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At least 73 records · Page 4

Novel Zwitterionic Polyurethane-in-Salt Electrolytes with High Ion Conductivity, Elasticity, and Adhesion for High-Performance Solid-State Lithium Metal Batteries

This study presents a novel polymer-in-salt (PIS) zwitterionic polyurethane-based solid polymer electrolyte (zPU-SPE) that offers high ionic conductivity, strong interaction with electrodes, and excellent mechanical and electrochemical stabilities, making it promising for high-performance all solid-state lithium batteries (ASSLBs). The zPU-SPE exhibits remarkable lithium-ion (Li+) conductivity (3.7 × 10⁻⁴ S cm−1 at 25 °C), enabled by exceptionally high salt loading of up to 90 wt.% (12.6 molar ratio of Li salt to polymer unit) without phase separation. It addresses the limitations of conventional SPEs by combining high ionic conductivity with a Li+ transference number of 0.44, achieved through the incorporation of zwitterionic groups that enhance ion dissociation and transport. The high surface energy (338.4 J m−2) and elasticity ensure excellent adhesion to Li anodes, reducing interfacial resistance and ensuring uniform Li+ flux. When tested in Li||zPU||LiFePO₄ and Li||zPU||S/C cells, the zPU-SPE demonstrated remarkable cycling stability, retaining 76% capacity after 2000 cycles with the LiFePO4 cathode, and achieving 84% capacity retention after 300 cycles with the S/C cathode. Molecular simulations and a range of experimental characterizations confirm the superior structural organization of the zPU matrix, contributing to its outstanding electrochemical performance. The findings strongly suggest that zPU-SPE is a promising candidate for next-generation ASSLBs.

Wang, Kun

Thermal conductivity measurement of U-Mo and U-Mo/Al interaction layers generated from in-pile irradiation using the suspended-bridge method

Here, this study presents the first measurement of the individual thermal conductivity of U-7wt.%Mo fuel particles and U-Mo/Al interaction layers (ILs) from in-pile irradiated dispersion fuel plates, using the suspended-bridge method. Nanorods of U-7wt.%Mo fuel and U-Mo/Al ILs were extracted by focused ion beam (FIB), and their microstructures were characterized with transmission electron microscopy (TEM). TEM revealed finely distributed nanobubbles in the U-7wt.%Mo matrix, along with an amorphous structure in the ILs. The thermal conductivity of in-pile irradiated U-7wt.%Mo was approximately 30% lower than that of the unirradiated material, ranging from 6.7 W/m·K at 300 K to 8.5 W/m·K at 380 K. The ILs exhibited even lower thermal conductivity, from 2.1 W/m·K at 300 K to 2.7 W/m·K at 380 K. These reductions, attributed to nanobubbles, fission products, and irradiation-induced point defects, were analyzed through a combination of microstructural characterization and literature-based transport models, which successfully reproduced the observed degradation trends.

42 - ENGINEERING

Understanding Peelle’s Pertinent Puzzle bias in generalized least squares regression through eigenspectrum analysis

Certain correlation structures in the data covariance matrix (DCM) used for generalized least squares (GLS) regression can result in biased estimates, commonly known in the field of nuclear data evaluation as Peele’s Pertinent Puzzle (PPP). This article introduces a generative, forward modeling framework within which the PPP bias is characterized through an eigenspectrum analysis of the DCM. This analysis highlights the root cause of the bias, generalizes the problem beyond the nuclear data field, and provides insight to the problem regimes where it can occur. What follows is an understanding that the bias can show up for any experimental neutron time-of-flight data for which systematic uncertainties have been quantified. Lastly, a discussion of the adaptation of cross validation approaches that require pre-whitening to incorporate the known ‘fix’ to the PPP bias in the GLS estimator.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Variance reduction in lattice QCD observables via normalizing flows

Normalizing flows can be used to construct unbiased, reduced-variance estimators for lattice field theory observables that are defined by a derivative with respect to action parameters. This work implements the approach for observables involving gluonic operator insertions in the SU(3) Yang-Mills theory and two-flavor QCD in four space-time dimensions. Variance reduction by factors of 10–60 is achieved in glueball correlation functions and in gluonic matrix elements related to hadron structure, with demonstrated computational advantages. The observed variance reduction is found to be approximately independent of the lattice volume, so volume transfer can be utilized to minimize training costs.

