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At least 55 records · Page 3

Computational prediction of dielectric breakdown strength of a transformer paper in oil with uncertainty quantification

The determination of the dielectric breakdown strengths of microstructurally heterogeneous materials has been a primarily experimental endeavor. We report the development of a microstructure-level model for computationally predicting the breakdown strength and analyzing the interactions between electromagnetic pulses (EMP) and the constituents in a composite of cellulose-based paper and mineral oil found in electrical transformers. The model allows explicit simulation of the material breakdown process by tracking the transition of dielectric constituents from non-conductive to conductive states. The focus is on the electric fields induced in the materials and the overall conditions for dielectric breakdown (defined as the onset of avalanche) caused by the electric field induced in the composite. Responses to three distinct pulse shapes, i.e., Steep Front (SF), Lightning (L), and AC with spectra spanning 60–9 × 105 Hz are considered. It is found that the breakdown strength of the material is significantly affected by microstructure heterogeneities, the spatial variations of the constituent properties, and the pulse shapes. A probabilistic characterization of the breakdown strength is computationally obtained and compared with experimental measurements. Although one particular material is analyzed, the model and approach are applicable to other heterogeneous materials as well.

breakdowns↗

Subsurface Spectroscopy of Thermal Degradation Inside an Inert Plastic Bonded Explosive (PBX) Simulant Using Feedback-Assisted Wavefront Shaping

We characterize the subsurface thermal degradation of an inert analog of high-explosive molecular crystals (Eu:Y(acac) 3 (DPEPO)) (EYAD) embedded inside of a plastic bonded explosive simulant using feedback-assisted wavefront shaping-based fluorescence and Raman spectroscopies. This technique utilizes wavefront shaping to focus pump light inside a heterogeneous material onto a target particle, which significantly improves its spectroscopic signature. We find that embedding the EYAD crystals in the heterogeneous polymer results in improved thermal stability, relative to bare crystal measurements, with the crystal remaining fluorescent to >612 K inside of the heterogeneous material, while the bare crystal’s fluorescence is fully quenched by 500 K. We hypothesize that this improvement is due to the polymer restricting the effects of EYAD melting, which occurs at 400 K and is the primary mechanism for spectroscopic changes in the temperature range explored.

Anderson, Benjamin R.↗

Adaptive Interface-PINNs (AdaI-PINNs) for inverse problems: Determining material properties for heterogeneous systems

Here, we determine spatially varying discontinuous material properties using a domain-decomposition based physics-informed neural networks (PINNs) framework named the Adaptive Interface-PINNs or AdaI-PINNs (Roy et al., 2024). We propose the use of distinct neural networks for the field variables and material properties within each material, utilizing adaptive activation functions. While the neural networks across different materials share the same weights and biases, their activation functions are uniquely tailored using a hyperparameter that influences the slope of the activation function. The proposed framework is tested on several one-dimensional and two-dimensional benchmark examples, and its performance is compared with conventional PINNs and existing domain-decomposition PINNs frameworks, namely, the Multi-domain physics-informed neural network (M-PINN), and the eXtended physics-informed neural networks (XPINNs). The results demonstrate that the proposed approach can determine randomly distributed discontinuous material properties with an L 2 error of $\mathscr{O}$ (10 -3 ) for the material property and the root-mean-square error of $\mathscr{O}$ (10 -3 ) for the primary variable while the other approaches yield errors that are approximately two orders of magnitude larger (that is, $\mathscr{O}$ (10 -1 )). Moreover, the spatial distribution of material properties obtained using the proposed framework is in close agreement with the true distribution, whereas the other approaches fare much worse. Additionally, the proposed approach is approximately 40% faster than its competitors, indicating its potential as a robust alternative for solving inverse problems in heterogeneous materials.

36 MATERIALS SCIENCE↗

Pressure Heterogeneity and Material Utilization in Thin-Film Solid-State Cathodes

Intimate interfacial contact between the solid electrolyte and the cathode active material is critical for maximizing cathode utilization in solid-state batteries. However, volume changes during electrochemical cycling induce internal stresses that drive interfacial degradation, particularly under nonuniform stack pressure. In this study, we employ in situ energy-dispersive X-ray diffraction tomography to visualize and quantify reaction heterogeneities across a 3 mm-diameter solid-state cathode with a well-defined interface. Our results reveal that regions under a lower stack pressure exhibit reduced material utilization and reversibility, which negatively affect the high-pressure regions. Interfacial degradation further impedes lithium-ion transport and amplifies microscale reaction heterogeneity. These findings highlight the critical role of stack pressure distribution in governing interfacial stability and electrochemical performance, offering important design insights into practical solid-state battery systems.

