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At least 253 records · Page 14

Assessing CESM2 Clouds and Their Response to Climate Change Using Cloud Regimes

Abstract The Community Earth System Model, version 2 (CESM2), has a very high climate sensitivity driven by strong positive cloud feedbacks. To evaluate the simulated clouds in the present climate and characterize their response with climate warming, a clustering approach is applied to three independent satellite cloud products and a set of coupled climate simulations. Using k -means clustering with a Wasserstein distance cost function, a set of typical cloud configurations is derived for the satellite cloud products. Using satellite simulator output, the model clouds are classified into the observed cloud regimes in both current and future climates. The model qualitatively reproduces the observed cloud configurations in the historical simulation using the same time period as the satellite observations, but it struggles to capture the observed heterogeneity of clouds which leads to an overestimation of the frequency of a few preferred cloud regimes. This problem is especially apparent for boundary layer clouds. Those low-level cloud regimes also account for much of the climate response in the late twenty-first century in four shared socioeconomic pathway simulations. The model reduces the frequency of occurrence of these low-cloud regimes, especially in tropical regions under large-scale subsidence, in favor of regimes that have weaker cloud radiative effects.

58 GEOSCIENCES↗

47 Tuc in Rubin Data Preview 1. Exploring Early LSST Data and Science Potential

We present analyses of the early data from Rubin Observatory’s Data Preview 1 (DP1) for the field of the globular cluster 47 Tuc. The DP1 data set for 47 Tuc includes four nights of observations from the Rubin Commissioning Camera (LSSTComCam), covering multiple bands (ugriy). We address challenges of crowding in the inner region of the cluster and toward the SMC in DP1, and demonstrate improved star–galaxy separation by fitting fifth-degree polynomials to the stellar loci in color–color diagrams and applying multidimensional sigma clipping. We compile a catalog of 3576 probable 47 Tuc member stars selected via a combination of isochrone, Gaia proper-motion, and color–color space matched filtering. We explore the sources of photometric scatter in the 47 Tuc color–color sequence, evaluating contributions from various potential sources, including differential extinction within the cluster. Finally, of the 72 well-characterized variables in the field, we recover three known variable stars, including two RR Lyrae and one eclipsing binary, in the coadd-based object catalog, and identify 62 in the difference image-based object catalog. Although the DP1 lightcurves have sparse temporal sampling, they appear to follow the patterns of densely sampled literature lightcurves well. Despite some data limitations for crowded-field stellar analysis, DP1 demonstrates the promising scientific potential for future LSST data releases.

Choi, Yumi [NSF National Optical-Infrared Astronom↗

The effect of massive stars on the ionized medium of extragalactic HII regions

Giant extragalactic H2 regions (GEHR) are centers of active star formation, ionized by populous clusters of OB stars. These objects are characterized by their low electron density, linear dimensions of order of 10(exp 2) - 10(exp 3) pc, varied morphology, and inhomogeneous distribution of the gas. They are ideal laboratories to study the processes of interaction between the gas and the stars, that could then be extended to the study of H2 and starburst galaxies. An observational program on a selected group of giant H2 regions with the use of one- and two-dimensional spectroscopy is being conducted. Our aim is two-fold: to understand the internal structure of the regions and to study the kinematics and dynamics of the ionized gas. A short report of our ongoing research is presented.

Castaneda, Hector O.↗

A Study of the December 1992 Westerly Wind Burst Event during TOGA COARE

Using the Penn State/NCAR MM5 mesoscale model, a westerly wind burst (WWB) that occurred during the period from 19 to 30 December 1992 over the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) has been simulated and compared with observation. This event is characterized by the presence of super cloud clusters and the occurrence of a major WWB that extended over the western and central Pacific Ocean. Although several of the observed convective systems were not precisely simulated by MM5, the model did capture many other observed characteristics, such as the explosive development of convection, the cyclonic circulation and the WWB. The WWB resulted from the coalescence of three types of tropical disturbances. The first type was a low-level westerly jet (LWJ) that developed at the equator and may be associated with the eastward propagation of an ISO (Intraseasonal Oscillation). The second type featured an easterly wave-like disturbance that originated in the south central Pacific Ocean and propagated westward. Finally, the third type involved a cross-equatorial flow that deflected Northern Hemispheric easterlies into the Southern Hemisphere and may be caused by inertial instability. These disturbances worked in concert, resulting in intense convection over the TOGA COARE region. Once intense convection developed, a large-scale circulation was produced over the western Pacific warm pool, propagated eastward, and initiated a WWB.

