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For over two decades, vascular stents have been widely used to treat clogged vessels, serving as a scaffold to enlarge the narrowed lumen and recover the arterial flow area. High-purity oligocrystalline austenitic steel is usually applied for the production of stents. Despite the popularity and benefit of stenting, it still may cause serious clinical adverse issues, such as in-stent restenosis and stent fracture. Therefore, the study of the mechanical properties of stents and in particular the prediction of their life cycles are in the focus of materials research. In our contribution, within the finite element method, a two-scale model of crack initiation in the microstructure of stents is elaborated. The approach is developed on the basis of the physically based Tanaka–Mura model (TMM), considering the evolution of shear bands during the crack initiation phase. The model allows for the analysis of the microstructure with respect to the life cycles of real materials. The effects of different loading conditions, grain orientation, and thickness of the specimen on Wöhler curves were analysed. It was found that the microstructural features of oligocrystals are very sensitive to different loading conditions with respect to their fatigue behaviour and play a major role in fatigue crack initiation. Different grain-orientation distributions result in qualitative and quantitative differences in stress distribution and in the number of cycles for crack initiation. It was found that presence of a neutral zone in the cut-out of the microstructure under three-point-bending loading conditions changes the qualitative and quantitative patterns of stress distribution and affects the number of cycles for crack initiation. It was found that under both tensile and bending loading conditions, thicker specimens require more cycles for crack initiation. The Wöhler curves for crack initiation in oligocrystalline microstructures of stents could be compared with the ones in the experiment, taking into account that for high cyclic fatigue (HCF), typically, more than 70% of the cycles refer to crack initiation. The developed numerical tools could be used for the material design of stents. [ABSTRACT FROM AUTHOR]

This work is devoted to the problem of thermal fracture of a functionally graded coating on a homogeneous substrate (FGC/H) with an emphasis on the analysis of a special system of cracks that simulates a curved interface. The FGC/H structure contains the pre-existing crack system in the FGC, both edge cracks (which are often seen in FGC/H structures) and internal cracks. The stress intensity factors are calculated. (Generally, both Mode I and Mode II are nonzero.) Then, using the appropriate fracture criterion for mixed-mode fracture conditions, the crack propagation direction (so-called fracture angles) and critical loads, when this propagation is initiated, are determined. The application of fracture criteria requires knowledge of the fracture toughness near the crack tips. Thus, it is assumed that the fracture toughness of an FGC, as well as other material properties, continuously varies through the thickness of the coating. For multiple cracks, it is also important to know the weakest crack that starts to propagate first, and the initial direction of this growth. Therefore, the main attention is paid to the evaluation of the fracture angles for the cracks for different parameters of the FGC/H structure. Both cases of a homogeneous semi-infinite medium with a system of cracks imitating a curved interface and FGC/H structures with identical crack systems are studied. [ABSTRACT FROM AUTHOR]

Auxetic structures made of biodegradable polymers are favorable for industrial and daily life applications. In this work, poly(butylene adipate-co-terephthalate) (PBAT) is chosen for the study of the deformation behavior of an inverse-honeycomb auxetic structure manufactured using the fused filament fabrication. The study focus is on auxetic behavior. One characteristic of polymer deformation prediction using finite element (FE) simulation is that no sounded FE model exists, due to the significantly different behavior of polymers under loading. The deformation behavior prediction of auxetic structures made of polymers poses more challenges, due to the coupled influences of material and topology on the overall behavior. Our work presents a general process to simulate auxetic structural deformation behavior for various polymers, such as PBAT, PLA (polylactic acid), and their blends. The current report emphasizes the first one. Limited by the state of the art, there is no unified regulation for calculating the Poisson's ratio ν for auxetic structures. Here, three calculation ways of ν are presented based on measured data, one of which is found to be suitable to present the auxetic structural behavior. Still, the influence of the auxetic structural topology on the calculated Poisson's ratio value is also discussed, and a suggestion is presented. The numerically predicted force–displacement curve, Poisson's ratio evolution, and the deformed auxetic structural status match the testing results very well. Furthermore, FE simulation results can easily illustrate the stress distribution both statistically and local-topology particularized, which is very helpful in analyzing in-depth the auxetic behavior. [ABSTRACT FROM AUTHOR]

