This work discusses the microstructure evolution observed in a quenching and partitioning (Q&P)-processed martensite/austenite stainless steel during the partitioning step at 400 °C for 300 s, where distinct microstructural bands rich in austenite due to elemental segregation, evolve into a uniform distribution of austenite grains. This phenomenon is characterised and investigated using a model for the carbon partitioning from martensite to austenite coupled with the movement of the martensite-austenite interface. The observed elimination of microstructural bands is found to be related to the topological distribution of austenite grains and the heterogeneity of the thermodynamic equilibrium regime at the various interfaces governing the partitioning process. Furthermore, the concurrence of banding elimination (local equilibrium) and phase growth towards the global equilibrium phase fractions is investigated in the simulations in terms of the role of Mn. It is found that the local equilibrium-negligible partitioning (LENP) conditions lead to the most realistic outcome.

This work investigates the formation of the recrystallisation microstructure and texture of various single-phase ferrite low-carbon steels that were rolled at different temperatures and of which the deformation microstructure was characterized by high resolution electron backscatter diffraction (EBSD). Three cases are considered: (i) cold-rolled interstitial-free (IF) steel, warm-rolled IF steel at 550 °C and warm rolled Fe-Si steel at 900 °C (below the austenitization temperature due to Si). It is well-known that the deformation texture after flat rolling of single-ferrite low carbon steels exhibits the characteristic α/γ-fiber texture, i.e. <110>//Rolling Direction (RD) and <111>//Normal Direction (ND), irrespective of the rolling temperature, as long as there is no concurrent phase transformation. However, different recrystallisation textures appear as a function of the rolling temperature. Generally speaking, the γ-fiber recrystallisation texture is obtained after cold rolling, whereas the θ-fiber components ( <100>//ND) intensify at the expense of the γ-fiber orientations with increasing rolling temperature. Although these phenomena are well-known, the reasons for this behavior in terms of preferential orientation selection remain as yet unclear. In the present paper, recrystallisation microstructures and textures are simulated with a full-field cellular-automaton (CA) description, whereby recrystallisation from its incipient stage is considered as a process of sub-grain coarsening controlled by the well-known physical laws of driving force and kinetics. The simulations integrate in one single model the various conditions that give rise to the observed temperature dependence of the evolving static recrystallisation texture and microstructure. The different rolling temperatures will give rise to different initial microstructures at the onset of recrystallisation with noticeable variations in short-range orientation gradients in γ and θ-fiber orientations, respectively. The mere application of local grain-boundary migration laws on the topology of the deformation structure, without imposing any specific nucleation selection criterion, will properly balance the dominance of γ-fiber grains after cold-rolling and θ-fiber orientations after warm rolling. Finally, the well-known nucleation of Goss orientations ({110}<001>) in shear bands occurring in γ-fiber grains is also simulated in this single conceptual framework.

Carbon segregation to defects in martensite is a phenomenon known for its occurrence and interference with mechanisms such as carbon partitioning in multiphase steels. Especially in martensite–austenite partitioning processes, carbon trapping at/de-trapping from martensite defects plays an important role since it interacts with the austenite enrichment. In this work, we develop a physics-based model in which we incorporate the concurrent evolution of carbon partitioning and trapping at/de-trapping from martensite defects. The model describes the global and local, time-dependent distribution of carbon between three lattice types, namely martensite defects, martensite solid solution, and austenite. We implement the model in mean-field and full-field descriptions, and discuss the interaction between carbon enrichment in austenite and segregation to martensite defects, on the basis of global equilibrium as well as on the carbon kinetics. We apply the model in several martensite — austenite microstructures and discuss the dependence of the interaction between carbon partitioning and trapping at/de-trapping from defects on specific microstructural features, i. e. phase fractions and microstructural banding.

This study investigates the sub-structure of IF steel in three conditions: cold rolled, statically recovered, and warm rolled. After both cold and warm rolling, the steel exhibits the typical 〈110〉//RD and 〈111〉//ND fiber textures. Considering the short-range misorientation gradient ∆θ/∆x to assess locally stored energy variations, it was observed that 〈111〉//ND grains exhibit significantly higher gradients than 〈001〉//ND grains in all conditions. In the statically recovered conditions, the ∆θ/∆x values are significantly reduced compared to the cold rolled condition, but these values are significantly higher than those of the dynamically recovered after warm rolling. The strongly reduced orientation gradients in the 〈111〉//ND grains after warm rolling may reduce the nucleation potency of these orientations in the ensuing recrystallization. This study enhances our knowledge of deformation microstructure as a function of rolling temperature and is relevant in explaining reported differences in annealing textures during static recrystallization after cold vs warm rolling.

Physics-based crystal plasticity models rely on certain statistical assumptions about the collective behavior of dislocation populations on one slip system and their interactions with the dislocations on the other slip systems. One main advantage of using such physics-based constitutive dislocation models in crystal plasticity kinematic frameworks is their suitability for predicting the mechanical behavior of polycrystals over a wide range of deformation temperatures and strain rates with the same physics-based parameter set. In this study, the ability of a widely used temperature-dependent dislocation-density-based crystal plasticity formulation to reproduce experimental results, with a main focus on the yield stress behavior, is investigated. First, the material parameters are identified from experimental macroscopic stress–strain curves using a computationally efficient optimization methodology that uses a genetic algorithm along with the response surface methodology. For this purpose, a systematic set of compression tests on interstitial free (IF) steel samples is performed at various temperatures and strain rates. Next, the influence of the individual parameters on the observed behavior is analyzed. Based on mutual interactions between various parameters, the ability to find a unique parameter set is discussed. This allows identifying shortcomings of the constitutive law and sketch ideas for possible improvements. Particular attention is directed toward identifying possibly redundant material parameters, narrowing the acceptable range of material parameters based on physical criteria, and modifying the crystal plasticity formulation numerically for high-temperature use.

