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At least 1,045 records · Page 58

Understanding interfacial crystallization dynamics on carbon fiber reinforced polypropylene composite manufacturing

Reinforcing polymers with discontinuous fibers improves mechanical properties, such as strength and stiffness, and in some cases achieve isotropic properties, rendering them suitable for various engineering applications. Matrix materials are generally highly engineered thermosets (e.g. crosslinked epoxies), bonded to the fiber periphery by proprietary surface and sizing chemistries. Semicrystalline thermoplastic matrices are less utilized due to poor fiber-matrix bonding resulting in inefficient interfacial load-transfer in reinforced composites. However, flexibility with melt-processing or molding conditions can be leveraged to promote non-covalent interfacial bonding between matrix and fiber via crystallization of the matrix onto fiber surface. In the present study, we utilize a co-mingle chopped carbon and isotactic polypropylene fibers to form isotropic composites, tailoring interfacial immobilized matrix or interphase morphology to optimize performance through precise control of thermal processing/molding windows. Calorimetry and optical microscopy were employed to investigate the impact of carbon fiber at various volume fractions (10, 20, and 30 %) on isotactic polypropylene crystallization and mechanical performance. Variations in mechanical properties correspond to the structural evolution of the interfacial region and are correlated to underlying microstructural attributes using wide-angle X-ray scattering, thermal analysis, and low-field nuclear magnetic resonance spectroscopy. These results provide a practical framework for the manufacturing of thermoplastic matrix composites. In conclusion, the results presented provide a guide for the strategic optimization of interphase design, showcasing tailorable tensile strengths which outperform any isotactic polypropylene carbon fiber composites previously reported in literature.

36 MATERIALS SCIENCE↗

Electronic structure, magnetic properties, and exchange splitting of gadolinium intermetallics

Here, we report here the electronic structure calculations of the magnetic moment, magneto-crystalline anisotropy energy (MAE), and density of states (DOS) of Gd-metal, GdAl 2 , GdAl 3 , GdCo 2 , GdCo 3 , and GdCo 5 . From the DOS, the exchange splitting energy is derived to map ferrimagnetic to paramagnetic phase transition (Curie temperature, T C ). The employed theoretical method here is based on advanced density functional theory, specifically the linearized augmented plane wave method (LAPW) within the local spin density approximation (LSDA), including spin–orbit coupling (SOC) and Hubbard model parameter (U). DOS analysis of both Gd-Al and Gd-Co systems reveals a strong correlation between exchange splitting energy and T C . The Gd-Co system exhibits an enormous exchange splitting energy among Co-3d electrons, vastly overwhelming the vanishing Gd 5d exchange splitting. Finally, these findings suggest that exchange splitting of Co-3d electrons plays a key role in the ground state magnetism and magnetic transition temperatures in these materials.

36 MATERIALS SCIENCE↗

Light scattering study of highly absorptive, non-fractal, hematite aggregates

In this paper, we present measurements of the scattered light intensity by aerosolized hematite aggregate particles. The measurements were made at a wavelength of 532 nm in the scattering angle range from 0.32° to 157°. Hematite has high values of the real and imaginary parts of the refractive index m = n + iκ = 3 + i0.5 at the studied wavelength. Scanning electron micrographs (SEM) indicated that the particles were aggregates whereas the optical microscope pictures showed that the aerosol had a bimodal distribution with effective mean diameters of roughly 1 and 10 µm. This is consistent with the light scattering results which displayed two Guinier regimes. The aggregates were composed of smaller grains with an approximate size of 200 nm. Ultra Small-Angle X-ray Scattering (USAXS) indicate that the aggregates were uniform and non-fractal. Mie calculations for a sphere equivalent to the aggregate size were compared to the experimentally observed results. The observed results showed an enhanced backscattering, whereas the Mie calculations did not due to the large imaginary part of the refractive index. Hematite aggregates were simulated by assuming they were composed of spherical monomers inside a spherical volume. Then the light scattering was calculated using the T-matrix method for these simulated aggregates. The calculated results show an enhanced backscattering. We present a dimensional analysis to estimate the extent of multiple scattering within the aggregate and find a correlation between the average number of scattering events within the aggregate and the enhancement in the backscattering.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Site specific porosity-thermal performance correlations in neutron irradiated U-10Zr fuel

