Search

Microstructure—property relationships are key to effective design of structural materials for advanced applications. Advances in computational methods enabled modeling microstructure-sensitive properties using 3D models (e.g., finite elements) based on microstructure representative volumes. 3D microstructure data required as input to these models are typically obtained from either 3D characterization experiments or digital reconstruction based on statistics from 2D microstructure images. In this work, we present machine learning (ML) approaches to modeling effective properties of heterogeneous materials directly from 2D microstructure sections. To this end, we consider statistical learning models based on spatial correlations and convolutional neural networks as two distinct ML strategies. In both strategies, models are trained on a dataset of synthetically generated 3D microstructures and their properties obtained from micromechanical 3D simulations. Upon training, the models predict properties from 2D microstructure sections. The advantage of the presented models is that they only need 2D sections, whose experimental acquisition is more accessible compared to 3D characterization. Furthermore, the present models do not require digital reconstruction of 3D microstructures.

The microstructural origins of highly localized elastic strain concentrations in polycrystalline microstructures under monotonic loading are studied using grain-scale, in situ digital image correlation and crystal plasticity finite element method. It is shown that the locations of exceptionally high elastic strain concentrations in the microstructure depend on particular crystallographic and morphological orientations of grains and less so on crystalline details of their local neighborhood. Based on these results, we discuss how topological and crystallographic features of annealing twin boundaries can increase the likelihood of slip band initiation throughout the microstructure of polycrystalline Ni-base superalloys.

Accelerating the design and development of new advanced materials is one of the priorities in modern materials science. These efforts are critically dependent on the development of comprehensive materials cyberinfrastructures which enable efficient data storage, management, sharing, and collaboration as well as integration of computational tools that help establish processing–structure–property relationships. In this contribution, we present implementation of such computational tools into a cloud-based platform called BisQue (Kvilekval et al., Bioinformatics 26(4):554, 2010). We first describe the current state of BisQue as an open-source platform for multidisciplinary research in the cloud and its potential for 3D materials science. We then demonstrate how new computational tools, primarily aimed at processing–structure–property relationships, can be implemented into the system. Specifically, in this work, we develop a module for BisQue that enables microstructure-sensitive predictions of effective yield strength of two-phase materials. Towards this end, we present an implementation of a computationally efficient data-driven model into the BisQue platform. The new module is made available online (web address: https://bisque.ece.ucsb.edu/module_service/Composite_Strength/) and can be used from a web browser without any special software and with minimal computational requirements on the user end. The capabilities of the module for rapid property screening are demonstrated in case studies with two different methodologies based on datasets containing 3D microstructure information from (i) synthetic generation and (ii) sampling large 3D volumes obtained in experiments.

A microstructure analytics and 3D reconstruction software package, DREAM.3D, was integrated as a module into a cloud-based platform, BisQue. Parallelization of DREAM.3D module executions and the ability to parameterize pipeline variables over a range of values have led to insights about the grain segmentation misorientation tolerance in TriBeam-collected 3D EBSD datasets of additively manufactured materials with complex anisotropic microstructures. Furthermore, a comparison in grain size measurements was made between standard 2D metallographic slices and 3D measures using BisQue’s parallelized DREAM.3D module executions. The direction of cloud-based data infrastructure and the prospects for impact in material science are also discussed.

Quantification of mesoscale microstructures of polycrystalline materials is important for a range of practical tasks of materials design and development. The current protocols of quantifying grain size and morphology often rely on microstructure metrics (e.g., mean grain diameter) that overlook important details of the mesostructure. In this work, we present a quantification framework based on directionally resolved chord length distribution and principal component analysis as a means of extracting additional information from 2-D microstructural maps. Towards this end, we first present in detail a method for calculating chord length distribution based on boundary segments available in modern digital datasets (e.g., from microscopy post-processing) and their low-rank representations by principal component analysis. The utility of the proposed framework for capturing grain size, morphology, and their anisotropy for efficient visualization, representation, and specification of polycrystalline microstructures is then demonstrated in case studies on datasets from synthetic generation, experiments (on Ni-base superalloys), and simulations (on steel during recrystallization).

In this work, uniaxial compression of nano/submicropillars in Au with the initial diameter D between 26.05 and 158.53 nm was modelled by concurrent atomistic-continuum simulations. Two mode...