36 MATERIALS SCIENCE↗

High-Throughput Nanoindentation Mapping of Additively Manufactured T91 Steel

Here, this work aims to adapt nanoindentation mapping combined with a k-means algorithm as a high-throughput technique to study the nano-scale spatial changes in mechanical properties for a heterogeneous material. This technique can also classify the individual data points based on their properties. Hundreds to thousands of indents were performed on additively manufactured T91 at room temperature, 300°C, 400°C, and 500°C across a square area with a side length of 120 μm to 400 μm. From this data, the hardness and reduced modulus at each point could be calculated and mapped. Using k-means clustering, we were able to arrange the data into three or four clusters corresponding roughly to the ferritic and martensitic phases as well as one or two intermediate clusters sampling both the phases. The hardness of these two phases appears to be quite stable as a function of temperature. Nanoindentation mapping and the k-means algorithm can therefore be used to rapidly assess the feasibility of heterogeneous materials under extreme conditions, such as nuclear reactor steels.

36 MATERIALS SCIENCE↗

Heterostructure engineering in electrode materials for sodium-ion batteries: Recent progress and perspectives

Sodium-ion batteries (SIBs) have stepped into the spotlight as a promising alternative to lithium-ion batteries for large-scale energy storage systems. However, SIB electrode materials, in general, have inferior performance than their lithium counterparts because Na + is larger and heavier than Li + . Heterostructure engineering is a promising strategy to overcome this intrinsic limitation and achieve practical SIBs. We provide a brief review of recent progress in heterostructure engineering of electrode materials and research on how the phase interface influences Na + storage and transport properties. Efficient strategies for the design and fabrication of heterostructures (in situ methods) are discussed, with a focus on the heterostructure formation mechanism. The heterostructure's influence on Na + storage and transport properties arises primarily from local distortions of the structure and chemomechanical coupling at the phase interface, which may accelerate ion/electron diffusion, create additional active sites, and bolster structural stability. Finally, we offer our perspectives on the existing challenges, knowledge gaps, and opportunities for the advancement of heterostructure engineering as a means to develop practical, high-performance sodium-ion batteries.

25 ENERGY STORAGE↗

Novel X-Ray Probes of Electronically Heterogeneous Quantum Materials

The goal of this research was to advance the use of resonant soft x-ray scattering (RSXS) by deepening our theoretical understanding of the technique and expanding its use to a wide range of materials. Under this award, we showed how RSXS techniques can be applied to oxide heterostructures, studied commensuration effects in Wigner crystals, discovered a charge density wave in nickel-arsenide superconductors, and measured time-resolved dynamics of charge order in copper-oxide superconductors, among many other achievements. This award contributed to adoption of RSXS techniques by researchers around the nation and the world.

36 MATERIALS SCIENCE↗

Results of the Micromorphic Upscaling Workflow for the PSAAP III Year 3 Report

Predicting the mechanical response and failure of heterogeneous materials has proven difficult. Multiscale numerical methods based in higher order continuum theories attempt to bridge the gap between microscale and macroscale structural behavior. Micromorphic continuum theories have shown promise. The Tardigrade software package is an implementation of Eringen’s micromorphic continuum theory with capabilities to support multiscale material modeling workflows. These include homogenization through the Micromorphic Filter, calibration of micromorphic material models, and macroscale simulation in Tardigrade-MOOSE. This work discusses micromorphic upscaling efforts of the University of Colorado Boulder PSAAP III multidisciplinary simulation center (MSC). Verification studies are presented that compare the accuracy of the upscaling workflow with analytical solutions for a trivial stress state and homogeneous material using direct numerical simulations (DNS) conducted in the Ratel finite element method (FEM) and GEOS material point method (MPM) codes. These verification studies consider upscaling using the Micromorphic Filter for a “single filter domain”. Finally, DNS of a heterogeneous composite material is upscaled using a “multiple filter domain” method.

