Behavior Of Materials Research Articles

Clinicoradiological application of the use of spectral cranial computed tomography in the management of acute ischemic stroke after mechanical thrombectomy.

Acute ischemic stroke is one of the leading global causes of morbidity and mortality. Mechanical thrombectomy has improved the functional prognosis of this condition; however, hemorrhagic transformation is a common complication. Spectral computed tomography (CT) imaging, as a neuroimaging control test, distinguishes contrast extravasation from hemorrhagic transformation due to the differential behavior of materials at dual energy levels. This distinction is valuable in its clinical therapeutic management. A single-center, observational, retrospective study was conducted in which the presence of various clinical, radiological, and therapeutic variables in patients with acute ischemic stroke treated with mechanical thrombectomy at our hospital between July 2022 and March 2023 was investigated using access to a dissociated database and medical records. Out of 155 included patients, spectral cranial CT was performed in 63, and conventional cranial CT in 75. In the spectral CT group, 21 hyperdense images were detected, compared to 28 in the conventional CT group. In 42.8% of cases where hyperdensity was detected in the conventional CT group, it was not possible to distinguish between contrast extravasation and hemorrhagic transformation, in contrast to the 4.8% in the spectral CT group (p < 0.001). Spectral CT provides high diagnostic confidence to the radiologist in identifying the type of detected hyperdensity, thereby offering significant therapeutic confidence to the neurologist in early resuming anticoagulation therapy.

Concurrent delamination propagation and deformation localization in semiconductor devices

In semiconductor devices, metals and polymers are often integrated as electrical conductors and insulators. Fabrication and operation of the devices cause stress in such an integrated structure. The stress can delaminate the metals and polymers, as well as deform them plastically. Here we show that the delamination can localize the deformation in the metals, which form necks to rupture the metals and sever electrical conduction. We simulate the coevolution of delamination propagation and deformation localization. The metals and polymers are modeled as elastic-plastic materials, and their adhesion is represented by a cohesive zone model. The simulation highlights that extensive delamination is a prerequisite for the metals to form necks, and that necking causes delamination to propagate further. Also highlighted are the impact of corners in the structure. Preexisting defects make the structure particularly vulnerable to concurrent delamination and necking. It is hoped that this study will draw renewed attention to the mechanical behavior of materials in the development of the semiconductor industry.

The anti-dogbone: Evaluating and designing optimal tensile specimens for deep learning of constitutive relations

Traditional tensile testing with “dogbone”-shaped specimen (ASTM E8, first standardized in 1924) strives for strain uniformity. Multiple tests with such samples help fit simple constitutive relation parameters on real materials. With the development of deep learning, the concept of employing entirely data-driven constitutive relations to capture more intricate material behavior has arisen. Nevertheless, these methods demand experimental data that are distributed throughout the complete stress–strain configuration space to effectively train the machine learning models. This is particularly crucial for mechanisms like hardening, which are time-dependent and sensitive to loading history. In this work, we investigate the potential to efficiently gather a wider range of experimental data points in the stress–strain configuration space using non-uniform samples and displacement-field mapping, leveraging advancements in computer vision techniques. We developed a metric to quantify stress state diversity in 2D tensile experiments and used it to optimize the shape of the sheet sample. The goal was to increase stress–strain diversity obtained within a single test, particularly in the linear elastic regime. Additional geometric constraints can be introduced on the design features, considering factors such as size and curvature to adapt to the microstructural characteristics of the sample material.

A Macro-Micro Approach for Identifying Crystal Plasticity Parameters for Necking and Failure in Nickel-Based Alloy Haynes 282