The role of microstructure and strain rate on the development of geometrically necessary dislocation (GND) density in polycrystalline copper subjected to compression is assessed via crystal plasticity modelling and electron microscopy. Micropolar crystal plasticity finite element (MP-CPFE) simulations show that GND density is strongly dependent on crystal orientation, with the highest values in grains with a direction parallel to the compression axis. Experimental analysis shows that this relationship breaks down and demonstrates that orientation is only one of many microstructural features that contributes to dislocation density evolution. Texture development as a function of strain rate is also considered, and it is found that the commonly observed compression texture is delocalized from that pole at high strain rate. Furthermore, quantitative analysis of the role of grain boundaries in GND density evolution highlights their role as strong dislocation sources.

A composite made of two phases is considered with a perfect disorder of the phases, and isotropic behavior. The strain hardening behavior of such a composite is modeled under axisymmetric tension. The approach is based on using the strain hardening behavior of the two constituent phases together with a relation between the plastic energy of the two phases. The newly developed analytical model was applied to several dual-phase steel alloys and on iron-silver composite metal. These case studies revealed that the equal-power approach reproduces faithfully the strain hardening behavior of the composite, together with the strain partitioning between the two phases, in good agreement with experiments.

In this work, we investigate the relationship between an intense slip band (ISB) and the zone of large lattice rotations that forms ahead of the tip of the ISB. We develop a crystal plasticity finite element model of a discrete ISB lying within an oligocrystalline assembly and calculate the local crystalline stress and lattice rotation fields generated by the ISB. The calculations demonstrate that, first, a region of severe lattice rotations, commonly referred to as a microvolume, does not form without the ISB, and second, large amounts of accumulated slip in the ISB are required to enlarge the microvolume to sizes and rotation magnitudes observed experimentally. Ahead of the ISB tip, the quintessential plastic zone always forms, but the atypical microvolume forms when non-concentrated and spatially diffuse slip is activated by the ISB-induced stress field. This result suggests that the detrimental ISB/microvolume pair will likely appear in pairs of crystals in which transmission of the slip from the ISB is severely blocked by the grain boundary, a hypothesis that we verify with a few target cases.

There is a critical need for the development and verification of practically useful multiscale modeling strategies for simulating the mechanical response of multiphase metallic materials with heterogeneous microstructures. In this contribution, we present data-driven reduced order models for effective yield strength and strain partitioning in such microstructures. These models are built employing the recently developed framework of Materials Knowledge Systems that employ 2-point spatial correlations (or 2-point statistics) for the quantification of the heterostructures and principal component analyses for their low-dimensional representation. The models are calibrated to a large collection of finite element (FE) results obtained for a diverse range of microstructures with various sizes, shapes, and volume fractions of the phases. The performance of the models is evaluated by comparing the predictions of yield strength and strain partitioning in two-phase materials with the corresponding predictions from a classical self-consistent model as well as results of full-field FE simulations. The reduced-order models developed in this work show an excellent combination of accuracy and computational efficiency, and therefore present an important advance towards computationally efficient microstructure-sensitive multiscale modeling frameworks.

In the present contribution, a phenomenological constitutive model of medium manganese steels, in which both twinning-induced (TWIP) and transformation-induced (TRIP) plasticity enhancing mechanisms are activated, is implemented in the finite element framework. The implementation is utilized for the analysis of the full-field strain partitioning in dual-phase microstructure maps obtained from electron backscattering diffraction. The results of the finite element analysis suggest that the strain localization in the studied steel has an alternating character. Specifically, in the low strain region, most of the externally imposed deformation is accommodated by the initially softer austenite. The higher strain hardening rate of austenite due to deformation twinning (TWIP effect) and the mechanically-induced transformation to martensite (TRIP effect) results in a shift of the strain localization to ferrite. This alternating strain localization is a key feature that distinguishes the medium manganese TWIP+TRIP steel. It is shown that this alternating strain localization contributes to the superior mechanical behavior of medium manganese TWIP+TRIP steel reported in the literature.

In this contribution, we present a new Materials Knowledge System framework for microstructure-sensitive predictions of effective stress--strain responses in composite materials. The model is developed for composites with a wide range of combinations of strain hardening laws and topologies of the constituents. The theoretical foundation of the model is inspired by statistical continuum theories, leveraged by mean-field approximation of self-consistent models, and calibrated to data obtained from micromechanical finite element simulations. The model also relies on newly formulated data-driven linkages between micromechanical responses (phase-average strain rates and effective strength) and microstructure as well as strength contrast of the constituents. The paper describes in detail the theoretical development of the model, its implementation into an efficient computational plasticity framework, calibration of the linkages, and demonstration of the model predictions on two-phase composites with isotropic constituents exhibiting linear and power-law strain hardening laws. It is shown that the model reproduces finite element results reasonably well with significant savings of the computational cost., 39 pages, 5 figures

