of the phononic degrees of freedom. We show that these effects are intrinsically linked to incoherent spectral features near the Fermi level, which arise due to the quantum nature of the local (on-site) triplets. This incoherent spectrum leads to a Stoner-like continuum on which spin excitations scatter, governing magnon lifetime and strongly influencing the dynamical spin structure factor. Our study explores the transition from coherent to incoherent magnon spectra by varying the electron density. Furthermore, we demonstrate that the magnitude of the localized spin mitigates decoherence by suppressing the incoherent spectral contributions near the Fermi level. We also discuss the effective J 1 –J 2 spin Hamiltonian, which can accurately describe the large doping region characterized by the magnon-mode softening. Finally, we show that this behavior is also present in multiorbital models with partially filled orbitals, namely, in systems without localized spin moments, provided that the model is in a strong coupling regime. Our results potentially have far-reaching implications for understanding FM ordering in various multi-band systems. These findings establish a previously unknown direct connection between the electronic correlations of those materials and spin excitations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Extremely massive disc galaxies in the nearby Universe form through gas-rich minor mergers

ABSTRACT In our hierarchical structure-formation paradigm, the observed morphological evolution of massive galaxies – from rotationally supported discs to dispersion-dominated spheroids – is largely explained via galaxy merging. However, since mergers are likely to destroy discs, and the most massive galaxies have the richest merger histories, it is surprising that any discs exist at all at the highest stellar masses. Recent theoretical work by our group has used a cosmological, hydrodynamical simulation to suggest that extremely massive (M* > 1011.4 M⊙) discs form primarily via minor mergers between spheroids and gas-rich satellites, which create new rotational stellar components and leave discs as remnants. Here, we use UV-optical and H i data of massive galaxies, from the Sloan Digital Sky Survey, Galaxy Evolution Explorer, Dark Energy Camera Legacy Survey (DECaLS), and Arecibo Legacy Fast ALFA surveys, to test these theoretical predictions. Observed massive discs account for ∼13 per cent of massive galaxies, in good agreement with theory (∼11 per cent). ∼64 per cent of the observed massive discs exhibit tidal features, which are likely to indicate recent minor mergers, in the deep DECaLS images (compared to ∼60 per cent in their simulated counterparts). The incidence of these features is at least four times higher than in low-mass discs, suggesting that, as predicted, minor mergers play a significant (and outsized) role in the formation of these systems. The empirical star formation rates agree well with theoretical predictions and, for a small galaxy sample with H i detections, the H i masses and fractions are consistent with the range predicted by the simulation. The good agreement between theory and observations indicates that extremely massive discs are indeed remnants of recent minor mergers between spheroids and gas-rich satellites.

79 ASTRONOMY AND ASTROPHYSICS↗

Exploring the dependence of gas cooling and heating functions on the incident radiation field with machine learning

ABSTRACT Gas cooling and heating functions play a crucial role in galaxy formation. But, it is computationally expensive to exactly compute these functions in the presence of an incident radiation field. These computations can be greatly sped up by using interpolation tables of pre-computed values, at the expense of making significant and sometimes even unjustified approximations. Here, we explore the capacity of machine learning to approximate cooling and heating functions with a generalized radiation field. Specifically, we use the machine learning algorithm XGBoost to predict cooling and heating functions calculated with the photoionization code cloudy at fixed metallicity, using different combinations of photoionization rates as features. We perform a constrained quadratic fit in metallicity to enable a fair comparison with traditional interpolation methods at arbitrary metallicity. We consider the relative importance of various photoionization rates through both a principal component analysis (PCA) and calculation of SHapley Additive exPlanation (shap) values for our XGBoost models. We use feature importance information to select different subsets of rates to use in model training. Our XGBoost models outperform a traditional interpolation approach at each fixed metallicity, regardless of feature selection. At arbitrary metallicity, we are able to reduce the frequency of the largest cooling and heating function errors compared to an interpolation table. We find that the primary bottleneck to increasing accuracy lies in accurately capturing the metallicity dependence. This study demonstrates the potential of machine learning methods such as XGBoost to capture the non-linear behaviour of cooling and heating functions.