Chen, Chaing↗

Monte-Carlo Simulations of Heavy Ions Track Structures and Applications

In space, astronauts are exposed to protons, high ]energy heavy (HZE) ions that have a high charge (Z) and energy (E), and secondary radiation, including neutrons and recoil nuclei produced by nuclear reactions in spacecraft walls or in tissue. The astronauts can only be partly shielded from these particles. Therefore, on travelling to Mars, it is estimated that every cell nucleus in an astronaut fs body would be hit by a proton or secondary electron (e.g., electrons of the target atoms ionized by the HZE ion) every few days and by an HZE ion about once a month. The risks related to these heavy ions are not well known and of concern for long duration space exploration missions. Medical ion therapy is another situation where human beings can be irradiated by heavy ions, usually to treat cancer. Heavy ions have a peculiar track structure characterized by high levels of energy ]deposition clustering, especially in near the track ends in the so ]called eBragg peak f region. In radiotherapy, these features of heavy ions can provide an improved dose conformation with respect to photons, also considering that the relative biological effectiveness (RBE) of therapeutic ions in the plateau region before the peak is sufficiently low. Therefore, several proton and carbon ion therapy facilities are under construction at this moment

Plante, Ianik↗

Insights into the Nanostructure, Solvation, and Dynamics of Liquid Electrolytes through Small-Angle X-Ray Scattering

The fundamental understanding of nanostructures of liquid electrolytes is expected to enable transformative gains in electrochemical energy storage capacities. However, the solvation structures and molecular dynamics in electrolytes are hard to probe, which limits further performance improvements in macroscopic properties such as ionic conductivity, viscosity, and stability. Small-angle X-ray scattering (SAXS), a non-destructive method for nanostructures characterization in liquids, offers a unique perspective on molecular clusters, anion-cation pairs, solvation sheath, percolating network, aggregates, and domain sizes of electrolytes. Notably, the SAXS method has excellent time-resolution, enabling the study of molecular dynamics by operando characterization. This review focuses on the microscopic understanding of liquid electrolytes by SAXS and operando SAXS. The unique capabilities of X-ray scattering for intra- and inter-molecular relationship and nanostructure characterization of electrolytes are highlighted.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Coupling Microstructural Evolution Simulations to Material Property Degradation Predictions for Plasma-Facing Materials

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500 C to 1500 C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 D/m^2-s. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗

Connect microstructure evolution to property degradation with validated simulation

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500$^o$C to 1500$^o$C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 $\frac{D}{m^2s}$. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗

Robust design of semi-automated clustering models for 4D-STEM datasets

Materials discovery and design require characterizing material structures at the nanometer and sub-nanometer scale. Four-Dimensional Scanning Transmission Electron Microscopy (4D-STEM) resolves the crystal structure of materials, but many 4D-STEM data analysis pipelines are not suited for the identification of anomalous and unexpected structures. This work introduces improvements to the iterative Non-Negative Matrix Factorization (NMF) method by implementing consensus clustering for ensemble learning. We evaluate the performance of models during parameter tuning and find that consensus clustering improves performance in all cases and is able to recover specific grains missed by the best performing model in the ensemble. The methods introduced in this work can be applied broadly to materials characterization datasets to aid in the design of new materials.