This work develops a two-scales macro-micro approach to address the challenge in calibrating crystal plasticity microstructural models when samples undergo necking prior to fracture. The crystal plasticity models are crucial for predicting the materials’ plastic deformation and failure at the microstructure level, identifying the materials’ intrinsic properties as well as investigating the microstructure-properties relationships. However, after necking occurs, the experimentally measured stress-strain curves fail to reflect the materials ‘true’ stress-strain behavior and cannot be directly fitted into crystal plasticity models. The proposed macro-micro approach employs a top-down strategy to address this challenge, which has been studied with experimental tests on precipitation-strengthened Ni-based superalloy Haynes® 282®. In this approach, a macro rate-dependent anisotropic plasticity model with Voce-type hardening and Rice-Tracey damage law is first utilized to model the deformation and failure of the tensile bar, and calibrated by matching the stress-strain curves, necking strain, and reduction of area. Especially, to match the testing results under different applied strain rates, the rate-sensitivity parameter m and saturation stress in the elasticity model are modified to incorporate dependence on the local strain rate. Then, the ‘true’ stress-strain behaviors are extracted from the necking zone of the macro-model, which are used to calibrate a micro-model with explicit microstructures and governed by an extended crystal plasticity law. The consistency between the micro-model and macro-model are enforced during calibration. The calibration outcomes from the crystal plasticity model elucidate the materials intrinsic properties for slip, hardening, and failure, which is vital for further investigations into the microstructure-properties relationship and for accurate prediction of the material behavior under various test and service conditions.

Peridynamic neural operators: A data-driven nonlocal constitutive model for complex material responses

Neural operators, which can act as implicit solution operators of hidden governing equations, have recently become popular tools for learning the responses of complex real-world physical systems. Nevertheless, most neural operator applications have thus far been data-driven and neglect the intrinsic preservation of fundamental physical laws in data. In this work, we introduce a novel integral neural operator architecture called the Peridynamic Neural Operator (PNO) that learns a nonlocal constitutive law from data. This neural operator provides a forward model in the form of state-based peridynamics, with objectivity and momentum balance laws automatically guaranteed. As applications, we demonstrate the expressivity and efficacy of our model in learning complex material behaviors from both synthetic and experimental data sets. We also compare the performances with baseline models that use predefined constitutive laws. We show that, owing to its ability to capture complex responses, our learned neural operator achieves improved accuracy and efficiency. Moreover, by preserving the essential physical laws within the neural network architecture, the PNO is robust in treating noisy data. The method shows generalizability to different domain configurations, external loadings, and discretizations.

I too [formula omitted]: A new class of hyperelastic isotropic incompressible models based solely on the second invariant

In contemporary elasticity theory, the strain–energy function predominantly relies on the first invariant, I1 of the deformation tensor; a practice that has been influenced by models derived from rubber elasticity. However, this approach may not fully capture the complexities of materials exhibiting pronounced shear deformations, such as very soft biological tissues. Here, we explore the implications and potential benefits of constitutive models where the strain–energy function is exclusively a function of the second invariant, I2. By shifting the focus towards I2, we aim to address the limitations of current models in accurately describing shear-dominated behaviors and to provide a more comprehensive understanding of material responses, particularly for materials that do not conform to the assumptions underlying I1-centric theories. Through theoretical musings, data analysis, and automated model discovery, we investigate the feasibility of this approach and its consequences for predicting material behavior under various loading conditions. We show that the so-called “second-invariant materials” conforming to I2-only have interesting properties that are found in biological tissues and are fundamentally different from the traditional “first-invariant materials”.

Ductile damage and fracture characterizations in bi-cyclic biaxial experiments

This paper discusses novel extremely low-cycle bi-cyclic biaxial reverse experiments with large strains. Various tests with tension-compression-tension (TCT) shear cyclic loads, superimposed by either non-reverse or reverse cyclic loading patterns, are newly designed to investigate the plastic, damage, and fracture behavior. These experiments fill the gaps in carrying out complex reverse loading by utilizing 4mm thick biaxially loaded cruciform specimens. The deformed specimens in different loading stages are examined metallographically with micrographs to elucidate the influence of loading histories on the occurrence and evolution of micro-defects. In addition, scanning electron microscopy (SEM) is also used to analyze the fractured surfaces and verify the anisotropic damage mechanism. An advanced anisotropic cyclic plastic-damage continuum model is utilized to characterize the material behavior, including the Bauschinger effect, the stress-differential effect and the non-hardening effect after shear reverse loading as well as stress-state-induced damage mechanisms. Due to the utilization of the digital image correlation (DIC) technique, the numerical results can be compared with the experimental ones in both load–displacement curves and strain fields, respectively. The elastic strain triaxiality and strain Lode parameter are introduced, providing a novel perspective for analyzing the cyclic loading experiments.