Interfacial debonding affects the mechanical behaviors of composite structures. In the present work, we developed a new phase-field-based cohesive zone model for modeling debonding at interfaces. The traction-separation law and evolution of phase-field considering the mixed-mode scheme of fracture toughness are given in a variational form. Besides, the present interfacial model can work with the phase-field cohesive zone model for the bulk region, in which a common phase-field value ϕ is shared for both regions. The interaction between the bulk region and interfacial cracking in both displacement, as well as phase-field, are taken into account directly to avoid the over-estimation of the free surface energy. The framework is implemented with the finite element method and validated with several numerical examples. The present work provides a unified approach for modeling quasi-brittle fracture in the bulk region and interfaces and shows its advantage in describing interactions between bulk and interfacial cracking. • A phase-field-based cohesive element is proposed for interfacial failure. • Srength and fracture toughness can be defined independently in different directions. • Closure effect of the interfacial crack can be modeled with given penalty stiffness. • Governing equation is given in a variational form. • Mixed-mode behaviors of interfacial fracture is also considered. • The interaction between interface and matrix is considered by a driving force term. [ABSTRACT FROM AUTHOR]

The current work investigates the auxetic tensile deformation behavior of the inversehoneycomb structure with 5 × 5 cells made of biodegradable poly(butylene adipate-coterephthalate) (PBAT). Fused deposition modeling, an additive manufacturing method, was used to produce such specimens. Residual stress (RS) and warpage, more or less, always exist in such specimens due to their layer-by-layer fabrication, i.e., repeated heating and cooling. The RS influences the auxetic deformation behavior, but its measurement is challenging due to its very fine structure. Instead, the finite-element (FE)-based process simulation realized using an ABAQUS plug-in numerically predicts the RS and warpage. The predicted warpage shows a negligibly slight deviation compared to the design topology. This process simulation also provides the temperature evolution of a small-volume material, revealing the effects of local cyclic heating and cooling. The achieved RS serves as the initial condition for the FE model used to investigate the auxetic tensile behavior. With the outcomes from FE calculation without consideration of the RS, the effect of the RS on the deformation behavior is discussed for the global force–displacement curve, the structural Poisson's ratio evolution, the deformed structural status, the stress distribution, and the evolution, where the first three and the warpage are also compared with the experimental results. Furthermore, the FE simulation can easily provide the global stress–strain flow curve with the total stress calculated from the elemental stresses. [ABSTRACT FROM AUTHOR]

Auxetic structures have a negative Poisson's ratio and therefore expand transversely to the direction of loading instead of tapering. This unique behavior is not caused by the materials used, but by the structure, and thus offers completely new functionalities and design possibilities. As a rule, auxetic structures have a very complex geometry, which makes cost-effective production possible only by means of additive manufacturing processes. Due to the high design freedom of the strand deposition method, it makes sense to manufacture auxetic structures using this process. Therefore, in this project, polylactide acid (PLA), polybutylene adipate terephthalate (PBAT), and blends of the two polymers were produced and characterized. Filaments of the two polymers and a blend were extruded, processed into auxetic structures by strand deposition process (SDP), and investigated for their properties, primarily their Poisson's ratio. The Poisson's ratio was determined and the influence of the material on it was identified. A specific number of 5 × 5 unit cells has been found to be ideal for investigation. Dual printed specimens showed a similar auxetic behavior as the specimens made of pure PBAT. Likewise, multiple loading and unloading of the structure is possible. Furthermore, in-situ computed tomography revealed the detailed characterization of the initial state, including the warpage of the structures, damage, and traced auxetic behavior in detail. [ABSTRACT FROM AUTHOR]

