Modeling Of Microstructure Evolution Research Articles

A general model of microstructure evolution including phase transformation in elasto‐plastic materials

A general model of microstructure evolution including phase transformation in elasto‐plastic materials

Microstructure evolution and constitutive modeling of Cu-bearing high-strength low-alloy steel during hot deformation

The microstructural evolution of austenite during hot deformation determines the mechanical properties of steel products. Consequently, industrial applications necessitate a thorough comprehension and modeling of this process. Under varied hot deformation conditions, the flow stress, microstructure evolution, and constitutive modeling of a Cu-bearing steel were examined. At various temperatures and strain rates, compression experiments are conducted, and the resulting microstructures were studied by electron backscatter diffraction (EBSD). Our results indicate that fine prior austenite grains with an average diameter of 22.1 m and a high-angle grain boundary density of 0.25 m1 were produced at a deformation temperature of 950 °C and a strain rate of 1 s−1. The dominating rotating cube components ({001}<110>) in the sample deformed at 1150 °C were gradually replaced by the γ-fiber texture component as the deformation temperature decreased. To accurately predict the flow behavior of this steel, we proposed an improved Arrhenius constitutive model that accounts for strain rate and adiabatic temperature rise. With a correlation coefficient (Rc) of 0.9936, a root mean square error (RMSE) of 4.92%, and a relative error (δ) of 6.05 MPa, our results demonstrate that this model predicts the flow stress of the experimental steel with good precision. This research contributes to the development of high-performance steel products by shedding light on the microstructural evolution and flow behavior of Cu-containing steels under hot deformation conditions.

Precipitate Structure, Microstructure Evolution Modeling and Characterization in an Aluminum Alloy 7050 Friction Stir Weld

Precipitate Structure, Microstructure Evolution Modeling and Characterization in an Aluminum Alloy 7050 Friction Stir Weld

A crystal plasticity-based micromechanical model for precipitate shearing: Application to cyclic softening of polycrystalline Ni-based superalloys

Cyclic deformation of polycrystalline Ni-based superalloys leads to cyclic hardening followed by softening, in terms of the mechanical response. A micromechanical constitutive model is proposed and implemented in a dislocation density-based, crystal plasticity framework to simulate the shearing of γ′ precipitates, which leads to the observed cyclic softening. The framework accounts for physically based deformation mechanisms. A slip-system level backstress model has been implemented to account for the kinematic hardening. Further, a micromechanical model for microstructure evolution due to precipitate shearing is developed that accounts for the dislocation-precipitate interactions and the resultant change in precipitate strengthening. The model is used to simulate cyclic deformation in two polycrystalline Ni-based superalloys, with different microstructures (in terms of the shape, size and volume fraction of precipitates), referred as Alloy 1 and Alloy 2. Room temperature cyclic deformation tests, followed by microstructure characterization were performed at different strain amplitudes for Alloy 1 to validate our predictions. For Alloy 2, the experimental stress–strain response was used from the literature to fit and validate our predictions. It is shown that the model can predict cyclic softening due to precipitate shearing for different initial microstructures and a range of loading conditions in polycrystalline Ni-based superalloys.

A Visualized Microstructure Evolution Model Integrating an Analytical Cutting Model with a Cellular Automaton Method during NiTi Smart Alloy Machining

In this study, a visualized microstructure evolution model for the primary shear zone during NiTi smart alloy machining was established by integrating an analytical cutting model with a cellular automaton method. Experimental verification was conducted using an invented electromagnet rotation-type quick-stop device. The flow stress curve during the dynamic recrystallization of the NiTi smart alloy, the influence of relevant parameters on the dynamic recrystallization process, and the distribution of dynamic recrystallization in the primary shear zone were studied via the model. The simulation results showed that strain rate and deformation temperature significantly affect the relevant parameters during the dynamic recrystallization process. Three typical shear planes were selected for a comparison between simulation results and experimental results, with a minimum error of 3.76% and a maximum error of 11.26%, demonstrating that the model accurately simulates the microstructure evolution of the NiTi smart alloy during the cutting process. These results contribute theoretical and experimental insights into understanding the cutting mechanism of the NiTi smart alloy.

Integrated Framework to Model Microstructure Evolution and Decipher the Microstructure-Property Relationship in Polymeric Porous Materials.