In this work, we present a site-specific three-dimensional analysis of porosity evolution in neutron-irradiated U–10Zr metallic fuel using high-resolution synchrotron X-ray tomography. Focused ion beam cubic lift-outs from four radial positions—fuel center, middle, edge, and fuel-cladding interaction (FCCI) zones—were imaged, reconstructed, and segmented to quantify pore volume, density, morphology, and pore connectivity. Porosity increased modestly from 5.5% at the center to 10.5% at the edge, yet pore number density increased by over two orders of magnitude in the fuel portion near the FCCI interface (from 4.8 x 10 4 to 6.0 x 10 6 pores/mm 3 ). Morphological classification revealed a progression from small spherical pores at the center to equiaxed and tortuous networks at the periphery, with enhanced orientation along the radial direction. Connectivity and permeability analysis reveal that the FCCI region maintains dense, highly interconnected pores despite a moderate volume fraction, enabling rapid fission gas transport and lanthanide migration. Effective thermal conductivity models incorporating sodium logging confirm that these site-specific pore features critically influenced heat transport during reactor irradiation. These findings demonstrate that pore topology—not just porosity fraction—controls thermal performance and thermal pathways in U–10Zr fuels, impacting fuel thermal performance in a reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Protective effect of SIRT6 on cholesterol crystal-induced endothelial dysfunction via regulating ACE2 expression

Highlights: • ACE2 was involved in CC-induced endothelial dysfunction. • SIRT1 and SIRT6 contributed to regulating the protein expression of ACE2 in CC-stimulated endothelial cells. • SIRT6 regulated ACE2 with intranuclear p-ATF2, but not affecting p-ATF2 expression in the cytoplasm. Sirtuins are a family of highly conserved nicotinamide adenine dinucleotide (NAD{sup +})-dependent enzymes. Among the sirtuins, SIRT1 and SIRT6 participate in the regulation of endothelial functions and play significant roles in the physiological and pathological processes of cardiovascular diseases (CVD). Recently, our study found that minute cholesterol crystals (CC) can be endocytosed by endothelial cells and further impair endothelial functions. Since previous studies have reported that angiotensin-converting enzyme (ACE2) involves Angiotensin (Ang) II-induced inflammation in endothelial cells, this study was designed to investigate the role of SIRT1 and SIRT6 in CC-induced variation of ACE2 expression and the related mechanism between SIRT6 and ACE2. We found that ACE2 is involved in CC-induced endothelial dysfunction, which inhibits decreases in nitric oxide (NO) level and endothelial nitric oxide synthase (eNOS) activity and increases in inflammatory factors and adhesion molecules. Besides, SIRT1 and SIRT6 regulated the protein expression of ACE2 in CC-stimulated human umbilical vein endothelial cells (HUVECs). Moreover, bioinformatics analysis from the Enrichr database indicated that activating transcription factor 2 (ATF2), is highly correlated with genes that significantly upregulated after infection with the SIRT6 adenovirus vector. In CC-induced HUVECs, ACE2 expression was up-regulated in cells transfected with ATF2 siRNA. However, further mechanism studies revealed that overexpression of SIRT6 decreases the accumulation of p-ATF2 in the nucleus, but did not affect p-ATF2 expression in the cytoplasm. Taken together, these data indicated that SIRT6 regulates ACE2 might via inhibiting the accumulation of nucleus p-ATF2 in CC-induced endothelial dysfunction.