A nonlinear analytical method for pipeline strain under soil thaw subsidence load in permafrost region

In frozen terrain, the transportation of heated oil triggers thermal soil thaw and collapse, leading to pipeline distortion and breakdown. During substantial ground settlement in such terrains, current strain prediction techniques for pipelines fall short, neglecting significant pipeline bending, non-linear material behaviors, or detailed pipeline-permafrost interplay. To address this, a model focusing on pipeline-soil dynamics is devised, incorporating material non-linearity and pronounced pipeline distortion. This model derives analytical strain solutions for pipelines by aggregating incremental distortions of pipeline components via a strain iteration technique. Concurrently, a three-dimensional solid finite element model is crafted, assessing pipeline strains across varying subsidence zone dimensions, factoring in the complicated permafrost environment. The model's efficiency is affirmed by its less than 3% discrepancy from finite element method results, showcasing its enhanced accuracy and dependability in predicting pipeline strains under extensive soil settlement scenarios.

Comparing the laser-induced damage distribution in POFs with raytracing simulations

The understanding of the laser-induced damage behavior in polymer optical materials is of high interest to prevent their damage and to increase the laser damage resistance of optical components. Moreover, compared with optical components made from high-quality glass materials, nanosecond laser-induced damage for wavelengths in the visible and near-infrared (NIR) occurs inside the bulk material of PMMA and not at its surface. This phenomenon complicates the determination of the laser-induced damage threshold (LIDT) in PMMA fibers. Since the bulk material itself determines the LIDT, knowledge of the intensity distribution in the multimode fiber is of utmost importance. Our fibers were irradiated at a wavelength of 532 nm with an ns-pulsed laser system with a 10 Hz repetition rate. To investigate the damage behavior in polymer optical fibers, we applied different imaging and analysis techniques. To our knowledge, those techniques are used here for the first time in order to study damaged polymer materials. With the help of a Nomarski microscope, axial and radial damage distributions within the multimode PMMA fibers were determined and compared with ray-tracing simulations of the intensity distribution within the optical fiber. Moreover, extruded PMMA plates were irradiated with the aim of comparing the damage behavior of materials with different manufacturing. In addition, the planar geometry of the plates allows for a more reliable application of the different measurement methods. Overall, investigations with a thermal imaging camera and EDX analysis indicate that the damage behavior of polymer optical material is thermally driven during the ns-pulsed irradiation. Furthermore, voids are formed during the damaging process within the polymer optical fibers and plates, as indicated by both SEM images and X-ray computed microtomography (µ-CT) investigations. Finally, we investigated the damages in fiber preforms and PMMA plates using two photon-microscopy. By doing this, we detected fluorescence signals from the damaged material, indicating that the damage process leads to a major modification of the polymer.

Hydrogen Reduction Behavior of NCM-based Lithium-ion Battery Cathode Materials

As the demand for lithium-ion batteries for electric vehicles is increasing, it is important to recover valuable metals from waste lithium-ion batteries. In this study, the effects of gas flow rate and hydrogen partial pressure on hydrogen reduction of NCM-based lithium-ion battery cathode materials were investigated. As the gas flow rate and hydrogen partial pressure increased, the weight loss rate increased significantly from the beginning of the reaction due to the reduction of NiO and CoO by hydrogen. At 700 °C and hydrogen partial pressure above 0.5 atm, Ni and Li2O were produced by hydrogen reduction. From the reduction product and Li recovery rate, the hydrogen reduction of NCM-based cathode materials was significantly affected by hydrogen partial pressure. The Li compounds recovered from the solution after water leaching of the reduction products were LiOH, LiOH·H2O, and Li2CO3, with about 0.02 wt% Al as an impurity.