Unraveling the microstructure-property relationship is crucial for improving material performance and advancing the design of next-generation structural and functional materials. However, this is inherently challenging because it requires both the comprehensive quantification of microstructural features and the accurate assessment of corresponding properties. To meet these requirements, we developed an efficient and comprehensive integrated modeling framework, using polymeric porous materials as a representative model system. Our framework generates microstructures using a physics-based phase-field model, characterizes them using various average and localized microstructural features, and evaluates microstructure-aware properties, such as effective diffusivity, using an efficient Fourier-based perturbation numerical scheme. Additionally, the framework incorporates machine learning methods to decipher the intricate microstructure-property relationships. Our findings indicate that the connectivity of phase channels is the most critical microstructural descriptor for determining effective diffusivity, followed by the domain shape represented by curvature distribution, while the domain size has a minor impact. This comprehensive approach offers a novel framework for assessing microstructure-property relationships in polymer-based porous materials, paving the way for the development of advanced materials for diverse applications.

Multiscale modelling of microstructure evolution, and local solidification behaviours of the AlSi10Mg build component in laser powder bed fusion process

Laser powder bed fusion (L-PBF) process is an additive manufacturing process, in which rapid heating and cooling takes place. The microstructure and the solidification behaviour of L-PBF components have significant impacts on their mechanical properties. The solidification takes place in a very short duration which is difficult to capture experimentally, therefore the finite-element (FE) simulation is the best feasible solution. In this paper, to study the evolution of the AlSi10Mg alloy’s microstructure during the L-PBF process, a model composed of macroscopic finite element (FE) model and microscopic phase field (PF) model was built. This model is suitable to predict a more realistic thermal behaviour involving the possible physical phenomena and the thermal behaviour for various heat inputs was calculated. The PF model was then updated with these results in order to simulate the chemical compositions’ concentration field and solidified microstructure. According to the simulation’s results, the primary dendrite arm spacing (PDAS) is significantly influenced by the laser line energy. To validate the FE model along with the Phase field (PF) model, the results were compared with the analytical and experimental findings; and the FE model and PF results exhibited good agreement with the experimental results. Additionally, the solute distribution analysis demonstrated that during the solidification process, micro-segregation developed and the process parameters affected the micro-segregation. Finally, the specimens were subjected to metallographic and element distribution analyses using an energy-dispersive spectrometer (EDS) to compare the results with those from the PF simulation and establish the relationship between the process parameters.

Exploring large language models for microstructure evolution in materials

There is a significant potential for coding skills to transition fully to natural language in the future. In this context, large language models (LLMs) have shown impressive natural language processing abilities to generate sophisticated computer code for research tasks in various domains. We report the first study on the applicability of LLMs to perform computer experiments on microstructure pattern formation in model materials. In particular, we exploit LLM’s ability to generate code for solving various types of phase-field-based partial differential equations (PDEs) that integrate additional physics to model material microstructures. The results indicate that LLMs have a remarkable capacity to generate multi-physics code and can effectively deal with materials microstructure problems up to a certain complexity. However, for complex multi-physics coupled PDEs for which a detailed understanding of the problem is required, LLMs fail to perform the task efficiently, since much more detailed instructions with many iterations of the same query are required to generate the desired output. Nonetheless, at their current stage of development and potential future advancements, LLMs offer a promising outlook for accelerating materials education and research by supporting beginners and experts in their physics-based methodology. We hope this paper will spur further interest to leverage LLMs as a supporting tool in the integrated computational materials engineering (ICME) approach to materials modeling and design.

Numerical simulation and experimental validation of microstructure evolution during the upsetting process of a large size martensitic stainless steel forging

The microstructure evolution, plastic deformation, and damage severity during the open die hot forging of a martensitic stainless steel were investigated using finite element (FE) simulation. A microstructure evolution model was developed and combined with a visco-elastoplastic model to predict the strain, the strain rate, and the temperature distribution, as well as the volume fraction and the size of dynamically recrystallized grains over the entire volume of an industrial size forging. The propensity to damage during hot forging was also evaluated using the Cockcroft & Latham model. The three models were implemented in the FE code and the results analyzed in terms of microstructure inhomogeneity and stress levels in different regions of the forging. A good agreement was obtained between the predicted and the experimental results, demonstrating that the simulation provided a realistic representation of the forging process at the industrial scale.