Bruefach, Alexandra (ORCID:0000000209323477)↗

High-entropy electrolytes for practical lithium metal batteries

Electrolyte engineering is crucial for improving battery performance, particularly for lithium metal batteries. Recent advances in electrolytes have greatly improved cyclability by enhancing electrochemical stability at the electrode interfaces, but concurrently achieving high ionic conductivity has remained challenging. Here we report an electrolyte design strategy for enhanced lithium metal batteries by increasing the molecular diversity in electrolytes, which essentially leads to high entropy electrolytes (HEEs). We find that in weakly solvating electrolytes, the entropy effect reduces ion clustering while preserving the characteristic anion-rich solvation structures, which is characterized by synchrotron-based X-ray scattering and molecular dynamics simulations. Electrolytes with smaller- sized clusters exhibit a 2-fold improvement in ionic conductivity compared to conventional weakly- solvating electrolytes, enabling stable cycling at high current densities up to 2C (6.2 mA cm -2 ) in anode- free LiNi 0.6 Mn 0.2 Co 0.2 (NMC622)||Cu pouch cells. In conclusion, the efficacy of the design strategy is verified by performance improvements in three disparate weakly solvating electrolyte systems.

25 ENERGY STORAGE↗

Characterizing different motility-induced regimes in active matter with machine learning and noise

Here we examine motility-induced phase separation (MIPS) in two-dimensional run-and-tumble disk systems using both machine learning and noise fluctuation analysis. Our measures suggest that within the MIPS state there are several distinct regimes as a function of density and run time, so that systems with MIPS transitions exhibit an active fluid, an active crystal, and a critical regime. The different regimes can be detected by combining an order parameter extracted from principal component analysis with a cluster stability measurement. The principal component-derived order parameter is maximized in the critical regime, remains low in the active fluid, and has an intermediate value in the active crystal regime. We demonstrate that machine learning can better capture dynamical properties of the MIPS regimes compared to more standard structural measures such as the maximum cluster size. The different regimes can also be characterized via changes in the noise power of the fluctuations in the average speed. In the critical regime, the noise power passes through a maximum and has a broad spectrum with a 1/f 1.6 signature, similar to the noise observed near depinning transitions or for solids undergoing plastic deformation.

97 MATHEMATICS AND COMPUTING↗

A multi-step nucleation process determines the kinetics of prion-like domain phase separation

Compartmentalization by liquid-liquid phase separation (LLPS) has emerged as a ubiquitous mechanism underlying the organization of biomolecules in space and time. Here, we combine rapid-mixing time-resolved small-angle X-ray scattering (SAXS) approaches to characterize the assembly kinetics of a prototypical prion-like domain with equilibrium techniques that characterize its phase boundaries and the size distribution of clusters prior to phase separation. We find two kinetic regimes on the micro- to millisecond timescale that are distinguished by the size distribution of clusters. At the nanoscale, small complexes are formed with low affinity. After initial unfavorable complex assembly, additional monomers are added with higher affinity. At the mesoscale, assembly resembles classical homogeneous nucleation. Careful multi-pronged characterization is required for the understanding of condensate assembly mechanisms and will promote understanding of how the kinetics of biological phase separation is encoded in biomolecules.

59 BASIC BIOLOGICAL SCIENCES↗

Divanadium substituted keggin [PV 2 W 10 O 40 ] on non-reducible supports-Al 2 O 3 and SiO 2 : synthesis, characterization, and catalytic properties for oxidative dehydrogenation of propane

Molecular metal oxide cluster, K 5 [α-1,2-PV 2 W 10 O 40 ] (PV 2 W 10 ), was found to have intrinsic catalytic activity for the oxidative dehydrogenation of propane with high selectivity (> 80%) to propylene at low propane conversion (0.3%). Synthesis of dispersed PV 2 W 10 in non-reducible supports, γ-Al 2 O 3 and SiO 2 , was done by incipient wetness impregnation. The supported catalysts were characterized by IR, Raman spectroscopy, nitrogen adsorption, x-ray powder diffraction (PXRD), elemental analysis, hydrogen temperature-programmed reduction (H 2 –TPR), and ammonia temperature-programmed desorption (NH 3 –TPD). Catalytic testing of the supported PV 2 W 10 at equimolar cluster concentration revealed that when supported in γ-Al 2 O 3 it is more active (sevenfold increase in propane conversion) but in SiO 2 it is more selective to propylene (94%). The observed performance was due to both an increase in reducibility and higher concentration of strong acid sites for PV 2 W 10 supported in γ-Al 2 O 3 versus SiO 2 . Lastly, PV 2 W10 was shown to remain intact under reaction conditions indicating its thermal and oxidative stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bio‐Based Piezo‐ and Thermoresistive Photocurable Sensing Materials from Acrylated Epoxidized Soybean Oil