Abbott, Ryan [Columbia U.; MIT, Cambridge, CTP; IA

Scalable Tensor Methods for Nonuniform Hypergraphs

While multilinear algebra appears natural for studying the multiway interactions modeled by hypergraphs, tensor methods for general hypergraphs have been stymied by theoretical and practical barriers. A recently proposed adjacency tensor is applicable to nonuniform hypergraphs, but is prohibitively costly to form and analyze in practice. We develop tensor times same vector (TTSV) algorithms for this tensor which improve complexity from $O(n^r)$ to a low-degree polynomial in $r$, where $n$ is the number of vertices and $r$ is the maximum hyperedge size. Our algorithms are implicit, avoiding formation of the order $r$ adjacency tensor. Here, we demonstrate the flexibility and utility of our approach in practice by developing tensor-based hypergraph centrality and clustering algorithms. We also show these tensor measures offer complementary information to analogous graph-reduction approaches on data, and are also able to detect higher-order structure that many existing matrix-based approaches provably cannot.

97 MATHEMATICS AND COMPUTING

Detailed Method for the Purification of Rhamnogalacturonan-I (RG-I) in Arabidopsis thaliana

The plant cell wall is a dynamic and complex extracellular matrix that not only provides structural integrity and determines cell shape but also mediates intercellular communication. Among its major components, pectins play essential roles in cell adhesion, wall porosity, hydration, and flexibility. Rhamnogalacturonan-I (RG-I), a structurally diverse pectic polysaccharide, remains one of the least understood components of the plant cell wall. Its backbone is substituted with arabinan, galactan, and arabinogalactan side chains that vary in length, branching, and composition across tissues, species, and developmental stages. In addition, RG-I can undergo modifications such as backbone acetylation, further contributing to its structural complexity and functional diversity. To advance understanding of RG-I, we present a detailed method for isolating RG-I from the model plant Arabidopsis thaliana . Leveraging Arabidopsis as a model system provides major advantages owing to its well-characterized genome and powerful molecular toolkit, enabling deeper investigation into the roles of RG-I in plant development and responses to environmental stress. Our method consists of two major steps: an initial chemical extraction using oxalate, followed by endo-polygalacturonase (EPG) digestion to fragment the pectic domains. An advantage of this approach is that it produces a dry material that can be stored at room temperature without special handling and does not introduce chemicals that may interfere with downstream analyses. The purified RG-I can be used for detailed compositional and structural analyses, as well as for functional studies of enzymes involved in pectin biosynthesis, modification, and degradation. Although this protocol was developed for isolating RG-I from Arabidopsis rosette leaves, it is also applicable to other Arabidopsis organs and other plant species.

25 ENERGY STORAGE

Constraining Hamiltonians from chiral effective field theory with neutron-star data

Multi-messenger observations of neutron stars (NSs) and their mergers have placed strong constraints on the dense-matter equation of state (EOS). The EOS, in turn, depends on microscopic nuclear interactions that are described by nuclear Hamiltonians. These Hamiltonians are commonly derived within chiral effective field theory (EFT). Ideally, multi-messenger observations of NSs could be used to directly inform our understanding of EFT interactions, but such a direct inference necessitates millions of model evaluations. This is computationally prohibitive because each evaluation requires us to calculate the EOS from a Hamiltonian by solving the quantum many-body problem with methods such as auxiliary-field diffusion Monte Carlo (AFDMC), which provides very accurate and precise solutions but at a significant computational cost. Additionally, we need to solve the stellar structure equations for each EOS which further slows down each model evaluation by a few seconds. In this work, we combine emulators for AFDMC calculations of neutron matter, built using parametric matrix models, and for the stellar structure equations, built using multilayer perceptron neural networks, with the PyCBC data-analysis framework to enable a direct inference of coupling constants in an EFT Hamiltonian using multi-messenger observations of NSs. We find that astrophysical data can provide informative constraints on two-nucleon couplings despite the high densities probed in NS interiors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Gluonic Structure from Instantons

