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At least 145 records · Page 8

Controlling superconductivity of CeIrIn 5 microstructures by substrate selection

Superconductor/metal interfaces are usually fabricated in heterostructures that join these dissimilar materials. A conceptually different approach has recently exploited the strain sensitivity of heavy-fermion superconductors, selectively transforming regions of the crystal into the metallic state by strain gradients. The strain is generated by differential thermal contraction between the sample and the substrate. Here, we present an improved finite-element model that reliably predicts the superconducting transition temperature in CeIrIn 5 even in complex structures. Different substrates are employed to tailor the strain field into the desired shapes. Using this approach, both highly complex and strained as well as strain-free microstructures are fabricated to validate the model. This enables a high degree of control over the microscopic strain fields and forms the basis for more advanced structuring of superconductors as in Josephson junctions yet also finds natural use cases in any material class in which a modulation of the physical properties on a chip is desirable.

36 MATERIALS SCIENCE↗

Brittle failure analysis and modeling of high-burnup PWR fuel cladding alloys

The aim of this research is the development of methods for predicting mechanical behavior and identification of limiting conditions to prevent brittle failure of high-burnup (HBU) pressure water reactor (PWR) fuel cladding alloys. A finite element (FE) model of the ring compression test (RCT) was created to analyze the failure behavior of zirconium-based alloys with radial hydrides during the RCT. An elastic-plastic material model describes the zirconium alloy. The stress-strain curve needed for the elastic-plastic material model was derived by inverse finite element analyses. Cohesive zone modeling is used to reproduce sudden load drops during RCT loading. Based on the failure mechanism in non-irradiated ZIRLO (R) claddings, a micro-mechanical model was developed that distinguishes between brittle failure along hydrides and ductile failure of the zirconium matrix. Two different cohesive laws representing these types of failure are present in the same cohesive interface. The key differences between these constitutive laws are the cohesive strength, the stress at which damage initiates, and the cohesive energy, which is the damage energy dissipated by the cohesive zone. Statistically generated matrix-hydride distributions were mapped onto the cohesive elements and simulations with focus on the first load drop were performed. Computational results are in good agreement with the RCT results conducted on high-burnup M5 (R) samples. It could be shown that crack initiation and propagation strongly depend on the specific configuration of hydrides and matrix material in the fracture area.

Simbruner, Kai↗

Failure Strain and Related Triaxiality of Aluminum 6061-T6, A36 Carbon Steel, 304 Stainless Steel, and Nitronic 60 Metals, Part I: Experimental Investigation

The objective of this study is to develop failure-limit material models for Aluminum 6061-T6, A36 Carbon Steel, 304 Stainless Steel, and Nitronic 60 metals, based on parameters of plastic equivalent strain (failure strain) and stress triaxiality. The research is conducted in two parts. This paper presents Part One of the study. In Part One, custom-designed test specimens undergo controlled uniaxial tension and compression testing at ambient temperature. These tests are performed at quasi-static speeds using Universal Testing Machines (UTMs) in accordance with ASTM E8 and ASTM E9 standards. Experimental data, specifically engineering stress–strain and force–displacement curves, are recorded from the onset of loading until specimen fracture, or in the case of compression tests, until the capacity of the testing machine is reached. In Part Two, the emphasis shifts to the calibration of Finite Element Analysis (FEA) models of the custom-designed test specimens. Plastic equivalent strain and the corresponding stress triaxiality values at failure are extracted from each test specimen for the given metal. These values are then systematically plotted onto a single graph to construct the failure-limit curve, which delineates the boundary conditions for material failure. This approach will facilitate the development of a comprehensive material property definition that correlates plastic equivalent strain with stress triaxiality at failure for Aluminum 6061-T6, A36 Carbon Steel, 304 Stainless Steel, and Nitronic 60 metals.