Twist extrusion (TE) is a severe plastic deformation method with a potential for commercialization. Deformation during the TE process is non-uniform and non-monotonic, which is expected to result in significant and non-trivial microstructural changes in metallic materials. In this study, texture evolution during TE of pre-textured copper was investigated. Experimental characterization of textures after various numbers of passes demonstrated that TE can be used for producing uniformly weak textures in pre-textured copper. Crystal plasticity simulations were found to run into the problem known as strain reversal texture. In particular, crystal plasticity simulations predicted the return of initial texture upon strain reversal in the first pass of TE, whereas the experimental texture was not reversed and had components related to simple shear. Grain refinement, imperfect strain reversal, and material asymmetry are proposed to be responsible for the occurrence of strain reversal texture in TE. Effects of the non-random initial texture on the microstructure and texture evolution are also discussed.

The local microtexture developments of Cu near the interface of Al-core/Cu-sheath composites during multi-pass caliber rolling are investigated using the finite element method in conjunction with a visco-plastic self-consistent model. Two models with different interfacial conditions between Al and Cu are used in order to investigate the effect of the interfacial condition. The resulting inverse pole figures and difference in ODFs for the different numbers of caliber rolling passes indicate that the Coulomb frictional contact condition between Al and Cu represents the final microtextures better than the fully bonded interfacial condition. Keywords: Caliber rolling, Core/sheath composite, Interface texture, Finite element method, Visco-plastic self-consistent model

The present paper introduces a twist extrusion (TE) process capable of processing of round bars with uniform deformation and reports physical, analytical, and numerical modeling of the process. It is shown that the ability to treat round bars can be achieved by design of special off-axis TE dies in which the axis of the twist surface is displaced from the central axis of the bar being processed. Physical modeling conducted in the current study with plasticine demonstrates the feasibility of off-axis TE. A marker insert technique employed in the physical model reveals that tool-controlled flow (ideal helical flow) of the material is dominant in the process. Analytical model developed in the present study explains why using off-axis TE dies leads to uniform deformation and how this deformation uniformity depends on the die geometry. The main conclusions made upon analytical modeling are confirmed with complement finite element simulations. The simulations also show that the main deformation mode in off-axis TE is simple shear at the intersection planes between the twist and the straight channels of the die.

The paper presents a new route for realizing the concept of architecturing of composites by severe plastic deformation. The proposed route involves multi-pass twist extrusion of a composite with fibers. The potential of the method is first illustrated by mathematical modeling and then tested through pilot processing of a composite consisting of a copper matrix and a single aluminum fiber. Metallographic analysis revealed an unexpected shape of the fiber after processing. Finite element simulations were performed to understand the evolution of the fiber shape and to optimize the processing regime for achieving improved reinforcements in twist-extruded composites.

Twist extrusion (TE) is a severe plastic deformation method with a potential for commercialization. Advancing TE toward industrial use requires in-depth understanding of deformation during the process and its dependence on processing factors. The helical flow model introduced with the concept of TE provides for a concise description of deformation in the process. To date, however, it was unclear under which conditions the helical flow model yields accurate predictions of deformation in TE. This paper presents a systematic finite-element study performed to identify effects of some key process and material factors on deformation in TE and its departure from the ideal deformation described by the helical flow model. It was found that high strain-hardening rate and friction lead to violations of the assumptions of the helical flow model and that these violations result in departure from the ideal deformation. Deviations from the ideal deformation tend to increase on decreasing the length of the twist channel. Friction effects appear especially critical to be considered for accurate prediction of deformation in TE. Finite-element simulations taking friction into account show good qualitative agreement with earlier marker-insert experiments. The results of the present finite-element study allowed for defining the simple shear model of TE.

In this study, porous titanium samples were manufactured by a space holder method with sodium chloride. Each porous titanium sample contained two types of pores based on their sizes: macropores and micropores. Macropores were those emerged from removing the space holder, whereas micropores were voids created during powder compaction. The porous titanium exhibited low elastic modulus close to that of the human bone. Computed tomography (CT) was employed to examine the porous structure of the Ti samples. The CT results were then used in finite element simulations for analysis of the mechanical behavior of the porous titanium. The CT-based finite element model was found to give better results compared to the unit-cell finite element model in terms of agreement with the experimental data. The CT model combined with the strain hardening behavior of Ti having micropores prescribed to the matrix allowed for accurate predictions of elastic modulus, yield strength, and flow stress. These results signify the importance of taking into account pores at different scales as well as their morphology and distribution at least at macroscale.