79 ASTRONOMY AND ASTROPHYSICS↗

The vertical-velocity skewness in the atmospheric boundary layer without buoyancy and Coriolis effects

One of the main features of near-neutral atmospheric boundary layer (ABL) turbulence is the positive vertical velocity skewness $Sk_w$ above the roughness sublayer or the buffer region in smooth-walls. The $Sk_w$ variations are receiving renewed interest in many climate-related parameterizations of the ABL given their significance to cloud formation and to testing sub-grid schemes for Large Eddy Simulations (LES). The vertical variations of $Sk_w$ are explored here using wind tunnel and flume experiments collected above smooth, rough, and permeable-walls in the absence of buoyancy and Coriolis effects. These laboratory experiments form a necessary starting point to probe the canonical structure of $Sk_w$ as they deal with a key limiting case (i.e., near-neutral conditions). Diagnostic models based on cumulant expansions, realizability constraints, and constant mass flux approach routinely employed in the convective boundary layer as well as prognostic models based on third-order budgets are used to explain variations in $Sk_w$ for the idealized laboratory conditions. The failure of flux-gradient relations to model $Sk_w$ from the gradients of the vertical velocity variance σ$_w^2$ are explained and corrections based on models of energy transport offered. Novel links between the diagnostic and prognostic models are also featured, especially for the inertial term in the third-order budget of the vertical velocity fluctuation. The co-spectral properties of w′/σ w vs w′ 2 /σ$_w^2$ are also presented for the first time to assess the dominant scales governing $Sk_w$ in the inner and outer layers, where w′ is the fluctuating vertical velocity and σ w is the vertical velocity standard deviation.>

Boundary layer flow↗

Connecting People to Data: Enabling Data Connected Communities through Enhancements to the Geothermal Data Repository

The Department of Energy's (DOE) Geothermal Data Repository (GDR) has implemented a series of new features designed to connect people to data. These features, which are based on feedback from the GDR user community and surveys of the greater geothermal research community, are designed to improve data quality and empower members of all communities to better engage with geothermal data resources by providing universal access to data and by improving the connections between data providers, subject matter experts, and the communities of people using GDR data. This paper will explore some of the recent enhancements made to the GDR to improve data discoverability, reduce submission time, and result in better quality data submissions. These improvements include the ability for users to save a list of their favorite datasets, search for insight into geothermal datasets or data availability, or sign up to receive notifications of future updates to specific datasets. These improvements aim to enhance the overall user experience of the GDR while further connecting communities to the data they need to inform decisions, advance geothermal research, and develop innovative solutions to local energy problems.

access↗

Atomic-resolution imaging as a mechanistic tool for studying single-site heterogeneous catalysis

Heterogeneous catalysts dominate the chemical industry but typically feature diverse, incompletely defined active sites. Thus, describing structure-activity relationships, unlike homogeneous catalysts, remains challenging. In contrast, molecularly defined single-site heterogeneous catalysts (SSHCs), using appropriate tools, are poised to address these challenges and provide new avenues for catalysis research and development. The present study explores eco-friendly H 2 production mediated by discrete MoO 2 sites supported on carbon nanohorns (CNHs) and active for alcohol dehydrogenation. While informative, detailed ensemble EXAFS/XANES/XPS, kinetic measurements, and DFT analysis alone cannot provide a full molecular picture of the reaction pathway. Here, using single-molecule atomic-resolution time-resolved electron microscopy (SMART-EM), we propose the identification of four key catalytic intermediates anchored to CNHs and uncover a new reaction pathway involving alkoxide/hemiacetal equilibration and acetal oligomerization. Furthermore, these intermediates are inferred through a combination of theory and SMART-EM, showcasing the potential of SMART-EM as a complementary tool for exploring mechanistic hypotheses in catalysis.