Abstract Bio‐based photocurable polymers are increasingly in demand as environmentally friendly materials for advanced applications. Together with functional fillers, these represent a next step for the generation of functional and active smart materials, compatible with additive manufacturing technologies. Herein, acrylated epoxidized soybean oil (AESO) mixed with different amounts of reduced graphene oxide (rGO) up to 6 wt% in order to obtain UV‐curable piezoresistive and thermoresistive materials, is reported. It is shown that the addition of rGO to AESO hinders the curing process, but always maintains double bond conversions higher than 50%. Composites are characterized by a good dispersion of micrometric filler clusters. Further, the thermal stabilities are close to 300 °C and crosslinking degrees are above 1.75 mmol cm –3 . The Young modulus of the composites decreases with the addition of the rGO fillers, in particular for the higher filler contents, and electrical conductivities up to 0.13 S m –1 are obtained for the composites with the highest rGO content. UV‐curable composites with piezoresistive and thermoresistive responses suitable for applications are thus obtained, characterized by gauge factors around 26 for deformations up to 2% and maximum thermoresistive sensitivity of S = 0.43, values similar to the values obtained for petroleum‐based materials.

Mendes‐Felipe, Cristian↗

Iron-sulfur clusters: the road to room temperature

Abstract Iron-sulfur proteins perform a wide variety of reactions central to the metabolisms of all living organisms. Foundational to their reaction chemistry are the rich electronic structures of their constituent Fe-S clusters, which differ in important ways from the active sites of mononuclear Fe enzymes. In this perspective, we summarize the essential electronic structure features that make Fe-S clusters unique, and point to the need for studies aimed at understanding the electronic basis for their reactivity under physiological conditions. Specifically, at ambient temperature, both the ground state and a large number of excited states are thermally populated, and thus a complete understanding of Fe-S cluster reactivity must take into account the properties, energies, and reactivity patterns of these excited states. We highlight prior research toward characterizing the low-energy excited states of Fe-S clusters that has established what is now a consensus model of these excited state manifolds and the bonding interactions that give rise to them. In particular, we discuss the low-energy alternate spin states and valence electron configurations that occur in Fe-S clusters of varying nuclearities, and finally suggest that there may be unrecognized functional roles for these states. Graphical abstract

Skeel, Brighton A. (ORCID:000000018458088X)↗

Galaxies as dynamical probes of cluster structure

The effects of galaxy-cluster tidal forces on the dynamical evolution of member galaxies are investigated by means of numerical simulations. The kinds of normal events in clusters that can have significant immediate or long-term effects on galaxies are reviewed; the principal cluster properties are discussed; and the simulation results are briefly characterized, summarizing the report of Miller (1986). The degree of damage to a galaxy is found to depend strongly on the distance at which it orbits the cluster center and on the 'hardness' of the cluster potential. It is suggested that observations of the internal structure of cluster galaxies can be used to explore the cluster gravitational potential near the center and help locate and identify the nonluminous mass.

Miller, R. H.↗

X-ray and Sunyaev-Zel'dovich Effect Measurements of the Gas Mass Fraction in Galaxy Clusters

We present gas mass fractions of 38 massive galaxy clusters spanning redshifts from 0.14 to 0.89, derived from Chandra X-ray data and OVRO/BIMA interferometric Sunyaev-Zel' dovich Effect (SZE) measurements. We use three models for the gas distribution: (1) an isothermal Beta-model fit jointly to the X-ray data at radii beyond 100 kpc and to all of the SZE data, (2) a nonisothermal double Beta-model fit jointly to all of the X-ray and SZE data, and (3) an isothermal Beta-model fit only to the SZE spatial data. We show that the simple isothermal model well characterizes the intracluster medium (ICM) outside of the cluster core, and provides consistently good fits to clusters spanning a wide range of morphological properties. The agreement in the results shows that the core can be satisfactorily accounted for by either excluding the core in fits to the X-ray data (the 100 kpc-cut model) or modeling the intracluster gas with a non-isothermal double Beta-model. We find that the SZE is largely insensitive to structure in the core.

LaRoque, Samuel J.↗