Harwell, Ron↗

Strain localization criteria for viscoplastic geomaterials

This report presents a viscoplastic localization criterion to detect quasi-instantaneous (i.e., load-induced) and delayed (creep-induced) strain localization in rate-dependent solids. The study is based on the theory of controllability and a viscoplastic description of the mechanical response. Analytical precursors of unstable states are defined through systems of ordinary differential equations (OEDs). The use of the proposed criteria is illustrated at the material point level through a set of strain localization analyses simulating active strain localization of a porous rock. In addition, full-field finite element simulations of compression tests conducted under various pressures are reported to demonstrate the role of local unstable viscoplasticity in the spontaneous propagation of deformation bands under stationary boundary conditions. The study shows that the viscoplastic localization criterion maintains a negative sign as long as the behavior is unstable, that is, the rate of deformation is accelerating. The sign switch coincides with the transition to decelerating deformation. The analyses revealed that pulses of overstress always emerge in correspondence with the growth of unstable behavior, and the peak matches the transition to stable behavior. The local responses recovered from full-field analyses were consistent with those observed in analyses at material point level and the predictions of the presented theory.

36 MATERIALS SCIENCE↗

Modeling of deformation of battery cells using thick shell element formulation

Here, we describe a new approach for modeling nonlinear deformation and stress distribution of battery cells using a new thick shell finite element formulation with a through-thickness calculation of stresses and strains that satisfy equilibrium conditions. Battery cells are transversely layered materials that contain numerous thin layers in a repeating sequence. The layers are made of materials with significantly different mechanical responses. Explicit discretization of the layers is computationally impractical except for very small domains, while homogenized material models cannot account for stress and strain variations and partition through the thickness. The new formulation allows for calculation of the transverse and interlayer stresses based on the material properties of the individual cell layers. The application to problems where the transverse stresses have strong influence is also possible.

25 ENERGY STORAGE↗

Boosting Piezoelectricity by 3D Printing PVDF‐MoS 2 Composite as a Conformal and High‐Sensitivity Piezoelectric Sensor

Abstract Additively manufactured flexible and high‐performance piezoelectric devices are highly desirable for sensing and energy harvesting of 3D conformal structures. Herein, the study reports a significantly enhanced piezoelectricity in polyvinylidene fluoride (PVDF) achieved through the in situ dipole alignment of PVDF within PVDF‐2D molybdenum disulfide (2D MoS 2 ) composite by 3D printing. The shear stress‐induced dipole poling of PVDF and 2D MoS 2 alignment are harnessed during 3D printing to boost piezoelectricity without requiring a post‐poling process. The results show a remarkable, more than the eight‐fold increment in the piezoelectric coefficient ( d 33 ) for 3D printed PVDF‐8wt.% MoS 2 composite over cast neat PVDF. The underlying mechanism of piezoelectric property enhancement is attributed to the increased volume fraction of β phase in PVDF, filler fraction, heterogeneous strain distribution around PVDF‐MoS 2 interfaces, and strain transfer to the nanofillers as confirmed by microstructural analysis and finite element simulation. These results provide a promising route to design and fabricate high‐performance 3D piezoelectric devices via 3D printing for next‐generation sensors and mechanical–electronic conformal devices.

2D MoS2↗

Hardening in Au-Ag nanoboxes from stacking fault-dislocation interactions

Porous, nano-architected metals with dimensions down to ~10 nm are predicted to have extraordinarily high strength and stiffness per weight, but have been challenging to fabricate and test experimentally. Here, we use colloidal synthesis to make ~140 nm length and ~15 nm wall thickness hollow Au-Ag nanoboxes with smooth and rough surfaces. In situ scanning electron microscope and transmission electron microscope testing of the smooth and rough nanoboxes show them to yield at 130 ± 45 MPa and 96 ± 31 MPa respectively, with significant strain hardening. A higher strain hardening rate is seen in rough nanoboxes than smooth nanoboxes. Finite element modeling is used to show that the structure of the nanoboxes is not responsible for the hardening behavior suggesting that material mechanisms are the source of observed hardening. Molecular dynamics simulations indicate that hardening is a result of interactions between dislocations and the associated increase in dislocation density.

42 ENGINEERING↗

Multitask graph neural networks for elastoplastic response prediction in dual-phase polycrystals