36 MATERIALS SCIENCE↗

Unequal {110} Facets: The Potential Role of Intraparticle Heterogeneity and Facet Termination in Photoelectrochemical Activity of Single BiVO 4 Particles

BiVO 4 photoanodes are promising for solar water splitting, with photogenerated electrons and holes preferentially reacting at top {010} and lateral {110} facets, respectively. However, the mechanisms driving this facet-dependent reactivity remain unclear. Here, in this study, we investigate facet-dependent photocurrent and material heterogeneity using correlative scanning photoelectrochemical microscopy (SPCM), electron beam induced current (EBIC) mapping, and mid-IR scattering scanning near-field optical microscopy (s-SNOM). SPCM measurements of 62 BiVO 4 particles confirmed higher photocurrents at lateral {110} facets compared to top {010} facets, but unexpectedly revealed variations in photocurrent among lateral facets within the same particle. Variations in lateral facet surface termination could explain the intraparticle-level reactivity heterogeneity, consistent with theoretical predictions. Nano-FTIR spectroscopy and Raman microspectroscopy indicated significant materials chemistry heterogeneity within individual particles and facets that could be attributed to variations in lattice vibration distortions that enhance the overlap between Bi 6s and O 2p orbitals. The increased orbital overlap is significant as it potentially increases hole mobility in the valence band and potentially explains the lateral facet-dependent charge separation efficiency observed in photocurrent maps. Facet-dependent electrical and EBIC measurements showed no space charge regions at interfacet junctions or metal-BiVO 4 contacts under vacuum, suggesting that photogenerated holes beneath top {010} facets are unlikely to transport to lateral {110} facets to drive water/sulfite oxidation. These findings indicate the potential influence of distinct bulk properties and surface termination chemistries across different particles and facets, highlighting the importance of carefully controlling defects and surface chemistry during sample growth to optimize photocatalytic performance.

BiVO4↗

A state-of-the-art review of experimental and computational studies of granular materials: Properties, advances, challenges, and future directions

Modeling of heterogeneous materials and media is a problem of fundamental importance to a wide class of phenomena and systems, ranging from condensed matter physics, soft materials, and composite media to porous media, biological systems, geosystems, ceramic engineering, pharmaceutical science and even in space discoveries. Among the most important materials are granular systems, which have received intense interest from the engineering, physics, and mathematics communities. In this review paper, the recent developments and new advances in experimental, and computational methods on a variety of scales and physics that extend understanding to a wide range of materials and phenomena are reviewed. Experimental advances include computed neutron and nanometer-scale tomography, magnetic resonance imaging, refractive index matching, digital image correlation, acoustic emission analysis, and the most recent 4D techniques. Furthermore, a tremendous shift has occurred from the continuum scale to micro-scale and developing multiscale approaches. As such, various computational methods, including, constitutive modeling, discrete modeling, and multiscale approaches, have been developed. In conclusion, aside from all these evolutions, more complicated modeling called coupled, or multiphysics, systems representing a simultaneous presence of heat, fluid, chemical variation, and mechanical effect are also explored.

36 MATERIALS SCIENCE↗

Learning macroscopic internal variables and history dependence from microscopic models

This paper concerns the study of history dependent phenomena in heterogeneous materials in a two-scale setting where the material is specified at a fine microscopic scale of heterogeneities that is much smaller than the coarse macroscopic scale of application. Here, we specifically study a polycrystalline medium where each grain is governed by crystal plasticity while the solid is subjected to macroscopic dynamic loads. The theory of homogenization allows us to solve the macroscale problem directly with a constitutive relation that is defined implicitly by the solution of the microscale problem. However, the homogenization leads to a highly complex history dependence at the macroscale, one that can be quite different from that at the microscale. In this paper, we examine the use of machine-learning, and especially deep neural networks, to harness data generated by repeatedly solving the finer scale model to: (i) gain insights into the history dependence and the macroscopic internal variables that govern the overall response; and (ii) to create a computationally efficient surrogate of its solution operator, that can directly be used at the coarser scale with no further modeling. We do so by introducing a recurrent neural operator (RNO), and show that: (i) the architecture and the learned internal variables can provide insight into the physics of the macroscopic problem; and (ii) that the RNO can provide multiscale, specifically FE 2 , accuracy at a cost comparable to a conventional empirical constitutive relation.