A comprehensive approach to understand the mechanical behavior of materials involves costly and time-consuming experiments. Recent advances in machine learning and in the field of computational material science could significantly reduce the need for experiments by enabling the prediction of a material's mechanical behavior. In this paper, a reliable data pipeline consisting of experimentally validated phase field simulations and finite element analysis was created to generate a dataset of dual-phase steel microstructures and mechanical behaviors under different heat treatment conditions. Afterwards, a deep learning-based method was presented, which was the hybridization of two well-known transfer-learning approaches, ResNet50 and VGG16. Hyper parameter optimization (HPO) and fine-tuning were also implemented to train and boost both methods for the hybrid network. By fusing the hybrid model and the feature extractor, the dual-phase steels' yield stress, ultimate stress, and fracture strain under new treatment conditions were predicted with an error of less than 1%. [ABSTRACT FROM AUTHOR]

Interfacial bonding of three different semi-coherent bcc-Fe(110)/graphene interfaces is investigated using the plane-wave pseudopotential method within density functional theory. The analysis of bond lengths, charge densities, charge transfer, magnetic moments and densities of states shows that interfacial adhesion can be understood from the electronic structure. Graphene is considered on Fe(110) surfaces as well as embedded in (110) planes of bulk Fe. Moreover, the influence of single vacancies in graphene is studied in case of graphene on the Fe(110) surfaces. It is found that a single vacancy in graphene leads to a strong increase of interfacial adhesion. The most important contribution to the adhesion is covalent bonding with hybridization of Fe states and C states which is most pronounced for neighboring atoms of the vacancy. [Display omitted] • bcc-Fe(110)/graphene interfaces exhibit strong adhesion due to covalent Fe–C bonds. • Single vacancies in graphene lead to a strong increase of adhesion. • Large magnetic moments are induced at C atoms neighboring a single vacancy. [ABSTRACT FROM AUTHOR]

The current work numerically investigates commercial polycrystalline Ag/17vol.%SnO 2 composite tensile deformation behavior with available experimental data. Such composites are useful for electric contacts and have a highly textured initial material status after hot extrusion. Experimentally, the initial sharp fiber texture and the number of Σ 3-twins were reduced due to tensile loading. The local inhomogeneous distribution of hardness and Young's modulus gradually decreased from nanoindentation tests, approaching global homogeneity. Many-scale simulations, including micro-macro simultaneous finite element (FE) and discrete dislocation dynamics (DDD) simulations, were performed. Deformation mechanisms on the microscale are fundamental since they link those on the macro- and nanoscale. This work emphasizes micromechanical deformation behavior. Such FE calculations applied with crystal plasticity can predict local feature evolutions in detail, such as texture, morphology, and stress flow in individual grains. To avoid the negative influence of boundary conditions (BCs) on the result accuracy, BCs are given on the macrostructure, i.e., the microstructure is free of BCs. The particular type of 3D simulation, axisymmetry, is preferred, in which a 2D real microstructural cutout with 513 Ag grains is applied. From FE results, Σ 3-twins strongly rotated to the loading direction (twins disappear), which, possibly, caused other grains to rotate away from the loading direction. The DDD simulation treats the dislocations as discrete lines and can predict the resolved shear stress (RSS) inside one grain with dependence on various features as dislocation density and lattice orientation. The RSS can act as the link between the FE and DDD predictions. [ABSTRACT FROM AUTHOR]

Our work investigates the polycrystalline composite deformation behavior through multiscale simulations with experimental data at hand. Since deformation mechanisms on the micro-level link the ones on the macro-level and the nanoscale, it is preferable to perform micromechanical finite element simulations based on real microstructures. The image segmentation is a necessary step for the meshing. Our 2D EBSD images contain at least a few hundred grains. Machine learning (ML) was adopted to automatically identify subregions, i.e., individual grains, to improve local feature extraction efficiency and accuracy. Denoising in preprocessing and postprocessing before and after ML, respectively, is beneficial in high quality feature identification. The ML algorithms used were self-developed with the usage of inherent code packages (Python). The performances of the three supervised ML models—decision tree, random forest, and support vector machine—are compared herein; the latter two achieved accuracies of up to 99.8%. Calculations took about 0.5 h from the original input dataset (EBSD image) to the final output (segmented image) running on a personal computer (CPU: 3.6 GHz). For a realizable manual pixel sortation, the original image was firstly scaled from the initial resolution 1080 2 pixels down to 300 2 . After ML, some manual work was necessary due to the remaining noises to achieve the final image status ready for meshing. The ML process, including this manual work time, improved efficiency by a factor of about 24 compared to a purely manual process. Simultaneously, ML minimized the geometrical deviation between the identified and original features, since it used the original resolution. For serial work, the time efficiency would be enhanced multiplicatively. [ABSTRACT FROM AUTHOR]