36 MATERIALS SCIENCE↗

Near-infrared spectra and molar absorption coefficients of trivalent lanthanides dissolved in molten LiCl–KCl eutectic

Determining the concentration of the dissolved lanthanide species in LiCl–KCl eutectic salt is important to the development of pyrochemical reprocessing of used nuclear fuel. In this process, lanthanide fission products are found dissolved in the electrorefiner electrolyte in their trivalent oxidation state. The presence of dissolved trivalent lanthanides increases the liquidus temperature of the electrolyte mixture and can lead to the formation of insoluble oxide or oxychloride phases and must therefore be continuously monitored and controlled during the operation. Absorbance spectroscopy is a promising method for continuous measurement of the concentration of lanthanides and other elements dissolved in the electrolyte. The absorption of light by elements is linearly proportional to the concentration of the element for relatively dilute solutions according to the Beer-Lambert law. Although measurement of the absorption of ultraviolet and visible range light by lanthanides in LiCl–KCl eutectic molten salt have been explored previously, near infrared (NIR) absorption spectroscopy has received far less attention. It may, however, provide a better analytical signal when insoluble phases are present due to less Raleigh scattering compared to shorter wavelength radiation. Additionally, it may allow for concentration determination for certain elements using NIR absorption features where UV and visible range features are overlapping with features from other species. In this study, we report the UV–Vis–NIR spectra of the trivalent lanthanide chlorides of neodymium, samarium, and dysprosium in LiCl–KCl eutectic. Molar absorption coefficients are reported for analytically useful absorption maxima, with a focus on the molar absorption coefficients for NIR absorption maxima which have not been reported previously. Additionally, we observe a NIR-range absorption band of Nd3+ which was previously predicted but never experimentally observed. Here, we compare the calculated crystal field levels to the newly observed absorbance band and find them to be in good agreement with previous predictions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Frontal Polymerization of Stereoisomers: Distinct Microstructures and Properties in Endo- and Exo- Dicyclopentadiene Thermosets

This study explores the relationship between monomer stereochemistry and the materials properties of thermosets generated by frontal ring-opening metathesis polymerization (FROMP). The exo- and endo-stereoisomers of dicyclopentadiene (DCPD) undergo rapid FROMP to fabricate robust thermosets within seconds. The exo-isomer provides significant benefits compared to the commonplace endo-DCPD resins; exo-DCPD supports faster fronts (≈3 times faster) than the endo-analogue and is an easier-to-handle liquid at room temperature. This work is among the first to explore the materials properties of p(exo-DCPD) thermosets. Here, we demonstrate a significant decrease in T g for products derived from exo-DCPD, despite having a similar rubbery plateau compared to p(endo-DCPD). Soluble oligomers were synthesized as models to probe the microstructural features affected by the monomer stereochemistry. Interestingly, hydrogenated oligomers of endo-DCPD exhibit slight differences in stereoregularity compared to their exo-counterparts. Finally, we incorporated a bisnorbornenyl cross-linker in exo-DCPD resins to boost the polymer T g , while also maintaining fronts that propagate faster than endo-DCPD.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revealing Mesoscale Ionomer Membrane Structure by Tender Resonant X-ray Scattering

Nafion, a perfluorosulfonic acid ionomer, has been well-studied for decades due to its key role as an ion-conductive membrane in electrochemical energy conversion and storage applications. When hydrated, this membrane phase separates into a complex hierarchical nanostructure with hydrophilic domains that facilitate ion transport. Hard X-ray scattering has been a powerful technique in understanding Nafion due to its capabilities in capturing the ionomer’s nanophase separated structure, which gives rise to contrast between polymer and water domains. More recently, resonant X-ray scattering, which tunes to elemental absorption edges to provide specificity on constituent elements, has been explored to highlight key interactions related to the sulfonic acid groups within its structure. Here, in this work, we study the Nafion nanostructure by combining hard X-ray scattering and tender resonant X-ray scattering (TReXS) at the sulfur K-edge to reveal a mesoscopic feature corresponding to a correlation length of approximately 40 nm that has been challenging to resolve with hard X-ray studies. Additionally, we study the effect of the dispersion solvent composition that plays a key role in the formation of this mesoscale feature. Notably, TReXS can attain high contrast to decipher this mesoscale morphology even for dry polymer membranes under a vacuum, which typically have reduced contrast for hard X-rays. We find that the correlation length of this mesoscale feature decreases with increasing water fraction in the dispersion, which is the opposite trend exhibited by the smaller intercrystalline feature in the same membranes. This study showcases the utility of TReXS to uncover multiscale morphological details in functional polymers that are not always revealed by other methods like hard X-ray scattering. We illustrate this with Nafion, which is a relevant ion-conducting polymer for electrochemical technologies.