High-resolution three-dimensional crystal plasticity simulations are used to investigate deformation heterogeneity and microstructure evolution during cold rolling of interstitial free (IF-) steel. A Fast Fourier Transform (FFT)-based spectral solver is used to conduct crystal plasticity simulations using a dislocation-density-based crystal plasticity model. The in-grain texture evolution and misorientation spread are consistent with experimental results obtained using electron backscatter diffraction (EBSD) experiments. The crystal plasticity simulations show that two types of strain localization features develop during the large strain deformation of IF-steel. The first type forms band-like areas with large strain accumulation that appear as river patterns extending across the specimen. In addition to these river-like patterns, a second type of strain localization with rather sharp and highly localized in-grain shear bands is identified. These localized features are dependent on the crystallographic orientation of the grain and extend within a single grain. In addition to the strain localization, the evolution of in-grain orientation gradients, misorientation features, dislocation density, kernel average misorientation, and stress in major texture components are discussed.

The capability of high-resolution modeling of crystals subjected to large plastic strain is essential in predicting many important phenomena occurring in polycrystalline materials, such as microstructure, deformation localization and in-grain texture evolution. However, due to the heterogeneity of the plastic deformation in polycrystals, the simulation mesh gets distorted during the deformation. This mesh distortion deteriorates the accuracy of the results, and after reaching high local strain levels, it is no longer possible to continue the simulation. In this work, two different adaptive remeshing approaches are introduced for simulating large deformation of 3D polycrystals with high resolution under periodic boundary conditions. In the first approach, a new geometry with a new mesh is created, and then the simulation is restarted as a new simulation in which the initial state is set based on the last deformation state that had been reached. In the second approach, the mesh is smoothened by removing the distortion part of the deformation, and then the simulation is continued after finding a new equilibrium state for the smoothed mesh and geometry. The first method is highly efficient for conducting high-resolution large-deformation simulations. On the other hand, the second method's primary advantage is that it can overcome periodicity issues related to shear loading, and it can be used in conjunction with complex loading conditions. The merits of the methodologies are demonstrated using full-field simulations performed using a dislocation-density-based crystal plasticity model for Interstitial free (IF-) steel. Particular emphasis is put on studying the effect of resolution and adaptive meshing. The algorithms presented have been implemented into the free and open-source software package, DAMASK (Düsseldorf Advanced Material Simulation Kit).

The role of microstructural defects (dislocation density and grain boundary areas) on the passive film properties formed on cold- and hot-rolled interstitial free (IF) steels is investigated in 0.1 M NaOH solution. Electron backscattered diffraction (EBSD) shows higher microstructural defect density on cold-rolled samples. Potentiodynamic polarization (PDP) and electrochemical impedance spectroscopy (EIS) results exhibit the lower barrier properties of passive films with the increase in microstructural defects. This is attributed to the increase in donor density measured with Mott-Schottky analysis and the lower relative quantity of protective γ-Fe₂O₃ in passive films (composed of Fe₃O₄,γ-Fe₂O₃ and FeO(OH)) with the increase in microstructural defect density.

A cellular automaton algorithm for curvature-driven coarsening is applied to a cold-rolled interstitial-free steel's microstructure - obtained through electron backscatter diffraction (EBSD). Recrystallization nucleation occurs naturally during the simulation, due to the highly heterogeneous and hence competitive growth among pre-existing (sub) grains. The spatial inhomogeneity of the subgrain growth that takes place derives from the large local variations of subgrain sizes and misorientations that comprise the prior deformed state. The results show that capillary-driven selective growth takes place to the extent that the prior elongated and deformed grains are replaced by equiaxed grains with no interior small-angle boundaries. Additionally, during the simulation certain texture components intensify and others vanish, which indicates that preferential growth occurs in a fashion that relates to the crystal orientations’ topology. The study of the early stages of recrystallization (i.e. nucleation) shows that the pre-existing subgrains that eventually recrystallize, exhibit certain topological characteristics at the prior deformed state. Successful nucleation occurs mostly for pre-existing matrix subgrains abutting shear bands or narrow deformation bands and particularly at regions where the latter intersect.

A severe obstacle for the routine use of crystal plasticity models is the effort associated with determining their constitutive parameters. Obtaining these parameters usually requires time-consuming micromechanical tests that allow probing of individual grains. In this study, a novel, computationally efficient, and fully automated approach is introduced which allows the identification of constitutive parameters from macroscopic tests. The approach presented here uses the response surface methodology together with a genetic algorithm to determine an optimal set of parameters. It is especially suited for complex models with a large number of parameters. The proposed approach also helps to develop a quantitative and thorough understanding of the relative influence of the different constitutive parameters and their interactions. Such general insights into parameter relations in complex models can be used to improve constitutive laws and reduce redundancy in parameter sets. The merits of the methodology are demonstrated on the examples of a dislocation-density-based crystal plasticity model for bcc steel, a phenomenological crystal plasticity model for fcc copper, and a phenomenological crystal plasticity model incorporating twinning deformation for hcp magnesium. The approach proposed is, however, model-independent and can be also used to identify parameters of, for instance, fatigue, creep and damage models. The method has been implemented into the Düsseldorf Advanced Material Simulation Kit (DAMASK) and is available as free and open-source software. The capability of translating complex material response into a micromechanical digital twin is an essential precondition for the ongoing digitalization of material property prediction, quality control of semi-finished parts, material response in manufacturing and the long-term behavior of products and materials when in service.