This paper addresses the damage behaviour of a nickel/yttria-stabilised zirconia (Ni-YSZ) anode, in order to understand microstructural degradation processes of Solid Oxide Fuel Cells (SOFCs) during long-term operation. Numerical investigations are carried out to analyse the failure mechanisms in detail. For this purpose, finite element (FE) models are generated from focused ion beam-scanning electron microscopy 3D image data, representing the anode microstructure with varying phase compositions. A brittle model and a ductile material model were assigned to the YSZ phase and the nickel phase, respectively. The porosity is found to affect the strength of the microstructure significantly, leading to low compressive strength results. A high Ni content generally increases the toughness of the overall structure. However, the orientation and the geometry of the nickel phase is essential. When the Ni phase is aligned parallel to the loading direction, a supporting effect on the microstructure is observed, resulting in a significant high toughness. On the contrary, a rapid failure of the sample occurs when the Ni phase is oriented perpendicular to the loading direction. Two main failure mechanisms are identified: (i) cracking at the Ni/YSZ interface and (ii) cracking of struts at the location of the smallest diameter. [ABSTRACT FROM AUTHOR]

In rock-like materials, mode I and II fracture toughness are distinctive while the compressive strength is much greater than the tensile strength. Besides, mixed-mode fractures instead of pure mode I or II fractures occur under complicated load cases in those materials. Therefore, to capture the mixed-mode cracking process, we developed a mixed-mode phase-field cohesive zone model based on the unified phase-field theory proposed by Wu. The model was built based on a strain energy decomposition scheme and the softening behavior of each mode is controlled by an independent degradation function. Thus, independent values of strength and toughness can be given for different failure modes simultaneously. A simple mixture rule of fracture toughness was introduced to describe the transition between different failure modes. The model can keep variational consistency perfectly and governing equations for displacement- and phase-field, which was never reported in other works. Several numerical examples verified the effectiveness and flexibility of this work. The present work showed a simple but effective way to simulate mixed-mode fracture. • A modified phase-field cohesive zone model is developed for mixed-mode fracture. • A simple mixture rule is utilized to describe the transition between each fracture mode. • The present model can keep the variational consistency perfectly. • Several numerical cases verify the present model. [ABSTRACT FROM AUTHOR]

• B substitution of a C atom increases the work of separation on the Fe(110) surface. • There is almost no effect of N on the graphene/Fe(110) interface. • B and N impurities affect the charge states of the nearest C atoms. • Impurities influence on the magnetic state of the nearest Fe atoms. Influence of B and N substitutional impurities on the adhesion properties, electronic and magnetic characteristics of the external and internal graphene/Fe(110) semi-coherent interface was investigated by the projector augmented-wave method within the density functional theory. The analysis of interatomic distances, charge densities, charge transfer and magnetic states of atoms was performed. It was shown that B-doped graphene has a higher adhesion energy on the Fe(110) surface and in the iron bulk in comparison with the undoped systems; whereas, N-doped graphene in the Fe bulk demonstrates the opposite trend and on the surface it has no effect. Boron acts as electron donor that increases charges of the nearest C atoms by 0.5–0.6 e. Nitrogen due to its high electronegativity is an acceptor and as a result the nearest C atoms lose 0.2–0.3 e. Both impurities, depending on the position, influence differently on the magnetic moment of the nearest iron atoms. [Display omitted] [ABSTRACT FROM AUTHOR]