Microstructure-sensitive prediction of elastoplastic response remains a recurring bottleneck in multiscale damage and fatigue modeling, where large ensembles of statistically distinct polycrystals are required to quantify variability and extreme-value behavior. In this work, we develop a multitask graph neural network (GNN) surrogate that maps dual-phase ferrite–martensite polycrystal microstructures to Statistical Volume Element (SVE)-level elastoplastic Quantities of Interest (QoIs). Each SVE is represented as a grain-adjacency graph, with node features encoding phase, geometry, and crystallographic orientation, and edge features encoding relative misorientation. A message-passing graph convolution generates node embeddings, which are pooled into a graph representation and passed to a multitask regression head that jointly predicts 10 scalar QoIs and vector-valued stress–strain responses in orthogonal loading directions across multiple martensite volume fractions and SVE sizes. Results show high accuracy for scalar QoIs and strong agreement for full stress–strain trajectories, with population envelopes reproducing both median behavior and finite-SVE variability across compositions and partition scales. A unified model trained on pooled volume-fraction data preserves most within-regime accuracy relative to regime-specific models while also capturing the broader cross-regime variation reflected in the pooled test set. Distributional comparisons further demonstrate that the surrogate preserves heterogeneity under SVE partitioning, enabling statistically consistent block-wise random-field construction for mesoscale analyses. Overall, the proposed grain-graph surrogate provides a practical pathway to accelerate ensemble-based studies of SVE-level constitutive variability in dual-phase polycrystals.

Crystal plasticity↗

Metallization of diamond

Experimental discovery of ultralarge elastic deformation in nanoscale diamond and machine learning of its electronic and phonon structures have created opportunities to address new scientific questions. Can diamond, with an ultrawide bandgap of 5.6 eV, be completely metallized, solely under mechanical strain without phonon instability, so that its electronic bandgap fully vanishes? Through first-principles calculations, finite-element simulations validated by experiments, and neural network learning, we show here that metallization/demetallization as well as indirect-to-direct bandgap transitions can be achieved reversibly in diamond below threshold strain levels for phonon instability. We identify the pathway to metallization within six-dimensional strain space for different sample geometries. We also explore phonon-instability conditions that promote phase transition to graphite. These findings offer opportunities for tailoring properties of diamond via strain engineering for electronic, photonic, and quantum applications.

36 MATERIALS SCIENCE↗

Validation of material models for puncture of 7075-T651 aluminum plate

Plate puncture simulations are challenging computational tasks that require advanced material models including high strain rate and thermal-mechanical effects on both deformation and failure, plus finite element techniques capable of representing large deformations and material failure. The focus of this work is on the material issues, which require large sets of experiments, flexible material models and challenging calibration procedures. In this study, we consider the puncture of 12.7 mm thick, 7075-T651 aluminum alloy plates by a cylindrical punch with a hemispherical nose and diameter of 12.7 mm. The plasticity and ductile failure models were isotropic with calibration data obtained from uniaxial tension tests at different temperatures and strain rates plus quasi-static notched tension tests and shear-dominated tests described here. Sixteen puncture experiments were conducted to identify the threshold penetration energy, mode of puncture and punch acceleration during impact, The punch was mounted on a 139 kg mass and dropped on the plates with different impact speeds. Since the mass was the same in all tests, the quantity of interest was the impact speed. The axis and velocity of the punch were perpendicular to the plate surface. The mean threshold punch speed was 3.05 m/s, and the mode of failure was plugging by thermal-mechanical shear banding accompanied by scabbing fragments. Application of the material models in simulations of the tests yielded accurate estimates of the threshold puncture speed and of the mode of failure. Time histories of the punch acceleration compared well between simulation and test. Remarkably, the success of the simulations occurred in spite of even the smallest element used being larger than the width of the shear bands.

36 MATERIALS SCIENCE↗

Simulating the non-monotonic strain response of nanoporous multiferroic composites under electric field control

In this work, we simulate and analyze the mechanical response of a class of multiferroic materials consisting of a templated porous nanostructure made out of cobalt ferrite (CFO) partially filled by atomic layer deposition (ALD) with a ferroelectric phase of lead zirconate titanate (PZT). The strain in the device is measured when an electric field is applied for varying ALD thicknesses, displaying a non-monotonic dependence with a maximum strain achieved for a coating thickness of 3 nm. To understand this behavior, we apply finite element modeling to the smallest repeatable unit of the nanoporous template and simulate the mechanical response as a function of PZT coating thickness. We find that this non-monotonic response is caused by the interplay between two driving forces opposing one another. First, increased porosity works toward increasing the strain due to a reduced system stiffness. Second, decreased porosity involves a larger mass fraction of PZT, which drives the electro-mechanical response of the structure, thus leading to a larger strain. The balance between these two driving forces is controlled by the shear coupling at the CFO/PZT interface and the effective PZT cross section along the direction of the applied electric field. Here, our numerical results show that considering a nonlinear piezoelectric response for PZT leads to an improved agreement with the experimental data, consistent with ex situ poling of the nanostructure prior to magnetic measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Stress field and interaction forces between dislocations and precipitate distributions