First principles study of chromium-based hydrides for optoelectronics and hydrogen storage applications

The first-principles study employed on chromium-based hydride XCrH3 (X: Na, K) is the first time studied and investigated different physical properties incorporated for optoelectronics and hydrogen storage applications. The structural properties results revealed that these materials have cubic phases, with lattice constants are 3.54 Å (NaCrH3), and 3.74 Å (KCrH3), which was also confirmed by the XRD analysis. The XRD results revealed that the intensity of KCrH3 is shifted towards to lower angle (2θ) degree due to high lattice constants and inter-planner distance. Moreover, both materials exhibited thermodynamically and mechanically stable due to negative formation energy, and elastic constants, and obeyed the Born approximation criteria. The phonons dispersion curve shows that XCrH3 is dynamically stable due to no imaginary frequency presence. Electronic properties found that current materials have metallic characteristics, due to zero band-gap energy, which plays a vital role in hydrogen storage applications. Magnetic properties exhibited paramagnetic behavior of current materials highly contributed to hydrogen storage application due to unpaired electrons and studied materials have spin-polarized magnetic nature. However, elastic properties confirmed that these materials are found hard, and brittle, with an ionic bonding nature between the atoms, and an anisotropic character. Besides this, different optical parameters have studied like as conductivity, absorption coefficient, refractive index, reflectance, and loss function and the results revealed that the examined materials dominated the role in LED, sensors, solar cells, and optoelectronics applications. Thermal analysis revealed that increasing temperature increases energy and entropy but decreases free energy. Among the studied materials, NaCrH3 has a high gravimetric ratio of 3.87 wt%, and KCrH3 is 3.21 wt%. These materials provided new potential for hydrogen storage applications.

Experimental investigation on the behavior of thermal super insulation materials for cryogenic storage tanks in fire incidents

The number of vehicles using or transporting cryogenic fuels such as Liquefied Hydrogen (LH2) or Liquefied Natural Gas (LNG) increases fast in the land transportation sector. Does this also entail new risks? The storage of cryogenic fuels requires tanks with Thermal Super Insulations (TSI) to keep the fluid cold and limit the formation of boil-off gas. TSI has proven itself in some applications since the middle of the 20th century, but in the land transport sector they are still quite new, where accidents involving fires, collisions, and their combination are to be expected. This work focuses on investigating the behavior of different types of TSI while exposed to a heat source representing a fire. To this aim, a High-Temperature Thermal Vacuum Chamber (HTTVC) was applied, which allows the thermal loading of a thermal insulation material in a vacuum and measuring the heat flow transported through the TSI in parallel. In this study, the results of 6 samples are presented regarding 3 types of MLI, rock wool, perlites, and microspheres. The thermal exposure caused different effects on the samples. In practice, this can be connected to the rapid release of flammable gases as well as to a Boiling Liquid Expanding Vapour Explosion (BLEVE). These results are relevant for reducing the risks to people and infrastructures in the progressive establishment of tanks for cryogenic fluids in our industry and society. The data presented in the study can be used to improve the design of tanks and TSIs, the assessment of accident scenarios, and the development of measures for first responders.

On-the-fly multiscale analysis of composite materials with a Generalized Finite Element Method

A multiscale computational framework to capture stress concentrations and localized nonlinearity in composite structures is presented. An enriched approximation space, constructed using the generalized finite element method (GFEM), is used to incorporate nonlinear, heterogeneous material behavior into coarse-scale models on the fly. Enrichment functions are constructed using the GFEM with global–local enrichment functions (GFEMgl). The auxiliary local problems associated with the GFEMgl also define fine-scale constitutive behavior that is inherited by the coarse global problem. This allows a coarse homogenized global problem to learn about material heterogeneity and/or nonlinearity on the fly, considerably increasing the flexibility of the method. On top of the explicit definition of heterogeneity in local problems, the locally defined constitutive law can incorporate further levels of heterogeneity that are not explicitly modeled at the global scale. The proposed GFEMgl comes with the efficiency and scalability characteristic of the method and greatly increases the flexibility when applied to heterogeneous structures with localized material nonlinearity.