Microstructure Prediction of 80MnSi8-6 Steel After Hot Deformation Based on Dynamic Recrystallization Kinetics and FEM Simulation

The microstructure evolution during hot deformation of 80MnSi8-6 nanobainitic steel was investigated through hot compression tests at deformation temperatures of 900–1250°C and strain rates of 0.1–20 s−1. The flow curves revealed strain-hardening behavior at the beginning of deformation followed by softening effects caused by microstructure evolution. A Johnson–Mehl–Avrami–Kolmogorov (JMAK) model for grain growth and dynamic recrystallization was developed, and the kinetics were determined. Critical and peak strains were identified, and coefficients for the microstructure evolution models were determined using linear regression. The analysis of S-curves revealed that decreasing the temperature delays the onset of recrystallization and that the strain rate significantly effects the recrystallization rate at lower temperatures. Constitutive modeling and determination of the Zener–Hollomon parameter allowed the determination of the influence of hot processing conditions on material behavior during deformation. Microstructure analysis showed that, at higher deformation temperatures, grain growth occurs simultaneously with grain refinement. Coefficients for the JMAK model were implemented in QForm software. Simulation results were compared with experimental measurements exhibited good arrangement, which confirms the accuracy of the JMAK model in predicting the microstructure evolution. This study demonstrated how microstructure evolution modeling and FEM simulations combined can be used to predict the grain size of 80MnSi8-6 steel after hot deformation.

Computationally Efficient Algorithm for Modeling Grain Growth Using Hillert's Mean-Field Approach.

To investigate the interconnected effects of manufacturing processes on microstructure evolution during hot-rolling, a through process model is required. A novel numerical implementation of the mean-field approach was introduced to efficiently describe the grain growth of larger systems and extended durations. In this approach, each grain is embedded within an average medium and interacts with the average medium, thus avoiding the complexities of individual grain interactions. The proposed upsampling approach dynamically adjusts the simulation grain ensemble, ensuring efficiency and accuracy regardless of the initial number of grains present. This adaptation prevents undersampling artifacts during grain growth. The accuracy of the model is verified against analytical solutions and experimental data, demonstrating high agreement. Moreover, the effects of different initial conditions are successfully investigated, demonstrating the model's versatility. Due to its simplicity and efficiency, the model can be seamlessly integrated into other microstructure evolution models.

Simulation of Solidification Structure in the Vacuum Arc Remelting Process of Titanium Alloy TC4 Based on 3D CAFE Method

Vacuum arc remelting is the main production method of titanium alloy ingots at present. In order to obtain good quality ingots, it is of great significance to study the formation of the solidification structure of ingots via vacuum arc remelting. In order to select and optimize the nucleation parameters for the solidification microstructure simulation of an ingot, a 3D CAFE model for microstructure evolution during vacuum arc remelting was established, taking into account heat transfer, flow, and solute diffusion. The Gaussian distribution continuous nucleation model and extended KGT model were used to describe the grain nucleation and dendrite tip growth rates, respectively. The multi-point mass source and moving boundary method were used to simulate the ingot growth. The results show that there are three typical crystal regions in the solidification structure of vacuum arc remelting titanium alloy ingots, namely the surface fine crystal region, columnar crystal region, and central equiaxed crystal region. The proportion of the columnar crystal region in the solidification structure of an ingot increases gradually with the increase in the undercooling of the maximum bulk nucleation. With an increase in the maximum bulk nucleation density, the equiaxed grain zone gradually increases, and the grain size gradually decreases. The proportion of the columnar crystal region in the solidification structure of an ingot increases gradually with an increase in the undercooling of the maximum bulk nucleation. The maximum volume nucleation variance has no obvious effect on the change in the solidification structure. When the maximum volume nucleation undercooling is 5.5 K, the maximum volume nucleation standard deviation is 4 K, and the maximum volume nucleation density is 5 × 108. The solidification structure simulation results are in good agreement with the experimental results.