36 MATERIALS SCIENCE↗

Stabilization of Ultrasmall Platinum Nanoparticles by Nitrogen-Doped Carbon: Implications for Catalysis and Electrocatalysis

Heterogeneous materials comprising platinum nanoparticles on carbon supports have numerous applications including fuel cell electrodes and heterogeneous catalysts. The effective application of these materials for fuel cells and catalysis will be greatly advanced by the ability to control the oxidation and sintering of the nanoparticles by modifications of the carbon support. One attempt of such control has been doping carbon supports with nitrogen. Here, in this work, a cutting-edge, high-sensitivity, in situ XRD instrument, which allows observation of ultrasmall Pt nanoparticles, has been combined with in situ XPS to provide unprecedented clarity in the characterization of supported Pt nanoparticles in oxidizing and high-temperature environments. On a nitrogen-doped carbon support derived from poly-phenylporphyrin, Pt nanoparticles show increased stability to oxidation and thermal sintering. The enhanced Pt–support interaction arising from the N dopant versus the N-free carbon is manifested by (1) decreased initial Pt particle sizes, (2) small particle size at higher surface densities, (3) increased resistance of Pt nanoparticles to oxidation, (4) increased electron binding energy of Pt0, and (5) increased resistance of Pt nanoparticles to sintering. It is expected that the higher stability of Pt on NC will be manifested in higher activity in fuel cells and high-temperature catalytic reactions.

catalytic reactions↗

EFRC-MUSE: Multi-Scale Fluid-Solid Interactions in Architected and Natural Materials

Phase interactions and fluid properties in geological and other environments are critical in applications ranging from hydrogen production and geologic storage and recovery, carbon dioxide storage and sequestration, and the sustainable use of water resources. The four goals of EFRC-MUSE: Multi-Scale Fluid-Solid Interactions in Architected and Natural Materials were based on the priority directions articulated in the Basic Research Needs documents, and the scientific needs in nanoscience. 1. Develop a fundamental understanding of confinement and surface interactions in mesoscale media with nanometer-sized pores on the phase behavior, thermodynamic and multiphase flow properties of multicomponent fluid mixtures. 2. Examine the impact of mineralogy and material heterogeneity on mechanical properties to better understand chemo-mechanical interactions in material failure. 3. Determine in-operando cross-scale structural and nanostructural material properties with fluids in confinement and flow under realistic condi

58 GEOSCIENCES↗

Statistical Distributions for Mesh Independent Solutions in ALEGRA

The representation of material heterogeneity (also referred to as "spatial variation") plays a key role in the material failure simulation method used in ALEGRA. ALEGRA is an arbitrary Lagrangian-Eulerian shock and multiphysics code developed at Sandia National Laboratories and contains several methods for incorporating spatial variation into simulations. A desirable property of a spatial variation method is that it should produce consistent stochastic behavior regardless of the mesh used (a property referred to as "mesh independence"). However, mesh dependence has been reported using the Weibull distribution with ALEGRA's spatial variation method. This report describes efforts towards providing additional insight into both the theory and numerical experiments investigating such mesh dependence. In particular, we have implemented a discrete minimum order statistic model with properties that are theoretically mesh independent.

36 MATERIALS SCIENCE↗

Time-domain thermoreflectance

Time-domain thermoreflectance (TDTR) has been instrumental in measuring the heat transfer properties of bulk and nanostructured materials over the past two decades. In this Primer, we describe the optical and thermal aspects of TDTR, with an in-depth discussion on the theory, apparatus design and implementation. We present examples that illustrate the ability of TDTR to measure thermal conductivity tensors, thermal conductance across material interfaces, and volumetric heat capacity of thin films, 2D materials and bulk materials. The ability of TDTR to spatially resolve thermal properties is useful for studying heterogeneous material systems, such as materials processed in or subjected to extreme environments. We consider current limitations of pump–probe metrologies and discuss recent advancements of TDTR, such as time-resolved magneto-optic Kerr effect (TR-MOKE), beam-offset TDTR/TR-MOKE, steady-state thermoreflectance, frequency-domain thermoreflectance and laser-flash TDTR. Lastly, we present an outlook on anticipated technological developments to further expand the ability of TDTR to measure nanoscale thermal properties.