To gain a deeper insight into the anomalous yield behavior of Ni 3 Al, it is essential to obtain temperature-dependent formation Gibbs energies of the relevant planar defects. Here, the Gibbs energy of the complex stacking fault (CSF) is evaluated using a recently proposed ab initio framework [Acta Materialia, 255 (2023) 118986], accounting for all thermal contributions—including anharmonicity and paramagnetism—up to the melting point. The CSF energy shows a moderate decrease from 300 K to about 1200 K, followed by a stronger drop. We demonstrate the necessity to carefully consider the individual thermal excitations. We also propose a way to analyze the origin of the significant anharmonic contribution to the CSF energy through atomic pair distributions at the CSF plane. With the newly available high-temperature CSF data, an increasing contribution to the energy barrier for the cross-slip process in Ni 3 Al with increasing temperature is unveiled, necessitating the refinement of existing analytical models. [ABSTRACT FROM AUTHOR]

Binary complexes that can be found in copper alloys are investigated in this work through a combination of computer simulations and machine learning. Copper alloys are made of a copper matrix and a combination of single alloying elements in n -ary forms. Due to the coexistence of different types of phases in this matrix, complex regions exist for which information on their precise atomistic structure is missing. In order to uncover such information, we apply active learning and generate moment tensor potentials. This development is based on quantum-mechanical calculations. This approach allows the on-the-fly relaxation of many thousands of potentially novel candidates and check their stability. The ground-state energy of these structures is used to build active learning-generated convex hulls, which are in turn being compared to those from the simulations and the AFLOW database. This procedure provides an insight to additional new stable copper alloy relevant binary complexes. Here, in view of Cu–Ni–Si–Cr alloys, the binary complexes Cu–Si, Ni–Si, Cr–Si, Cr–Ni, Cu–Ni, and Cu–Cr have been investigated. Their stability and the identification of novel stable candidates are discussed based on energetic arguments and the analysis of the respective phonon dispersion. The pipeline followed in this work is able to successfully predict binary phases in Cu–Ni–Si–Cr alloys, specifically for the Cu-Si, Ni–Si, Cr–Ni and Cu–Ni complexes, and to extend the already reported structures in the AFLOW library. In the end, we show the applicability of a predicted Cu–Si stable phase and the developed machine learned potentials at the larger scale of atomistic simulations for the calculation of their mechanical properties and melting behavior. This work provides a computationally efficient framework for material structure prediction and calculation of their properties at a quantum-mechanical accuracy. • Efficient discovery of new binary phases of Cu-Ni-Si-Cr alloys. • Active learning training of moment tensor potentials. • Generation of machine-learned potentials with quantum-mechanical accuracy. [ABSTRACT FROM AUTHOR]

Antiphase boundaries (APBs) are crucial to understand the anomalous temperature dependence of the yield stress of Ni 3 Al. However, the required, accurate prediction of temperature-dependent APB energies has been missing. In particular, the impact of magnetism at elevated temperatures has been mostly neglected, based on the argument that Ni 3 Al is a weak ferromagnet. Here, we show that this is an inappropriate assumption and that – in addition to anharmonic and electronic excitations – thermally-induced magnetic spin fluctuations strongly affect the APB energies, especially for the (100)APB with an increase of nearly up to 40% over the nonmagnetic data. We utilize an ab initio framework that incorporates explicit lattice vibrations, electronic excitations, and the impact of magnetic excitations up to the melting temperature. Our results prompt to take full account of thermally-induced spin fluctuations even for weak itinerant ferromagnetic materials. Consequences for large-scale modeling in Ni-based superalloys, e.g., of dislocations or the elastic–plastic behavior, can be expected. [Display omitted] [ABSTRACT FROM AUTHOR]

In order to contribute to the understanding of advanced materials with improved mechanical properties we investigate strengthening and failure processes in iron-graphene composites using molecular dynamics simulations. Graphene sheets are embedded in {110} planes of bulk iron. Tensile tests and shear tests are conducted and evaluated with regard to the orientation of the graphene sheet. It is found that two different failure mechanisms involving interfacial fracture and dislocation nucleation can occur due to tensile load. The shear tests revealed three mechanisms of dislocation-obstacle interaction. The highest strengthening was found for graphene sheet orientations which normal vectors are not orthogonal to the Burgers vector of the interacting dislocation. [Display omitted] • Graphene sheet orientation significantly affects failure and strengthening • High CRSS and low UTS with non zero components in tensile and shear direction • Dislocation interaction with graphene is mostly cutting of the matrix • Cutting results in folding, straining and rotation of the sheet. [ABSTRACT FROM AUTHOR]