Innovative microstructures in SmCo5-based ribbons regulated by Fe-Ni-Al-Ti alloy

We proposed a new measure to optimize the comprehensive magnetic properties of SmCo5 alloy. By compounding Fe-15Ni-3Al-1Ti (FNAT) alloy with high saturation magnetization and Sm(Co, Cu)5 matrix alloy in the liquid state, an innovative two-phase separation microstructure or cellular microstructure is formed after melt-spinning using the phase separation effect of the two alloys. At the same time, the element concentration, relative phase content, and microstructure are adjusted by adding different contents of FNAT alloy. The results show that FNAT addition promotes the as-spun ribbons phase separation (or spinodal decomposition) into Co-rich SmCo5- and Sm-Ni-rich CeCo5- or Sm2Co7-type phases. Adding 3 wt.% FNAT increases the coercivity, saturation magnetization, and remanence of the ribbons by 320.6 %, 39.8 %, and 82.8 %, respectively. Adding 5 wt.% FNAT promotes forming the Sm2(Co, M)7 cell-wall phase and increases the coercivity and remanence by 272.7 % and 48.1 %, respectively. Finally, the corresponding microstructure evolution models, magnetization, and demagnetization mechanisms are proposed.

A Mechanics-Based Phase-Field Model and Finite Element Simulations for Microstructure Evolution during Solidification of Ti-6Al-4V

A Mechanics-Based Phase-Field Model and Finite Element Simulations for Microstructure Evolution during Solidification of Ti-6Al-4V

Multiscale microstructural evolution of Fe–Ni–Al–Ti alloy with high magnetization

The Fe–15Ni–3Al–1Ti ribbons are produced by melt-spinning the annealed ingots at 10–40 m/s. The annealed ingots consist of Fe3Ni grains and α-Fe-type grain boundary phase, forming a columnar grain microstructure in the vertical direction and getting the maximum saturation magnetic polarization (Js) of 1.88 ± 0.03 T in the cross-section. Before and after the annealing, the ribbons form a cellular structure composed of the Fe3Ni intragranular phase and γ-(Fe, M), Fe7Ni3, or α-(Fe, M) cell boundary phases. Formation of enhanced <100> orientation is the primary mechanism for obtaining a high Js of 2.35 ± 0.07 T in the ribbons. The grain and grain boundary size of the ribbons is reduced by the phase transformation induced by annealing at 600 °C. The phase transformation processes of the ribbons before and after annealing are as follows: L→γ→melt−spunFe3Ni+γ1→annealedFe3Ni+Fe7Ni3 when melt-spinning at a speed of 10–25 m/s, and L→γ→melt−spunFe3Ni+Fe7Ni3→annealedFe3Ni+α−(Fe,Ni) at 40 m/s. Finally, the multiscale microstructure evolution models are used to summarize the phase transformation process of the alloys.

Microstructure Evolution and Numerical Modeling of TC4 Titanium Alloy during Ultrasonic Shot Peening Process

Ultrasonic shot peening (USP) is a surface treatment technology used in the mechanical properties strengthening of the engineering material and components during manufacturing. TC4 titanium alloy is a commonly used engineering material in the aerospace industry. In this study, a gradient nanostructured surface layer was successfully fabricated on the TC4 titanium alloy via USP technology at room temperature. The microstructure evolution of TC4 titanium alloy during USP was investigated. The surface microhardness was elevated from 330 HV to 438 HV with a penetrating depth of around 900 μm after USP with the duration of 8 min. EBSD characterization results confirmed the presence of high-density grain boundaries within the gradient structure in the region of 0–200 μm, accompanied by proliferation of dislocation density. TEM characterization indicated a substantial amount of nanograin with an average size of 74.58 nm. Furthermore, the USP process was also investigated by the finite element method to evaluate the surface-strengthening effect. The calculated maximum residual stress reached 973 MPa after multi-ball impact. The impact behavior of the shots during the USP process was studied. The effect of the parameters on the USP strengthening intensity was explored based on the validated model. This work provided a clearer understanding of the USP strengthening process of TC4 titanium alloy through an effective method of evaluating the process parameters.