60 APPLIED LIFE SCIENCES↗

CO 2 Capture Characteristics of Hyperbranched Poly(alkylene imine): A Molecular Dynamics Simulation Approach

This study explores the CO 2 capture characteristics of hyperbranched poly(ethylenimine) (HB-PEI) and poly- (propyleneimine) (HB-PPI) through molecular dynamics simulations using density functional theory-calibrated force fields. Key features such as density, free volume, glass transition temperature, CO 2 /H 2 O distribution, and molecular diffusion are systematically investigated to elucidate structure−function relationships under dry and hydrated conditions. HB-PEI demonstrates a slightly higher density and lower free volume compared to HB-PPI yet shows superior CO 2 capture due to the high amine concentration. Glass transition analysis indicates a higher thermal mobility in HBPEI, enhancing the CO 2 diffusivity. Pair correlation and coordination analyses confirm a stronger affinity of CO 2 with primary and secondary amines, particularly in hydrated environments where water competes with CO 2 for binding sites. Despite its more compact structure, HB-PEI outperformed HB-PPI in CO 2 and H 2 O transport, as confirmed by higher diffusion coefficients across all hydration levels. These findings highlight a critical balance among polymer architecture, amine accessibility, and hydration in designing next-generation solid amine sorbents for efficient direct air capture applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molten Sodium Penetration in NaSICON Electrolytes at 0.1 A cm –2

High-conductivity solid electrolytes, such as the Na superionic conductor, NaSICON, are poised to play an increasingly important role in safe, reliable battery-based energy storage, enabling advanced sodium-based batteries. Coupled demands of increased current density (≥0.1 A cm –2 ) and low-temperature (<200 °C) operation, combined with increased discharge times for long-duration storage (>12 h), challenge the limitations of solid electrolytes. Here, we explore the penetration of molten sodium into NaSICON at high current densities. Previous studies of β"-alumina proposed that Poiseuille pressure-driven cracking (mode I) and recombination of ions and electrons within the solid electrolyte (mode II) are the two main mechanisms for Na penetration, but a comprehensive study of Na penetration in NaSICON is necessary, particularly at high current density. To further understand these modes, this work employs unidirectional galvanostatic testing of Na|NaSICON|Na symmetric cells at 0.1 A cm –2 over 23 h at 110 °C. Further, while galvanostatic testing shows a relatively constant yet increasingly noisy voltage profile, electrochemical impedance spectroscopy (EIS) reveals a significant decrease in cell impedance correlated with significant sodium penetration, as observed in scanning electron microscopy (SEM). Further SEM analysis of sodium accumulation within NaSICON suggests that mode II failure may be far more prevalent than previously considered. Further, these findings suggest that total (dis)charge density (mAh cm –2 ), as opposed to current density (mA cm –2 ), may be a more critical parameter when examining solid electrolyte failure, highlighting the challenge of achieving long discharge times in batteries using solid electrolytes. Together, these results provide a better understanding of the limitations of NaSICON solid electrolytes under high current and emphasize the need for improved electrode–electrolyte interfaces.

25 ENERGY STORAGE↗

Nowcasting Earthquakes: Imaging the Earthquake Cycle in California With Machine Learning

We propose a new machine learning-based method for nowcasting earthquakes to image the time-dependent earthquake cycle. The result is a timeseries that may correspond to the process of stress accumulation and release. The timeseries are constructed by using principal component analysis of regional seismicity. The patterns are found as eigenvectors of the cross-correlation matrix of a collection of seismicity timeseries in a coarse grained regional spatial grid (pattern recognition via unsupervised machine learning). The eigenvalues of this matrix represent the relative importance of the various eigenpatterns. Using the eigenvectors and eigenvalues, we compute the weighted correlation timeseries of the regional seismicity. This timeseries has the property that the weighted correlation generally decreases prior to major earthquakes in the region, and increases suddenly just after a major earthquake occurs. As in a previous paper, we find that this method produces a nowcasting timeseries that resembles the hypothesized regional stress accumulation and release process characterizing the earthquake cycle. We then address the problem of whether the timeseries contain information regarding future large earthquakes. For this, we compute a receiver operating characteristic and determine the decision thresholds for several future time periods of interest (optimization via supervised machine learning). We find that signals can be detected that can be used to characterize the information content of the timeseries. These signals may be useful in assessing present and near-future seismic hazards.