The instanton vacuum provides an effective description of chiral symmetry breaking by local topological fluctuations of the gauge fields, as observed in lattice QCD simulations. The resulting effective dynamics at momenta below 1/$\bar{ρ}$ ≈ 0.6 GeV explains the basic features of light-quark correlation functions and is used extensively in studies of hadron structure. The instanton fields also make definite contributions to the gluonic structure of light hadrons, as expressed in the matrix elements of composite quark– gluon or gluon operators. The article reviews the gluonic structure of light hadrons (nucleon, pion) induced by instantons. This includes: (i) twist-2 parton distributions and momentum sum rule; (ii) twist-3 angular momentum and spin-orbit interactions; (iii) twist-3 and twist-4 quark–gluon correlations and power corrections; (iv) trace anomaly and hadron mass decomposition; (v) scalar gluon form factors and mechanical properties; (vi) axial anomaly and pseudoscalar gluon form factors. It also discusses possible further applications of the methods and recent developments including gauge field configurations beyond instantons.

Weiss, C. [Thomas Jefferson National Accelerator F

A flexible class of priors for orthonormal matrices with basis function-specific structure

Statistical modeling of high-dimensional matrix-valued data motivates the use of a low-rank representation that simultaneously summarizes key characteristics of the data and enables dimension reduction. Low-rank representations commonly factor the original data into the product of orthonormal basis functions and weights, where each basis function represents an independent feature of the data. However, the basis functions in these factorizations are typically computed using algorithmic methods that cannot quantify uncertainty or account for basis function correlation structure a priori. While there exist Bayesian methods that allow for a common correlation structure across basis functions, empirical examples motivate the need for basis function-specific dependence structure. We propose a prior distribution for orthonormal matrices that can explicitly model basis function-specific structure. The prior is used within a general probabilistic model for singular value decomposition to conduct posterior inference on the basis functions while accounting for measurement error and fixed effects. We discuss how the prior specification can be used for various scenarios and demonstrate favorable model properties through synthetic data examples. Finally, we apply our method to two-meter air temperature data from the Pacific Northwest, enhancing our understanding of the Earth system’s internal variability.

97 MATHEMATICS AND COMPUTING

Interface Evolutionand Long-Term Performance of NegativeCarbon Fiber Structural Electrodes

Abstract Laminated structural batteries present a transformative solution to reducing weight constraints in electric vehicles. These structural batteries are based on a multifunctional material that incorporates an energy storage function within a carbon fiber-reinforced polymer. Despite the potential of this technology, the intricate morphology of fiber–matrix or electrode–electrolyte interfaces and the impact of long-term cycling at low current rates (C-rates) on these interfaces remain insufficiently understood. This study addresses these critical knowledge gaps by examining the influence of matrix composition on the long-term electrochemical performance of structural battery electrodes and exploring advanced techniques to investigate carbon fiber–matrix interfaces. Localized imaging and X-ray scattering techniques were used to characterize morphological changes at the electrode–electrolyte interfaces by analyzing negative structural electrodes. The findings revealed that the matrix composition influences long-term electrochemical behavior and fiber–matrix interface formation. While the intrinsic properties of carbon fibers largely remain unaffected by long-term cycling, cycling promotes debonding at fiber–matrix interfaces. Nonetheless, residual regions of adhesion persist, underscoring the potential for preserving multifunctionality even under prolonged cycling conditions. These insights advance the understanding of interface dynamics, which is critical for optimizing structural battery technologies.

Chemistry

Visualizing Crystallization Dynamics and Transformation Pathways of Disordered Rocksalt Oxides During Thermally Activated Sol–Gel Synthesis