36 MATERIALS SCIENCE↗

Impact of a New Cloud Microphysics Parameterization on the Simulations of Mesoscale Convective Systems in E3SM

Abstract Mesoscale convective systems (MCSs) are one of the most climatically significant forms of convection because of their large role in water and energy cycles. The mesoscale features associated with MCS are difficult to represent in climate models because the relevant dynamics and physics are absent or poorly represented with coarse model resolution (∼100 km). Using a regionally refined model (RRM) with 0.25° grid spacing embedded in the Energy Exascale Earth System Model (E3SM), we explore the impact of cloud microphysics parameterizations on the simulation of precipitation, particularly MCS precipitation over the contiguous United States. The Predicted Particle Properties (P3) cloud microphysics scheme has been modified and implemented into E3SM to overcome the limitations of the default Morrison and Gettelman (MG2) scheme in which rimed precipitating ice particles (graupel/hail) are absent and frozen particles are artificially partitioned into cloud ice and snow. We show that P3 improves the simulation of precipitation statistics including frequency distribution compared with MG2 with a limited effect on the diurnal cycle. P3 predicts higher hourly rain rates, resulting in 20% more MCSs and a higher total MCS precipitation (4.4%) compared to MG2, agreeing better with observations. The improvements with P3 mainly result from improved representations of ice microphysics, which not only produces higher rain rates through melting but also leads to a stronger large‐scale ascending motion by releasing more latent heating. This study suggests that improving microphysics parameterization is important for simulating MCS precipitation as future climate model resolutions continue to increase.

54 ENVIRONMENTAL SCIENCES↗

Machine learning prediction of self-diffusion in Lennard-Jones fluids

In this work, different machine learning (ML) methods were explored for the prediction of self-diffusion in Lennard-Jones (LJ) fluids. Using a database of diffusion constants obtained from the molecular dynamics simulation literature, multiple Random Forest (RF) and Artificial Neural Net (ANN) regression models were developed and characterized. The role and improved performance of feature engineering coupled to the RF model development was also addressed. The performance of these different ML models was evaluated by comparing the prediction error to an existing empirical relationship used to describe LJ fluid diffusion. It was found that the ANN regression models provided superior prediction of diffusion in comparison to the existing empirical relationships.

74 ATOMIC AND MOLECULAR PHYSICS↗

Twinned nanostructure of VO 2 thin films grown on r-cut sapphire

Due to strong electron-phonon interactions, strain engineering is a powerful tool to control quantum critical phenomena in strongly correlated oxides. Exploring this possibility requires understanding the nanoscale structure of quantum materials and the role it plays in forming the strain landscape. In this work, we used a combination of x-ray nanoimaging and reciprocal space mapping to study the nanostructure of the archetypal Mott insulator VO 2 featuring an insulator-to-metal and structural phase transitions. We found that VO 2 thin films grown on r-cut sapphire consist of two intertwined crystal lattices, permanently inclined with respect to each other. This persistent pattern of twin domains stands out from the symmetry breaking induced by the structural phase transition and conceivably originates from the post-growth strain relaxation process. We propose a model explaining the formation of twin domains and the emergence of anisotropy in the film nanostructure. Our work suggests using miscut substrates to suppress either one or the other twin that can serve as a new tool to control strain in VO 2 films.

36 MATERIALS SCIENCE↗

Vortex rings in event-by-event relativistic heavy-ion collisions

We present event-by-event simulations for central asymmetric light+heavy and Au +Au collisions to investigate the formation and evolution of vortex-ring structures in the longitudinal flow velocity profile. The production-plane polarization of Λ hyperons, defined with respect to the Λ momentum and the beam, can track the “vortex-ring” feature in the event, a characteristic vortical structure generated by longitudinal flow gradients. We make comprehensive model predictions for the rapidity-dependent vortex-ring observables for different collision system sizes at √s NN = 200 and 72 GeV. Furthermore, our predictions at the latter energy can be explored in the future LHCb fixed-target experiment at the Large Hadron Collider.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Relationship between molecular structure and corrugations in self-assembled polypeptoid nanosheets revealed by cryogenic electron microscopy