58 GEOSCIENCES↗

Machine-learning-accelerated multimodal characterization and multiobjective design optimization of natural porous materials

Natural porous materials such as nanoporous clays are used as green and low-cost adsorbents and catalysts. The key factors determining their performance in these applications are the pore morphology and surface activity, which are typically represented by properties such as specific surface area, pore volume, micropore content and pH. The latter may be modified and tuned to specific applications through material processing and/or chemical treatment. Characterization of the material, raw or processed, is typically performed experimentally, which can become costly especially in the context of tuning of the properties towards specific application requirements and needing numerous experiments. In this work, we present an application of tree-based machine learning methods trained on experimental datasets to accelerate the characterization of natural porous materials. The resulting models allow reliable prediction of the outcomes of experimental characterization of processed materials (R2 from 0.78 to 0.99) as well as identification of key factors contributing to those properties through feature importance analysis. Furthermore, the high throughput of the models enables exploration of processing parameter–property correlations and multiobjective optimization of prototype materials towards specific applications. We have applied these methodologies to pinpoint and rationalize optimal processing conditions for clays exploitable in acid catalysis. One of such identified materials was synthesized and tested revealing appreciable acid character improvement with respect to the pristine material. Specifically, it achieved 79% removal of chlorophyll-a in acid catalyzed degradation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Constraints on primordial non-Gaussianity from the cross-correlation of DESI luminous red galaxies and Planck CMB lensing

We use the angular cross-correlation between a luminous red galaxy (LRG) sample from the Dark Energy Spectroscopic Instrument (DESI) Legacy Survey data release DR9 and the Planck cosmic microwave background (CMB) lensing maps to constrain the local primordial non-Gaussianity parameter, f NL , using the scale-dependent galaxy bias effect. The galaxy sample covers approximately 40% of the sky, contains galaxies up to redshift z ∼ 1.4, and is calibrated with the LRG spectra that have been observed for DESI Year 1 (Y1). We apply a nonlinear imaging systematics treatment based on neural networks to remove observational effects that could potentially bias the f NL measurement. Our measurement is performed without blinding, but the full analysis pipeline is tested with simulations including systematics. Using the two-point angular cross-correlation between LRG and CMB lensing only, we find f NL = 39 −38 +40 at the 68% confidence level, and our result is robust in terms of systematics and cosmological assumptions. If we combine this information with the autocorrelation of LRG, applying a scale cut to limit the impact of systematics, we find f NL = 24 −21 +20 at the 68% confidence level. Our results motivate the use of CMB lensing cross-correlations to measure f NL with future datasets, given its stability in terms of observational systematics compared to the angular autocorrelation. Furthermore, performing accurate systematics mitigation is crucially important in order to achieve competitive constraints on f NL from CMB lensing cross-correlation in combination with the tracers’ autocorrelation.

79 ASTRONOMY AND ASTROPHYSICS↗

Exact restoration of Galilei invariance in density functional calculations with quantum Monte Carlo

We investigate some aspects of the connection between mean-field and ab-initio calculations for any-nucleon systems employing the Gogny effective interaction. In particular, we present variational Monte Carlo calculations of 4 He and 16 O, for which we extended the formalism of the linear method to the case of a density-dependent Hamiltonian. Monte Carlo calculations using an uncorrelated basis reduce to Hartree-Fock ones, but Galilean invariance can be preserved, contrary to the usual treatment. An analysis of the results obtained with the Gogny force when used in conjunction with correlated wave functions has also been performed. Here, the calculations show the collapse of the deuteron, leading to a set of unphysical predictions for the structure of heavier nuclei. This behavior remarks the different role of the Gogny effective interaction as compared to bare interactions typically used in fully microscopic calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

An analysis of parameter compression and Full-Modeling techniques with Velocileptors for DESI 2024 and beyond