Repair Analysis of Overlay Woven Fabric CFRP Laminates

The increase in aerospace composites usage for structural components demands advanced repair analysis. Overlay repairs of carbon fiber-reinforced polymer laminates offer an alternative that is easier to perform and less time-consuming to produce than the widely used tapered scarf repair and stepped lap. Composite specimen manufacturing was based on both twill carbon/epoxy prepreg and wet lay-up. The repair was performed with both prepreg and wet extra plies to the parent prepreg structure. However, the design of overlay joints must be carefully investigated to avoid generating stress concentration regions at free edges. This study examined specific extra ply terminations' impact on peak stresses in the adhesive bond line. Linear finite element analysis was performed to conduct a maximum principal stress study with a focus on three joint design parameters: ply material, overply effect, and stacking sequence. FEA accurately predicted experimentally observed responses and provided further insight into the failure behavior of the structure. Results showed that overlay joints have a strong sensitivity to ply material type, the number of overply, and stacking sequence. The introduction of overplies provided protection and stiffness at joint tips, and an overply material behavior was identified. The location of 0̊ plies in the composite laminates was highlighted as an important factor. The analysis was then extended to three-dimensional FE models for verification. In conclusion, results showed that high-stress concentration in overlay joints can be mitigated with the introduction of overplies and appropriate changes in joint design parameters to reduce stress peaks at joint tips and corners.

Fracture toughness of AlSi10Mg alloy produced by LPBF: effects of orientation and heat treatment

AbstractIn this study, AlSi10Mg samples were manufactured by laser-powder bed fusion process to explore the fracture toughness dependence on both built orientation and aging treatment. The experiments were performed on as-built and directly-aged (200$$^{\circ }$$ ∘ C/4 h) conditions, with the latter revealed to be a valuable treatment for improving fracture toughness. A comprehensive investigation involving detailed microstructural analysis, grain-orientation mapping, and crack-tip strain measurements was conducted to investigate the mechanisms governing the material behavior. The results revealed that specimens subjected to direct aging display higher toughness, thereby enhancing the fracture resistance of AlSi10Mg. Moreover, a considerable variation in fracture toughness values was observed for the different printing orientations, indicating the existence of manufacturing-induced anisotropy. The findings highlight that this anisotropy mainly correlates with the distinctive microstructure induced by the additive manufacturing process. In particular, this study focuses on the different preferential crack paths dictated by the melt pool boundaries orientation respective the crack propagation direction. A substantial reduction in fracture toughness was observed when the crack propagates along the melt pool boundaries.

Ultralow-threshold dual-wavelength optical bistability from a perovskite hyperbolic metasurface and its application in a photonic neural network

In a hyperbolic metamaterial or metasurface (HMM or HMS), strong light-matter interaction occurs at the phase transition wavelength where the material behavior changes from metal to dielectric. As a result, the enhanced electric field can generate non-linear phenomena, such as optical bistability. In this work, we numerically investigate polarization-dependent dual-wavelength optical bistability from perovskite HMS consisting of alternating layers of MAPbBr3 perovskite and Au. Benefiting from the anisotropic property, the bistable operation wavelength for TE and TM polarizations are different. In particular, for TE polarization, strong light matter interaction resulting from the increment of incident light power not only shifts the phase transition wavelength but also enhances the transmission. Consequently, the bistable on-off contrast ratio is unprecedentedly enlarged. For TM polarization, strong light-matter interaction gives rise to an ultra-low bistable threshold. The proposed optical bistable states can serve as an activation function for optical neurons in a photonic neural network, with similar prediction accuracy across a variety of learning tasks as the classic activation functions ReLU and Sigmoid. Our work suggests a novel avenue towards the insertion of perovskite HMS into optical computing networks.

Simulating Elastoplastic and Anisotropic Behavior in Thermoplastic Additively Manufactured Components: An Application-Oriented Modeling Approach.