Microstructural evolution and multi-mechanism strengthening model of nanocrystalline Al-Mg alloys

To unravel the determinants contributing to the remarkable strength observed in nanocrystalline binary alloys, we employed a high-pressure torsion method to fabricate Al-Mg alloys with varying Mg concentrations. Mechanical property analysis indicates that, with the increasing Mg content, both the hardness and yield strength exhibit an ascending trend. Notably, the nanocrystalline Al-8Mg alloy boasted an impressive hardness and yield strength of 295 HV and 889 MPa, respectively. Comprehensive characterizations of solute distribution and microstructural evolution were conducted using X-ray diffraction, electron back-scatter diffraction, transmission electron microscopy, and atom probe tomography. We clarified the distribution mechanism of Mg atoms at grain boundaries, developed a method for the precise assessment of inhomogeneous solute distribution, and proposed a multi-mechanism strengthening model, incorporating the inhomogeneous solute distribution strengthening mechanism. The calculated results aligned well with the experimental data.

Modeling of irradiation-induced microstructure evolution in Fe: Impact of Frenkel pair distribution

This study investigated the irradiation-induced microstructure evolution in Fe, employing the Creation-Relaxation Algorithm and different interatomic potentials. The influence of self-interstitial atoms (SIAs), which were either locally or uniformly being distributed during the creation of the Frenkel pairs, was investigated on the evolving microstructure. The spatially localized distribution of SIAs, mimicking the low-energy transfer irradiation conditions, moderated the microstructure development, compared to uniform distribution of SIAs, delaying the nucleation of dislocation for higher irradiation doses. Introducing multiple Frenkel pairs facilitated a cumulative irradiation dose of 5 dpa in large supercells. In small supercells, the accumulation of SIAs led to the formation of an artificially stabilized self-interacting planar interstitial cluster, suggesting a minimum cell dimension of 10 nm for an accurate modeling of microstructure evolution when the development of the dislocation network is of interest. The formation and evolution of the C15 Laves phase structure were explored. The evolving C15 structure developed larger clusters with uniformly distributed SIAs, and their sizes depended on the interatomic potential employed. Finally, a comparison with experimental measurements demonstrated that the density and the average size of interstitial dislocation loops aligned well with those observed in experimentally irradiated ultra-high purity Fe at low and room temperatures.

Application of grazing incidence wide-angle X-ray scattering to characterise mechanically plated coatings

Post-mechanical plating heat treatment on zinc and zinc–tin coatings resulted in the formation of an iron–zinc-rich intermetallic layer between the substrate and the coatings, while the outer coating layer became tin-rich in the case of heat-treated zinc–tin coatings. The novel use of grazing incidence wide-angle X-ray scattering detected not only ζ-FeZn13, δ1p-Fe13Zn126 and δ1k-FeZn6.67 phases but also Γ1-Fe11Zn40 and Γ-Fe4Zn9 phases due to the higher resolution and signal-to-noise ratio of synchrotron X-ray diffraction (XRD) compared to traditional XRD. Microstructure evolution models during the heat treatment of mechanically plated zinc and zinc–tin coatings are proposed. The formation of iron–zinc intermetallic phases was in the sequence of ζ-FeZn13, δ1p-FeZn10, δ1k-FeZn7, Γ-Fe3Zn10 and Γ1-Fe5Zn21 phases when the heat treatment duration increased.

Simulation and Experimental Study on the Effect of Superheat on Solidification Microstructure Evolution of Billet in Continuous Casting.

The control of the solidification structure of a casting billet is directly correlated with the quality of steel. Variations in superheat can influence the transition from columnar crystals to equiaxed crystals during the solidification process, subsequently impacting the final solidification structure of the billet. In this study, a model of microstructure evolution during billet solidification was established by combining simulation and experiment, and the dendrite growth microstructure evolution during billet solidification under different superheat was studied. The results show that when the superheat is 60 K, the complete solidification time of the casting billet from the end of the 50 mm section is 252 s, when the superheat is 40 K, the complete solidification time of the casting billet is 250 s, and when the superheat is 20 K, the complete solidification time of the casting billet is 245 s. When the superheat is 20 K, the proportion of the equiaxed crystal region is higher-the highest value is 53.35%-and the average grain radius is 0.84556 mm. The proportion of the equiaxed crystal region decreases with the increase of superheat. When the superheat is 60 K, the proportion of the equiaxed crystal region is the lowest-the lowest value is 46.27%-and the average grain radius is 1.07653 mm. Proper reduction of superheat can obviously reduce the size of equiaxed crystal, expand the area of equiaxed crystal and improve the quality of casting billet.