In anticipation of forthcoming data releases of current and future spectroscopic surveys, we present the validation tests and analysis of systematic effects within velocileptors modeling pipeline when fitting mock data from the AbacusSummit N-body simulations. We compare the constraints obtained from parameter compression methods to the direct fitting (Full-Modeling) approaches of modeling the galaxy power spectra, and show that the ShapeFit extension to the traditional template method is consistent with the Full-Modeling method within the standard ΛCDM parameter space. We show the dependence on scale cuts when fitting the different redshift bins using the ShapeFit and Full-Modeling methods. We test the ability to jointly fit data from multiple redshift bins as well as joint analysis of the pre-reconstruction power spectrum with the post-reconstruction BAO correlation function signal. We further demonstrate the behavior of the model when opening up the parameter space beyond ΛCDM and also when combining likelihoods with external datasets, namely the Planck CMB priors. Finally, we describe different parametrization options for the galaxy bias, counterterm, and stochastic parameters, and employ the halo model in order to physically motivate suitable priors that are necessary to ensure the stability of the perturbation theory.

79 ASTRONOMY AND ASTROPHYSICS↗

Characterization of damage processes in Montney siltstone under triaxial compression using acoustic emission and diagnostic imaging

SUMMARY Crack nucleation and rock failure processes in a fine-grained siltstone (Montney Formation) under triaxial compression are investigated using combined diagnostic techniques, including ultrasonic-wave measurement, acoustic-emission (AE) monitoring, computed tomography (CT) scanning, and thin-section imaging. The sample displays a weak-to-moderate inherent seismic anisotropy and noticeable stress-induced anisotropy prior to failure. No AE event was detected until the applied axial stress reached 95 per cent of the peak value. The signal-to-noise ratio is relatively low, however, and detectable AE events are more diffuse than those observed in highly brittle rocks. The AE locations correlate with a shear fracture zone imaged by CT scanning. AE moment-tensor analysis reveals that events with larger relative magnitudes are characterized by high volumetric (tensile or compressive) components, and the initiation of the failure zone is dominated by combined shear-tensile (ST) failure. Stress inversion of the AE events with high tensile components is in good agreement with the known applied stress. Microscopic imaging of thin sections from the failed sample shows that the failure zone is an en echelon structure consisting of a major fracture with branching micro and minor cracks. This failure mechanism is consistent with a ST source mechanism and is interpreted to be associated with the fine granular structure and mineral composition of Montney siltstone.

Jia, Suzie Q. (ORCID:0000000326496190)↗

Self-calibrating optical galaxy cluster selection bias using cluster, galaxy, and shear cross-correlations

ABSTRACT The clustering signals of galaxy clusters are powerful tools for self-calibrating the mass–observable relation and are complementary to cluster abundance and lensing. In this work, we explore the possibility of combining three correlation functions – cluster lensing, the cluster–galaxy cross-correlation function, and the galaxy autocorrelation function – to self-calibrate optical cluster selection bias, the boosted clustering and lensing signals in a richness-selected sample mainly caused by projection effects. We develop mock catalogues of redMaGiC-like galaxies and redMaPPer-like clusters by applying halo occupation distribution models to N-body simulations and using counts-in-cylinders around massive haloes as a richness proxy. In addition to the previously known small-scale boost in projected correlation functions, we find that the projection effects also significantly boost three-dimensional correlation functions to scales of 100 $h^{-1} \, \rm Mpc$. We perform a likelihood analysis assuming survey conditions similar to the Dark Energy Survey and show that the selection bias can be self-consistently constrained at the 10 per cent level. We discuss strategies for applying this approach to real data. We expect that expanding the analysis to smaller scales and using deeper lensing data would further improve the constraints on cluster selection bias.

Astronomy & Astrophysics↗

Singlet magnetism in intermetallic UGa 2 unveiled by inelastic x-ray scattering

Using high resolution tender x-ray resonant inelastic scattering and hard x-ray nonresonant inelastic scattering beyond the dipole limit we were able to detect electronic excitations in intermetallic UGa 2 that are highly atomic in nature. Analysis of the spectral lineshape reveals that the local 5⁢ƒ 2 configuration characterizes the correlated nature of this ferromagnet. The orientation and directional dependence of the spectra indicate that the ground state is made of the Γ 1 singlet and/or Γ 6 doublet symmetry. With the ordered moment in the ab plane, we infer that the magnetism originates from the higher lying Γ 6 doublet being mixed with the Γ 1 singlet due to intersite exchange, qualifying UGa 2 to be a true quantum magnet. The ability to observe atomic excitations is crucial to resolve the ongoing debate about the degree of localization versus itineracy in U intermetallics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A = 3 ( e , e ' ) x B ≥ 1 cross-section ratios and the isospin structure of short-range correlations