Deformation twinning from grain boundaries is often observed in face-centered cubic metals with low stacking fault energy. One of the possible factors that contribute to twinning origination from grain boundaries is the intergranular interactions during deformation. Nonetheless, the influence of mechanical interaction among grains on twin evolution has not been fully understood. In spite of extensive experimental and modeling efforts on correlating microstructural features with their twinning behavior, a clear relation among the large aggregate of grains is still lacking. In this work, we characterize the micromechanics of grain-to-grain interactions that contribute to twin evolution by investigating the mechanical twins near grain boundaries using a full-field crystal plasticity simulation of a twinning-induced plasticity steel deformed in uniaxial tension at room temperature. Microstructures are first observed through electron backscatter diffraction technique to obtain data to reconstruct a statistically equivalent microstructure through synthetic microstructure building. Grain-to-grain micromechanical response is analyzed to assess the collective twinning behavior of the microstructural volume element under tensile deformation. Examination of the simulated results reveal that grain interactions are capable of changing the local mechanical behavior near grain boundaries by transferring strain across grain boundary or localizing strain near grain boundary. Grains that should not favour twin formation exhibit twinning as a result of surrounding grains acting on their boundaries. A team led by HyoungSeop Kim at the Pohang University of Science and Technology in the Republic of Korea simulated the deformation of synthetic metallic microstructures with many grains of different orientations, based on steels that deform by both dislocation slip and twinning mechanisms. Twinning first started near grain boundaries and depended on initial grain orientation but, with further deformation, strong twin activity on one side of a boundary triggered strong twin activity on the other side of that boundary. This happened even when the grain on the other side of the boundary was unfavourable to twinning. Taking into account grain neighbourhood may therefore help in optimising twin-forming alloys.

Plastic deformation behavior and microstructural evolution of an Al-core/Cu-sheath composite during multi-pass caliber rolling are investigated using the finite element simulations and experimental analyses. The simulated equivalent plastic strains generated by 1 to 7 pass caliber rolling are correlated with the hardness values and microstructures measured in the longitudinal cross sections of the specimens. The average strains developed in the Al-core and Cu-sheath are almost identical, which satisfy the quasi-isostrain condition in composites with inner soft and outer hard materials. Both the Al-core and Cu-sheath exhibit increasing hardness, but decreasing hardening rates with an increase in the number of passes. The increasing hardness with an increase in the number of caliber rolling passes is attributable to the combined effect of increased dislocation density and decreased grain size. The simulated results for the hardness were shown to be in good agreement with the experimental data for Cu and Al. It was concluded that the finite element method is well placed as a tool for describing and predicting deformation behaviors during caliber rolling.

We present a computational framework for multiscale forward modeling of ultrasound resonance in heterogeneous materials that accounts for microstructure. The approach includes two steps. The first step is the accurate determination of the elastic properties of heterogeneous materials with finite element simulations on a representative volume element of the microstructure at the mesoscopic length scale. The second step is modeling resonance frequencies of a macroscopic component made of an effective homogeneous medium having the same elastic properties as the actual material with microstructure. The approach is validated in a case study on a Cu–W two-phase composite, for which resonance frequencies predicted with the proposed framework are compared against the experimental measurements. The present multiscale modeling approach, involving computational homogenization and leveraging 3D microstructure data, showed better accuracy compared to classical Voigt/Reuss bounds often used for forward modeling of resonant ultrasound spectroscopy.

This letter introduces a method for designing hierarchical cellular metals employing multipass accumulative bundle extrusion and selective dissolving. The method provides several degrees of freedom for manipulating both the cell-wall properties and architecture of cellular materials. Cellular copper was produced and analyzed as an example of implementing the proposed method. The material hierarchy that can be formed and controlled by means of multipass accumulative extrusion assures strength and enables the material to perform the prescribed functions.

Upon intensive investigation during the recent years, severe plastic deformation (SPD) has been commonly accepted as a strong tool for improving mechanical properties of metallic materials. The interest in commercial use of SPD materials with superior properties addresses the issue of scaling up the SPD methods. In this regard, methods that can provide SPD conditions in billets with large dimensions become of prime interest. Twist extrusion (TE) is such a process, whereby large strains are accumulated owing to repeated extrusion through a die that imposes shearing stresses. Despite a few studies of TE in the literature, many features of the process's nature remain unclear or even unknown. In the current article, we have studied an important effect of TE named “cross flow” that previously received scarce attention. By performing both experiments and simulations, we elucidated the mechanism of the cross flow as well as how it is affected by material properties and process conditions. Since practical significance of the cross flow became apparent, special attention was paid to the problem of control and reliable prediction of the cross flow. Finally, prospective applications of the investigated effect were suggested. Conclusions of the current study are anticipated to contribute to further research on simulation of other simple-shear-based SPD processes.