A computational method is developed for calculation of the stress field and interaction forces between dislocations and precipitates of arbitrary shape and distribution. The internal stress generated by precipitates due to coherency strain is implemented within the discrete dislocation dynamics (DDD) framework. The s-version finite element method (s-FEM), which models a precipitate of arbitrary shape using a local mesh is used to calculate coherency stress fields. The method facilitates meshing precipitate volumes of arbitrary geometry, and multiple local meshes can be superimposed at various positions of the global mesh. Accuracy and convergence conditions of the method are established. For a single precipiate, the method is shown to be 3.5 times faster than a standard FEM calculation for the same accuracy, and the gain in speed increases with the number of precipitates. The CRSS of spherical precipitates is found to be higher than disk-shaped precipitates of the same volume fraction.

42 ENGINEERING↗

High-temperature compressive creep tests of U 3 Si 2 with spark plasma sintering: Experiments and finite element modeling

This paper reports a systematic high-temperature creep behavior of dense U 3 Si 2 pellets using a spark plasma sintering (SPS) apparatus at elevated temperatures and pressures under vacuum conditions. The stress exponent was subsequently derived to be 3.21 at 1173 K and 2.17 at 1223 K, respectively, indicating a grain boundary sliding creep mechanism. The creep activation energy was determined to be 203.6 ± 19.0 kJ/mol, which agrees well with the literature. Finite element modeling was performed using the creep parameters fitted from the strain-time plot. Additionally, the results suggest an excellent match with the experimental data, confirming the validity of the experiments. Microstructure characterizations indicate that the main phase of the specimens after creep tests remains to be U 3 Si 2 , with a 4 μm thick layer of nano-sized particles induced from the diffusion between U 3 Si 2 and alumina disc used to avoid electric current passing through the sample. The successful conduct of creep experiments demonstrates the great potential of SPS to perform high-temperature mechanical testing of nuclear fuels under vacuum conditions. The subsequent finite element modeling exhibits excellent capabilities for accurately predicting material performance in the creep tests and provides a practical tool in evaluating nuclear fuels’ performance for a much-extended time scale.

36 MATERIALS SCIENCE↗

A System-Level Model for Estimating Residual Strain and Life of Nuclear Reactor Coolant System Components Under Connected-System-Thermal–Mechanical Boundary Conditions

Background: Environmental-assisted fatigue (EAF) is a major issue for the long-term survival of nuclear power plant fleets in the U.S. and worldwide. Multi-material welded regions (e.g., nozzles) and other high-stress regions of reactor coolant system (RCS) components are prone to EAF-related damage. Objective: The discussed work describes a system-level finite element (FE) model of RCS components of a pressurized water reactor (PWR). This is with the goal of predicting the stress hotspots, strain residuals, strain amplitudes and the resulting fatigue lives. Methods: Herein, the FE model was developed considering system-level loading conditions (under connected system thermal-mechanical boundary conditions). Thermal-mechanical stress analysis was performed considering thermal stratification and a design-basis reactor loading cycle. Based on the FE model results, the strain residuals, strain amplitudes and resulting fatigue lives of RCS components were predicted. Results: The results show that some of the RCS components can have significantly different strain amplitudes, residual strain, and fatigue lives, despite having similar geometry and material. Higher residual strain can lead to accelerated cyclic hardening of material and the associated effect of EAF. The simulated component-level strain profile (under realistic multi-axial-multi-physics loading cycle) can guide the selection of appropriate test inputs for conducting laboratory-scale EAF tests, which is a focus of future works. Conclusions: Despite similar geometry and material the RCS component can have significantly different strain profiles and resulting fatigue lives. The discussed approach can help to identify and prioritize the RCS components for conducting expensive nondestructive evaluation (NDE) inspections.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Machine-Learning-Based Multiscale Methods for 3D Modelling of Granular Materials by Incorporating History-Dependent State Variables