We study the relation between measured high-x B , high-Q 2 , helium-3 to tritium, (e,e') inclusive-scattering cross-section ratios and the relative abundance of high-momentum neutron-proton (np) and proton-proton (pp) short-range correlated (SRC) nucleon pairs in three-body (A=3) nuclei. In this study, analysis of this data using a simple pair-counting cross-section model suggested a much smaller np/pp ratio than previously measured in heavier nuclei, questioning our understanding of A=3 nuclei and, by extension, all other nuclei. Here we examine this finding using spectral-function-based cross-section calculations, with both an ab initio A=3 spectral function and effective Generalized Contact Formalism (GCF) spectral functions using different nucleon-nucleon interaction models. The ab initio calculation agrees with the data, showing good understanding of the structure of A=3 nuclei. An 8% uncertainty on the simple pair-counting model, as implied by the difference between it and the ab initio calculation, gives a factor of 5 uncertainty in the extracted np/pp ratio. Thus we see no evidence for the claimed "unexpected structure in the high-momentum wavefunction for hydrogen-3 and helium-3."

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Evidence of Quadrupole and Octupole Deformations in Zr 96 + Zr 96 and Ru 96 + Ru 96 Collisions at Ultrarelativistic Energies

In the hydrodynamic model description of heavy-ion collisions, the elliptic flow v 2 and triangular flow v 3 are sensitive to the quadrupole deformation β 2 and octupole deformation β 3 of the colliding nuclei. The relations between v n and β n have recently been clarified and were found to follow a simple parametric form. The STAR Collaboration has just published precision v n data from isobaric Ru 96 + Ru 96 and Zr 96 + Zr 96 collisions, where they observe large differences in central collisions v 2 , Ru > v 2 , Zr and v 3 , Ru < v 3 , Zr . Using a transport model simulation, we show that these orderings are a natural consequence of $\beta_{2,Ru} \gg \beta_{2,Zr}$ and $\beta_{3,Ru} \ll \beta_{3,Zr}$ We reproduce the centrality dependence of the v 2 ratio qualitatively and v 3 ratio quantitatively and extract values of β 2 and β 3 that are consistent with those measured at low-energy nuclear structure experiments. STAR data provide the first direct evidence of strong octupole correlations in the ground state of Zr 96 in heavy-ion collisions. Our analysis demonstrates that flow measurements in high-energy, heavy-ion collisions, especially using isobaric systems, are a new precision tool to study nuclear structure physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Dark energy survey: Modeling strategy for multiprobe cluster cosmology and validation for the full six-year dataset

Here, we introduce an updated To&Krause2021 model for joint analyses of cluster abundances and large-scale two-point correlations of weak lensing and galaxy and cluster clustering (termed CL+3×2 pt analysis) and validate that this model meets the systematic accuracy requirements of analyses with the statistical precision of the final Dark Energy Survey (DES) Year 6 (Y6) dataset. The validation program consists of two distinct approaches, (i) identification of modeling and parametrization choices and impact studies using simulated analyses with each possible model misspecification and (ii) end-to-end validation using mock catalogs from customized Cardinal simulations that incorporate realistic galaxy populations and DES-Y6-specific galaxy and cluster selection and photometric redshift modeling, which are the key observational systematics. In combination, these validation tests indicate that the model presented here meets the accuracy requirements of DES-Y6 for CL+3×2 pt based on a large list of tests for known systematics. In addition, we also validate that the model is sufficient for several other data combinations: the CL+GC subset of this data vector (excluding galaxy–galaxy lensing and cosmic shear two-point statistics) and the CL+3×2 pt+BAO+SN (combination of CL+3×2 pt with the previously published Y6 DES baryonic acoustic oscillation and Y5 supernovae data).

79 ASTRONOMY AND ASTROPHYSICS↗