[Display omitted] • Interfacial debonding of a porous TBC system is studied via SEM image-based FE analysis. • Microstructural pores of SEM image of TBC sample are imported into FE software via CMM. • Pores of TC force the stress to be concentrated adjacent to rough TC/TGO interface and develop TC/TGO interface damage. • Porosity within the BC diminishes stress and damage values along the TGO/BC interface. • Creep leads to stress relaxation of TC up to 24.82 % and lowers the damage level of TGO/BC interface. Numerical analysis of interfacial delamination and the effect of microstructural pores and rough interfaces on the field variables in thermal barrier coatings (TBCs) based on a real scanning electron microscope (SEM) image is performed. The interfacial delamination is modelled by the utilization of cohesive zone method (CZM) in finite element (FE) analysis. The empirical TBC sample considered in this study is constructed via air plasma spray (APS) method and comprises ZrO 2 7 - 8 wt. % Y 2 O 3 ceramic top coat (TC), thermally grown oxide (TGO) made of Al 2 O 3 and NiCrAlY metallic bond coat (BC). A compatible geometry is provided by applying image processing technique to SEM image of the sample's cross-section. SEM image-based geometry imported into FE software to scrutinize the interplay effects of porosity and rough interfaces on temperature fields, thermal stresses and interfacial debonding of TC/TGO and TGO/BC interfaces of the TBC structure. FE analysis reveal that porosity distribution has a prominent role on the stress concentration zones at the sharp corners of pores especially adjacent to undulations of the TC/TGO interface, which is responsible for possible internal cracks and interfacial fracture, respectively. The main findings demonstrate that the porosity near the TC/TGO interface has detrimental effect as leads to aggravation in the TC/TGO interface damage, which causes an increment in TC/TGO interfacial crack length. While, the porosity within the BC has the ability to reduce the stress and damage level along the TGO/BC interface. In addition, considering creep for all layers leads to lower stress levels up to 24.82 % and consequently alleviates the TC/TGO interface damage. [ABSTRACT FROM AUTHOR]

• The physically based TM formulation is a promising numerical method to predict the fatigue short crack initiation, specially for the stent components. • By implementing the current numerical method we can predict the time before the nucleation of the first micro-cracks within the stent components. Most of the micro-components, such as coronary stents, consist of an oligo-crystalline micro-structure. This means that the detection of the few coarse grains which are columnar and parallel to the longitudinal ingot axis is possible. The deformation behavior of such micro-structures is obviously different from polycrystalline materials, since the anisotropic properties of one grain, in relation to its nearest neighbors should be considered. The goal of this study is the simulation of the crack initiation process under a cyclic loading situation in the oligo-crystalline micro-structure of the stent component made of X2CrNiMo-18-15-3. The crack initiation process is simulated employing the physically-based Tanaka-Mura model implemented in Finite Element Method (FEM). The available experimental result data have also been used as the input parameters to the current modelling approach. In this regard the grain size and the grain orientation are changed, and their effect together with the influence of the surface roughness on the fatigue life of the stent components has been studied. [ABSTRACT FROM AUTHOR]

[Display omitted] • Strategy for bridging microscopic and macroscopic crack-growth simulation proposed. • The multiscale model and the concept of the bridging method are integrated. • Reduction of more than 90% in the numerical costs compared to multiscale model. • Accurate and efficient prediction of fatigue life/limit and crack-growth processes. • Can evaluate fatigue failure behaviour of thick components/structures. A strategy for bridging microscopic and macroscopic crack-growth simulations is proposed for efficiently and accurately predicting the fatigue strength of steels by integrating the multiscale model and the concept of the bridging method. Validation by comparing the experimental results of macro-crack specimens and the numerical results of the multiscale model shows a reduction of more than 90% in the numerical costs with the proposed strategy compared to the multiscale model. Only 4.2% and 2.7% errors in fatigue life for the two macro-crack specimens under the maximum loading cases are achieved, whereas no errors in fatigue limits are observed using the proposed strategy, compared to the multiscale model. The accuracy and efficiency of predicted results indicate that the proposed strategy can serve as a robust foundation for evaluating the fatigue failure behaviour of thick components/structures in engineering applications. [ABSTRACT FROM AUTHOR]