This paper presents a comprehensive approach aimed at developing a coupled process-structure simulation that integrates anisotropic and elastoplastic material behavior for plastic components manufactured through Fused Filament Fabrication (FFF) 3D printing. The simulation incorporates material orientation considerations, linking the process simulation with structural simulation. Subsequently, stress and strain values from the simulations are compared with the test results. Moreover, the fracture behavior of components manufactured in this way is also taken into account in relation to material orientation. The executed simulations have yielded successful outcomes, affirming the efficacy of the anisotropic and elastoplastic simulation across all strand orientations. Special attention is paid to the application of the method. Here, the simulation method introduced in this contribution with the approaches for describing the material behavior under mechanical load can be used in the future in the dimensioning of FFF manufactured plastic components to predict the deformation behavior and failure, especially under consideration of a well economic and efficient virtual product development.

Nanosecond pulsed discharge plasma modified porous polymer adsorbent materials for efficient removal of low‐concentration bisphenol A in liquid

AbstractThe efficient removal of low‐concentration endocrine disruptors is crucial for the protection of the aquatic environment. In this study, porous polymer adsorbent materials were modified by nanosecond pulsed discharge plasma to achieve efficient adsorption of low‐concentration bisphenol A (BPA). The removal efficiency of BPA reached 99% after 10 min of plasma modification at a pulse peak voltage of 28 kV, which increased by 25.8% compared to the raw materials. This enhancement was attributed to the increase of active sites and oxygen‐containing functional groups. The adsorption behaviors of the porous polymer materials were primarily dominated by monolayer chemisorption. Subsequently, comparative experiments further verified the high‐efficiency adsorption performance of porous polymer materials after plasma treatment.

Digital Image Correlation Analysis of Uniform Deformation and Necking in Solid‐State Welded Nanocrystalline Aluminum via High‐Pressure Torsion

Solid‐state welding of Al 1043 sheets was achieved via high‐pressure torsion (HPT) processing to produce bulk nanostructured Al disks. A homogeneous nanostructure without segregation was observed, with grain sizes of ∽430‐470 nm. Miniature tensile testing, coupled with the digital image correlation (DIC) technique, was employed to determine the room‐temperature tensile deformation behavior, particularly the non‐uniform behavior with necking, of the HPT‐bonded ultrafine‐grained (UFG) aluminum, comparing it with annealed coarse‐grained counterpart. The HPT‐bonded UFG Al exhibited a large fraction of post‐necking strain, which is supported by the estimated high strain rate sensitivity value of m = 0.085, suggesting the delay of local necking leading to tensile fracture. Detailed DIC analysis revealed prolonged diffuse necking, thus delaying local necking, in the HPT‐bonded UFG Al, while the annealed samples show high fractions of local necking during the non‐uniform deformation. Moreover, the DIC data illustrated that local necking predominantly occurred at a limited neck zone, maintaining a plateau strain distribution at the out‐of‐neck zone throughout necking deformation towards tensile failure for both annealed and UFG aluminum. The DIC method offers an alternative means to demonstrate the transition in necking behaviors of materials by estimating the plastic lateral contraction exponent.This article is protected by copyright. All rights reserved.

Surface Tension Estimation of Steel above Boiling Temperature

Surface tension is an important characteristic of materials. In particular at high temperatures, surface tension values are often unknown. However, for metals, these values are highly relevant in order to enable efficient industrial processing or simulation of material behavior. Plasma, electron or laser beam processes can induce such high energy inputs, which increase the metal temperatures to, and even above, boiling temperatures, e.g., during deep penetration welding or remote cutting. Unfortunately, both theoretical and experimental methods experience challenges in deriving surface tension values at high temperatures. Material models of metals have limitations in explaining complex ion interactions, and experimentally measuring temperature and surface tension at high temperatures is a challenge for methods and equipment. Therefore, surface wave analysis was conducted in this work to derive surface tension values around the boiling temperature of steel and identify trends. In addition, a simple ion interaction calculation was used to simulate the impacting parameters that define the surface tension. Since both the experimental values and simulation results indicate an increasing trend in surface tension above the boiling temperature, it is concluded that the dominating attractive forces above this temperature should increase with increasing temperature and lead to increasing surface tension forces in the surface layers of liquid metal.