Sol–gel synthesis is a wet-chemical processing route for fabricating functional materials with control over composition and microstructure at relatively low temperatures compared to conventional solid-state synthesis. While sol–gel process initiates with intermixed molecular precursors, the early-stage nucleation pathways are insufficiently understood. Here, in this study, the chemical and structural transformation of ion disordered rocksalt (DRX) Li 1.2 Mn 0.4 Ti 0.4 O 2 (LMTO), a promising cathode material for lithium batteries, is studied by multiscale characterizations. In situ heating transmission electron microscopy (TEM) using a liquid cell visualizes and identifies crystallization pathways at the nanoscale. While some regions follow a classical multi-step transition through thermodynamically stable intermediates, others exhibit a kinetic shortcut via a localized amorphous matrix to directly form the DRX structure. Macroscale Fourier transform infrared spectroscopy corroborates the findings and reveals that transition metal ions are more strongly incorporated into the acetate-coordinated network than lithium. Although in situ heating TEM captures diverse local transformation pathways, in situ synchrotron X-ray diffraction indicates that the macroscopic transformation proceeds predominantly through spinel LMTO and lithium titanates toward DRX-LMTO. The findings uncover the spatiotemporal chemical and structural transformations in sol–gel derived DRX-LMTO materials, and call for fine-tuning of such sol–gel chemistries to manipulate the crystallization pathways and achieve target material homogeneity more efficiently.

cathode material

Microstructure of Neutron-Irradiated Al 3 Hf-Al Thermal Neutron Absorber Materials

A thermal neutron-absorbing metal matrix composite (MMC) comprised of Al 3 Hf particles in an aluminum matrix was developed to filter out thermal neutrons and create a fast flux environment for material testing in a mixed-spectrum nuclear reactor. Intermetallic Al 3 Hf particles capture thermal neutrons and are embedded in a highly conductive aluminum matrix that provides conductive cooling of the heat generated due to thermal neutron capture by the hafnium. These Al 3 Hf-Al MMCs were fabricated using powder metallurgy via hot pressing. The specimens were neutron-irradiated to between 1.12 and 5.38 dpa and temperatures ranging from 286 °C to 400 °C. The post-irradiation examination included microstructure characterization using transmission electron microscopy (TEM) and energy-dispersive X-ray spectroscopy. This study reports the microstructural observations of four irradiated samples and one unirradiated control sample. All the samples showed the presence of oxide at the particle–matrix interface. The irradiated specimens revealed needle-like structures that extended from the surface of the Al 3 Hf particles into the Al matrix. An automated segmentation tool was implemented based on a YOLO11 computer vision-based approach to identify dislocation lines and loops in TEM images of the irradiated Al-Al 3 Hf MMCs. This work provides insight into the microstructural stability of Al 3 Hf-Al MMCs under irradiation, supporting their consideration as a novel neutron absorber that enables advanced spectral tailoring.

36 MATERIALS SCIENCE

Hierarchically Structured Vitrimer Biocomposites for Sustainable Manufacturing

Polymers containing dynamic covalent bonds (DCBs) exhibit thermoplastic-like flow above their topology freezing temperature (T v ) while maintaining thermoset-like properties below it, making them promising for sustainable manufacturing. However, their large-scale adoption remains limited due to challenges in accurately determining T v and achieving efficient fiber-matrix bonding in composite applications. Here, hierarchically structured epoxy-anhydride-based polyester vitrimer composites reinforced with cellulosic filaments is demonstrated, where hydroxyl groups on fiber surfaces participate directly in transesterification with the matrix. Further, this dynamic interfacial bonding delivers exceptional mechanical properties, including ≈70 MPa shear strength and >10% strain-to-failure, while enabling thermal malleability. Using a combination of nuclear magnetic resonance and nano-infrared spectroscopies, direct evidence is provided that chemical bond exchange begins well below the conventionally measured T v , supporting the hypothesis that rheologically determined T v reflects a combination of chemical exchange and frictional dynamics rather than a discrete transition. The composites demonstrate excellent processability through vacuum-assisted resin transfer molding and maintain >90% of their mechanical properties after multiple thermal reforming cycles. These findings advance both the fundamental understanding of vitrimeric transitions and the practical development of sustainable, high-performance composite materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Solving a class of infinite-dimensional tensor eigenvalue problems by translational invariant tensor ring approximations

Here, we examine a method for solving an infinite-dimensional tensor eigenvalue problem Hx = λx, where the infinite-dimensional symmetric matrix H exhibits a translational invariant structure. We provide a formulation of this type of problem from a numerical linear algebra point of view and describe how a power method applied to e -Ht is used to obtain an approximation to the desired eigenvector. This infinite-dimensional eigenvector is represented in a compact way by a translational invariant infinite Tensor Ring (iTR). Low rank approximation is used to keep the cost of subsequent power iterations bounded while preserving the iTR structure of the approximate eigenvector. We show how the averaged Rayleigh quotient of an iTR eigenvector approximation can be efficiently computed and introduce a projected residual to monitor its convergence. In the numerical examples, we illustrate that the norm of this projected iTR residual can also be used to automatically modify the time step to ensure accurate and rapid convergence of the power method.