The present paper deals with numerical comparison of two twist-based severe plastic deformation processes: (i) the elliptical cross-section spiral equal-channel extrusion (ECSEE) proposed recently as a novel process and (ii) the classical twist extrusion (TE). ECSEE was developed in attempt to process cylindrical work pieces and to generate more uniform strain distribution compared to classical TE. However, the present finite element simulations showed that twist zones used in both methods impose identical stress and strain states. Furthermore, the ability of ECSEE to treat cylindrical billets is achieved at the expense of the possibility to perform multi-pass extrusion through the twist zone and it requires higher loads for the overall process of extrusion. [doi:10.2320/matertrans.MH201315]

Twist extrusion (TE), a promising severe plastic deformation (SPD) technique for grain refinement down to ultrafine/nanocrystalline microstructures, was introduced as an attempt to provide large plastic deformation conditions similar to those in high pressure torsion while allowing large workpiece dimensions for industrial applications. As a relatively new SPD technique, TE requires in-depth investigation of its plastic deformation characteristics. The present study investigates the influence of process parameters such as backward pressure and friction on the loading history, the stress/strain states, and the final shape of processed workpieces using the finite element method. The results provide a basis for reasonable decision of processing conditions and also identify prerequisites for studies in formability and fracture of metals subjected to TE.

Basing on the kinetic modeling, the role of microstructure peculiarities in formation of a revealed experimentally high-strength state of the nanostructured Al 6061 (Mg 0.8…1.2, Si 0.4…0.8, Cu 0.15…0.40, Cr 0.15…0.35, Mn 0.15, Fe 0.7, Zn 0.25, Ti 0.15 wt. %) alloy was analyzed, Possible strengthening mechanisms of the alloy subjected to high pressure torsion at room temperature have been considered. It has been shown that the grain size and segregation of Si, Cu and Mg atoms from the solid solution in the grain boundaries area are the main factors that enhance the alloy strength. Conclusions on the deformation mechanisms acting in the considered alloy have been made. They can be helpful for predicting the mechanical properties of materials. Quantitative estimation of the dislocation density, the stress of dislocation strengthening, and the stress of dislocation pinning by Mg atoms has been made.

Twist extrusion (TE) is one of the most popular techniques of severe plastic deformation, aiming at imparting to a material a tailored microstructure and the associated property improvement. The article provides a survey of the literature on the mechanics of TE and the effect it has on the structure, texture, and the attendant properties of various materials, including metals and alloys, powder materials, and polymers. Special emphasis is placed on vortex flow during TE and its hitherto unexplored potential for producing micro- and macrostructures that promise superior properties of the materials. In particular, the possibility of creating novel hybrid materials with chiral inner architecture is demonstrated. The survey is concluded by a presentation of examples of practical applications of TE.

The resistance stability and thermal resistance of phase change memory devices using ∼40 nm diameter Ga-doped In2O3 nanowires (Ga:In2O3 NW) with different Ga-doping concentrations have been investigated. The estimated resistance stability (R(t)/R0 ratio) improves with higher Ga concentration and is dependent on annealing temperature. The extracted thermal resistance (Rth) increases with higher Ga-concentration and thus the power consumption can be reduced by ∼90% for the 11.5% Ga:In2O3 NW, compared to the 2.1% Ga:In2O3 NW. The excellent characteristics of Ga-doped In2O3 nanowire devices offer an avenue to develop low power and reliable phase change random access memory applications.

Phase change random access memory (PCRAM) devices are usually constructed using tellurium based compounds, but efforts to seek other materials providing desirable memory characteristics have continued. We have fabricated PCRAM devices using Ga-doped In2O3 nanowires with three different Ga compositions (Ga/(In+Ga) atomic ratio: 2.1%, 11.5% and 13.0%), and investigated their phase switching properties. The nanowires (∼40 nm in diameter) can be repeatedly switched between crystalline and amorphous phases, and Ga concentration-dependent memory switching behavior in the nanowires was observed with ultra-fast set/reset rates of 80 ns/20 ns, which are faster than for other competitive phase change materials. The observations of fast set/reset rates and two distinct states with a difference in resistance of two to three orders of magnitude appear promising for nonvolatile information storage. Moreover, we found that increasing the Ga concentration can reduce the power consumption and resistance drift; however, too high a level of Ga doping may cause difficulty in achieving the phase transition.