• The interface crack between two dissimilar quasicrystal materials. • The gradient theory of thermoelasticity for quasicrystals. • The gradient theory for heat conduction problem. • Decagonal quasicrystal properties. • The mixed FEM formulation with C0 continuous finite elements for independent approximations of displacements and strains. The interface crack problem between two dissimilar materials under a thermal load is analyzed by the gradient elasticity theory since the size effect is expected in the very thin quasicrystal layer. The uncoupled thermoelasticity is considered here, where the thermal fields are independent on mechanical ones. The thermal transport can't be well described by classical Fourier's law in nano-sized structures. Therefore, a novel gradient theory is developed in such structures, where the second derivatives of temperature in the constitutive equation for the high-order heat flux are considered. Moreover, the phonon strain gradients are incorporated into the higher-grade continuum model. Decagonal quasicrystal material properties are considered here. Governing equations and corresponding boundary conditions are derived from the principle of virtual work. The mixed finite element method (MFEM) is developed for a general 2D boundary value problem. Numerical examples are presented to illustrate the phonon, phason and thermal response to external thermal loading within the considered model. [ABSTRACT FROM AUTHOR]

The curing behavior of a thermosetting material that influences the properties of the material is a key issue for predicting the changes in material properties during processing. An empirical equation can describe the reaction kinetics of the curing behavior of an investigated material, which is usually estimated using experimental methods. In this study, the curing process of an epoxy resin, the polymer matrix in an epoxy molding compound, is computed concerning thermal influence using molecular dynamics. Furthermore, the accelerated reaction kinetics, which are influenced by an increased reaction cutoff distance, are investigated. As a result, the simulated crosslink density with various cutoff distances increases to plateau at a crosslink density of approx. 90% for the investigated temperatures during curing time. The reaction kinetics are derived according to the numerical results and compared with the results using experimental methods (dielectric analysis and differential scanning calorimetry), whereby the comparison shows a good agreement between experiment and simulation. [ABSTRACT FROM AUTHOR]

Commercial Co/WC/diamond composites are hard metals and very useful as a kind of tool material, for which both ductile and quasi-brittle behaviors are possible. This work experimentally investigates their damage evolution dependence on microstructural features. The current study investigates a different type of Co/WC-type tool material which contains 90 vol.% Co instead of the usual <50 vol.%. The studied composites showed quasi-brittle behavior. An in-house-designed testing machine realizes the in-situ micro-computed tomography (μ CT) under loading. This advanced equipment can record local damage in 3D during the loading. The digital image correlation technique delivers local displacement/strain maps in 2D and 3D based on tomographic images. As shown by nanoindentation tests, matrix regions near diamond particles do not possess higher hardness values than other regions. Since local positions with high stress are often coincident with those with high strain, diamonds, which aim to achieve composites with high hardnesses, contribute to the strength less than the WC phase. Samples that illustrated quasi-brittle behavior possess about 100–130 MPa higher tensile strengths than those with ductile behavior. Voids and their connections (forming mini/small cracks) dominant the detected damages, which means void initiation, growth, and coalescence should be the damage mechanisms. The void appears in the form of debonding. Still, it is uncovered that debonding between Co-diamonds plays a major role in provoking fatal fractures for composites with quasi-brittle behavior. An optimized microstructure should avoid diamond clusters and their local volume concentrations. To improve the time efficiency and the object-identification accuracy in μ CT image segmentation, machine learning (ML), U-Net in the convolutional neural network (deep learning), is applied. This method takes only about 40 min to segment more than 700 images, i.e., a great improvement of the time efficiency compared to the manual work and the accuracy maintained. The results mentioned above demonstrate knowledge about the strengthening and damage mechanisms for Co/WC/diamond composites with >50 vol.% Co. The material properties for such tool materials (>50 vol.% Co) is rarely published until now. Efforts made in the ML part contribute to the realization of autonomous processing procedures in big-data-driven science applied in materials science. [ABSTRACT FROM AUTHOR]