Over the past decades, the prevalence of machine learning (ML) methods has made the development of ML-based constitutive models for granular materials undoubtedly a popular subject. Numerous studies have been made to feature the loading path or history-dependent stress-strain response of granular media using neural networks. In this work, a novel finite element method (FEM)–ML multiscale approach was developed by incorporating internal variables to improve the simulation accuracy of 3D history-dependent granular materials for the first time. To this end, a surrogate constitutive model based on the single-step-based multi-layer perceptron (MLP) neural network was used to replace representative volume element (RVE) simulations conducted by the discrete element method (DEM) in the multiscale FEM–DEM approach. Although the prediction principle of the MLP aligns with the FEM algorithm, artificially added internal variables are required to differentiate the loading history. To address this issue, history variables associated with the Frobenius norm are proposed to be fed into the MLP coupled with the strain tensor to extract the history-dependent behaviour of granular assemblies. The developed FEM–ML approach was demonstrated in 3D conventional triaxial compression (CTC) simulations. Compared to the multiscale FEM–DEM approach, the proposed FEM–ML method exhibits a significantly improved computational efficiency.

granular materials↗

Comparison of three state-of-the-art crystal plasticity based deformation twinning models for magnesium alloys

In magnesium alloys, deformation twinning and its interactions with dislocation slip are responsible for a sigmoidal shape stress–strain behavior and an asymmetrical tension–compression yield strength in magnesium alloys. The sensitivity of twinning to the underlying microstructure renders the crystal plasticity method the most commonly adopted modeling approach for magnesium-twinning. This paper compares three state-of-the-art crystal plasticity-based twinning models from the literature, namely the elastic-viscoplastic self-consistent twinning-detwinning (EVPSC-TDT) model, crystal plasticity finite element model based on enhanced predominate twin reorientation approach (CPFE-ePTR), and the crystal plasticity finite element model based on “discrete twinning” approach (CPFE-DT). A polycrystalline microstructure is simulated with all three methods to compare the resulting stress–strain curves and lattice strains to those from the experimentally measured data. All three methods showed the capability of capturing the experimental results with different levels of accuracy. Additionally, the EVPSC-TDT method avoids solving the finite element matrices and showed the highest computational efficiency. The CPFE-ePTR model shows a higher accuracy in capturing the lattice strain. The CPFE-DT relies on high-resolution finite element mesh and is much slower than the other two methods, but it captured the local deformation concentration and stress reversal phenomena near the twin band, which was not possible with the other two methods. Based on the comparison, guidance for the selection of the appropriate model based on the specific modeling target is provided in this paper.

36 MATERIALS SCIENCE↗

Learning constitutive relations using symmetric positive definite neural networks

In this work, we present a new neural-network architecture, called the Cholesky-factored symmetric positive definite neural network (SPD-NN), for modeling constitutive relations in computational mechanics. Instead of directly predicting the stress of the material, the SPD-NN trains a neural network to predict the Cholesky factor of the tangent stiffness matrix, based on which the stress is calculated in incremental form. As a result of this special structure, SPD-NN weakly imposes convexity on the strain energy function, satisfies the second order work criterion (Hill's criterion) and time consistency for path-dependent materials, and therefore improves numerical stability, especially when the SPD-NN is used in finite element simulations. Depending on the types of available data, we propose two training methods, namely direct training for strain and stress pairs and indirect training for loads and displacement pairs. We demonstrate the effectiveness of SPD-NN on hyperelastic, elasto-plastic, and multiscale fiber-reinforced plate problems from solid mechanics. The generality and robustness of SPD-NN make it a promising tool for a wide range of constitutive modeling applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Behavior of strain stripe networks in barium titanate nanocrystals on crossing its ferroelectric phase transition

Nanoscale strain networks are reported in BaTi O 3 (BTO) crystals of 300 nm size using Bragg coherent diffractive imaging. BTO nanocrystals with clear facets were chosen to identify the crystallographic directions, allowing the strain field direction and periodicity to be studied in detail. Stripes of strain were observed, which were both stable and preserved in tetragonal and cubic phases at elevated temperatures, above the tetragonal-to-cubic phase transition. A finite element analysis approach was used to simulate the domain structures inside a BTO crystal and to understand the origins of the strain stripes as piezoelectric blocks. A 180 ∘ domain model gives a better qualitative match to the experimental images. Published by the American Physical Society 2024

77 NANOSCIENCE AND NANOTECHNOLOGY↗