Designing conformationally dynamic molecules that self-assemble into predictable nanostructures remains an important unmet challenge. This paper describes how atomic-scale cryogenic transmission electron microscopy (cryo-TEM) can be used to explore the relationship between molecular structure and self-assembly of block copolymers. We examined sheetlike micelles formed in water using a series of diblock copolypeptoids with the same hydrophilic block and three distinct crystalline hydrophobic blocks. Our cryo-TEM images revealed all the structures share nansoscale features, but differ in their intermolecular packing geometries. Different molecular arrangements, parallel and antiparallel V-shaped crystal motifs, were revealed by two-dimensional atomic-scale through-plane images. However, images from tilted samples revealed an unexpected feature when the hydrophobic polypeptoid block comprised phenyl rings with substituted bromine atoms at the para position. The nanosheets contained atomic-scale corrugations that were absent in the other systems which comprised unsubstituted aliphatic and aromatic side chains. We hypothesize that these corrugations are due to the dipolar characteristics of the brominated phenyl group and interactions between this group and water molecules. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗

Emulation of quantum correlations by classical dynamics in a spin-$\frac{1}{2}$ Heisenberg chain

We simulate the dynamical spin structure factor (DSSF) 𝒮⁡(𝑞,𝜔) of the spin-1/2 Heisenberg antiferromagnetic chain using classical simulations. By employing Landau-Lifshitz Dynamics, we emulate quantum correlations through temperature-dependent corrections, including rescaling of magnetic dipoles and renormalization of exchange interactions. Here, our results closely match Quantum Monte-Carlo calculations for 𝑘 B⁢ 𝑇/𝐽≳1, extending the applicability of classical dynamics to the challenging case of gapless excitations. At higher temperatures, our simulations comply with general predictions for uncorrelated paramagnetic fluctuations in the infinite temperature limit. Entanglement witnesses derived from the quantum-equivalent DSSF act as sensitive diagnostics for the quantum-to-classical crossover. Their reliability stems from their dependence on spectral features alone, enabling classical dynamics to emulate quantum thresholds without genuine entanglement. This framework also reproduces transverse spin correlations in finite magnetic fields, in agreement with quantum simulations. Together, our results establish quantum-corrected classical dynamics as a scalable and predictive tool for interpreting scattering experiments and exploring quantum correlations in strongly correlated spin systems.

Inelastic neutron scattering↗

Resource selection functions based on hierarchical generalized additive models provide new insights into individual animal variation and species distributions

Habitat selection studies are designed to generate predictions of species distributions or inference regarding general habitat associations and individual variation in habitat use. Such studies frequently involve either individually indexed locations gathered across limited spatial extents and analyzed using resource selection functions (RSFs) or spatially extensive locational data without individual resolution typically analyzed using species distribution models. Both analytical methodologies have certain desirable features, but analyses that combine individual- and population-level inference with flexible non-linear functions may provide improved predictions while accounting for individual variation. Here, we describe how RSFs can be fit using hierarchical generalized additive models (HGAMs) using widely available software, providing a means to explore individual variation in habitat associations and to generate species distribution maps. We used GPS tracking data from golden eagles Aquila chrysaetos from across eastern North America with four environmental predictors to generate monthly distribution models. We considered three model structures that assumed different amounts of individual variation in the functional relationship between predictors and habitat use and used k-fold cross-validation to compare model performance. Models accounting for individual variability in shape and smoothness of functional responses performed best. Eagles exhibited the least amount of individual variation in response to land cover variables during winter months, with most individuals more closely adhering to the population-level trend. During the summer months, eagles exhibited more substantial individual variation in shape and smoothness of the functional relationships, suggesting some need to account for individual variation in eagle habitat use for both inferential and predictive purposes, during this time of year. Because they allow users to blend flexible functions with random effects structures and are well-supported by a variety of software platforms, we believe that HGAMs provide a useful addition to the suite of analyses used for modeling habitat associations or predicting species distributions.

54 ENVIRONMENTAL SCIENCES↗