97 MATHEMATICS AND COMPUTING

Development of alpha cluster structure in nuclei of the same mass number

The resonant 14 N+α particle scattering was studied in the 18 F excitation region from 6.5 to 9 MeV at Astana cyclotron using the TTIK approach. The excitation functions for the elastic 14 N+α scattering were analyzed in the framework of R-matrix approach. The observed strong alpha cluster structure in 18 F is compared with that in 18 O.

Nurmukhanbetova, Aliya

3D printed water-stable Cd-doped Cs 4 MnBi 2 Cl 12 /polylactic acid perovskite/polymer composites for high-flux X-ray scintillation

Stable and efficient X-ray scintillators are crucial for medical diagnostics, industrial, and defense applications. However, conventional scintillator technologies face a trade-off between stability, optimal performance, and sustainability. Herein, we introduce 3D-printed Cs 4 MnBi 2 Cl 12 (Pero1) and Cs 4 Cd 0.68 Mn 0.32 Bi 2 Cl 12 (Pero2) perovskite microcrystals embedded within a polylactic acid (PLA) polymer composite as X-ray scintillators, combining efficiency, stability, and sustainability. The orange luminescent perovskite powder phosphors exhibited poor water stability, which was successfully addressed through incorporation into PLA via filament extrusion and fused deposition modeling (FDM) 3D printing. The resulting composite films demonstrated remarkable water stability while maintaining uniform orange emission throughout the polymer matrix, as confirmed by 3D topography scanning and X-ray fluorescence mapping. Structural characterization revealed minimal chemical interaction between the perovskite and PLA matrix, with the composites retaining their crystalline properties. The PLA-Pero2 composite exhibited superior optical properties, with a photoluminescence quantum yield of 47%, nearly 17 times higher than that of PLA-Pero1 (2.8%), attributed to the effective suppression of non-radiative decay pathways through Cd 2+ doping. Under hard X-ray irradiation at synchrotron beamlines, both composites exhibited excellent radioluminescence, with emission peaks at 605 nm, a linear response across a wide X-ray flux range, and remarkable radiation stability, showing less than 3% intensity degradation after 600 seconds of continuous high-dose exposure. The PLA-Pero2 composite achieved a spatial resolution of 5 line pairs per millimeter and a contrast ratio of 0.255. These performance metrics, combined with the polymer's biodegradability and scalability through additive manufacturing, position PLA-based composites as a more sustainable alternative to conventional petroleum-based polymer scintillators for next-generation medical imaging, radiation monitoring, and industrial radiography applications.

3D Printing

Effects of high-pressure hydrogen exposure on filler-elastomer adhesion

Elastomers are known to gain enhanced mechanical properties through compounding with nanosized filler particles such as silica or carbon black. Filler dispersion and filler-polymer interfacial strength are key contributing factors to this improvement. The interfacial strength is critical to part lifetime in pressurized gas sealing applications such as O-rings, where weak binding between the filler particle and polymer matrix can lead to internal void structures. With the aim to build a fundamental understanding of precursors to pressurized hydrogen-induced failure in elastomers, we use all-atom molecular dynamics simulations to study the impact of hydrogen oversaturation on filler-polymer interaction strength. We systematically study the interface between a commonly used elastomer, ethylene-propylene-diene monomer (EPDM) and silica by varying gas concentration, crosslink density, and surface chemistry. Our simulations predict that decompression leads to a localization of excess gas near the interface. In conclusion, we demonstrate that this localized gas can weaken interfacial adhesion and quantify the interaction using thermodynamic approaches.

EPDM