42 ENGINEERING↗

Single-Molecule Fluorescence Investigations of Solute Transport Dynamics in Nanostructured Membrane Separation Materials

Many materials used for membrane separations comprise of nanoscale structures such as pores and domains. Such nanostructures often control the solute permeability and selectivity of separation membranes. Thus, for future development of highly efficient separation membranes, it is important to understand the structural and chemical properties of these nanostructures, and also their influences on solute transport dynamics. For the last two decades, single-molecule fluorescence techniques have been used to measure the detailed dynamics of solute molecules diffusing in various nanostructured materials, giving valuable insights into molecular transport mechanisms influenced by nanoscale material heterogeneity. This Perspective will discuss recent single-molecule fluorescence studies on solute diffusion in materials relevant to membrane separations, including dense polymer films and nanoporous materials. These studies have revealed the formation and properties of nanostructures, and unique transport dynamics of solute molecules manipulated by their confinement and partitioning to the nanostructures, which play key roles in membrane separations. Furthermore, this Perspective will also point out scientific challenges toward thorough understanding of molecular-level mechanisms in membrane separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tardigrade-examples V0.1.0

Tardigrade-examples is a repository of computational workflows that exercise the Tardigrade software package. The Tardigrade software package is an implementation of Eringen’s micromorphic continuum theory with capabilities to support multiscale material modeling. These capabilities include homogenization through the Micromorphic Filter, calibration of micromorphic material models, and macroscale simulation in Tardigrade-MOOSE. This repository investigates continuum upscaling of various direct numerical simulations (DNS) conducted in Abaqus finite element (FE), Ratel FE, and GEOS material point method (MPM) software. Verification of the upscaling workflow is first investigated by considering DNS of trivial stress states for homogeneous materials, results of which indicate that classical continuum behavior is recovered as expected. DNS of heterogeneous materials are then considered.

Allard, Thomas↗

Mechanical and Thermophysical Properties of 3D-Printed SiC before and after Neutron Irradiation – FY21

This report presents the mechanical and thermophysical properties of 3D-printed SiC before and after neutron irradiation that have been evaluated to assess the fuel matrix material for the Transformational Challenge Reactor (TCR). The TCR fuel form consists of an additively-manufactured silicon carbide (SiC) matrix and uranium nitride tristructural isotropic (UN TRISO) fuel particles, which is manufactured through a newly developed processing route combining binderjet 3D printing, TRISO fuel particle loading, and chemical vapor infiltration (CVI). Because the fuel matrix is a primary component of the TCR core and its response to mechanical and thermal loads during operation is one of the most influential factors on the integrity of TCR core, testing and evaluation have focused on producing mechanical and thermophysical properties data for the binderjet/CVI SiC. Baseline mechanical and thermophysical properties were measured from the disk specimens printed for different and sizes orientations, which included equibiaxial flexural failure strength, elastic constants, thermal diffusivity and conductivity, density, and the coefficient of thermal expansion. Flexural failure strength datasets showed similar Weibull distributions regardless of sample variants including different orientations. The mean failure strengths of the 3D-printed SiC variants were in the range of 280–310 MPa, which are slightly lower than that of the chemical vapor deposition (CVD) SiC. Thermophysical test results showed that specific heat and thermal expansion are not sensitive to the build direction of SiC samples, while thermal conductivity is highly dependent on the build direction and can be correlated to the anisotropic character of the 3D-printed SiC. Neutron irradiation tests were carried out on the 3D-printed 6-mm diameter SiC disk specimens. Irradiation was carried to 2.3 dpa over a temperature range of 360–880°C. No significant degradation in strength was observed in SiC after irradiations in various conditions and with different orientations. Anisotropy that had been observed in the thermal conductivity of 3D-printed SiC prior to irradiation vanished after irradiation as the irradiation defect thermal resistivity accumulated in the material. Electron microscopy of the microstructure after neutron irradiation showed distinct defect morphologies in the heterogenous material, but no evidence for irradiation-induced cracking or degradation in the microstructure was observed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