Although the deformation behavior of high-entropy alloys (HEAs) has been extensively studied at the macroscale, many important properties have yet to be explored for these alloys at the microscale, thus hampering accurate prediction of damage and failure processes. Synchrotron high-energy diffraction microscopy (HEDM) and fast-Fourier transform-based crystal plasticity modeling was conducted to investigate the three-dimensional (3D) grain-resolved micromechanical response for approximately 1,900 constituent grains within a single-phase FCC HEA up to 1% applied strain. The evolution of grain-resolved elastic strains, lattice reorientations, and maximum resolved shear stresses (mRSS) were evaluated to quantify elastic, yield, and fully plastic behavior. Overall, the initial critical resolved shear stress (CRSS), determined via in situ HEDM and companion modeling, was found to be > 20% higher than estimated using the classical polycrystalline Taylor factor (M = 3.06). However, a descriptive parameter based on the average grain-resolved Taylor factor (M¯) was found to show excellent agreement with plastic yielding behavior observed within HEDM datasets. Noticeable deviations in HEDM lattice reorientations compared to both EVP-FFT simulations and classical predictions for FCC polycrystals were discovered, highlighting the complexity in correlating local lattice reorientations, Taylor, and Schmid factors with plastic response for this material at the grain-scale. Therefore, it is anticipated that the overall trends and parameter identification of 3D grain-resolved properties in this study can serve as an important foundation for continued mesoscale investigation on both well-established and newly developed Cantor-like HEAs.

Using a large-scale, experimentally captured 3D microstructure data set, we implement the generative adversarial network (GAN) framework to learn and generate 3D microstructures of solid oxide fuel cell electrodes.The generated microstructures are visually, statistically, and topologically realistic, with distributions of microstructural parameters, including volume fraction, particle size, surface area, tortuosity, and triple-phase boundary density, being highly similar to those of the original microstructure.These results are compared and contrasted with those from an established, grain-based generation algorithm (DREAM.3D). Importantly, simulations of electrochemical performance, using a locally resolved finite element model, demonstrate that the GAN-generated microstructures closely match the performance distribution of the original, while DREAM.3D leads to significant differences. The ability of the generative machine learning model to recreate microstructures with high fidelity suggests that the essence of complex microstructures may be captured and represented in a compact and manipulatable form.

Microstructure control in the laser powder bed fusion additive manufacturing processes is a topic of major interest because of the submillimeter length scale at which the manufacturing process occurs. The ability to control the process at the melt pool scale allows for microstructure control that few other manufacturing techniques can match. The majority of work on microstructure control has focused on altering laser parameters to control solidification conditions (Ref (R.R. Dehoff, M.M. Kirka, W.J. Sames, H. Bilheux, A.S. Tremsin, L.E. Lowe, and S.S. Babu, Site Specific Control of Crystallographic Grain Orientation through Electron Beam Additive Manufacturing, Mater. Sci. Technol., 2014, 31(8), p 931—938. R. Shi, S.A. Khairallah, T.T. Roehling, T.W. Heo, J.T. McKeown, and M.J. Matthews, Microstructural Control in Metal Laser Powder Bed Fusion Additive Manufacturing Using Laser Beam Shaping Strategy, Acta Mater., 2020, 184, p 284—305, https://doi.org/10.1016/j.actamat.2019.11.053.)). Other machine parameters, besides the laser parameters, have also been shown to affect the microstructure of AM parts (Ref (N. Nadammal, S. Cabeza, T. Mishurova, T. Thiede, A. Kromm, C. Seyfert, L. Farahbod, C. Haberland, J.A. Schneider, P.D. Portella, and G. Bruno, Effect of Hatch Length on the Development of Microstructure, Texture and Residual Stresses in Selective Laser Melted Superalloy Inconel 718, Mater. Des., 2017, 134, p 139—150, https://doi.org/10.1016/j.matdes.2017.08.049. F. Geiger, K. Kunze, and T. Etter, Tailoring the Texture of IN738LC Processed by Selective Laser Melting (SLM) by Specific Scanning Strategies, Mater. Sci. Eng. A, 2016, 661, p 240—246, https://doi.org/10.1016/j.msea.2016.03.036.)). We propose an investigation of the effects of hatch spacing and layer thickness on microstructure development in laser powder bed fusion additive manufacturing. A Monte Carlo Potts model with textured solidification capabilities is used to study the effects of these parameters on a unidirectional scan strategy. The simulation results reveal substantial changes in grain morphology as well as texture. Additionally, EVP-FFT crystal plasticity simulations were performed to evaluate the effect of the microstructural shifts on mechanical response. The conclusions from this work elucidate the effects of these parameters on part microstructure as predicted by the texture-aware solidification Potts model and inform understanding of how bulk texture is predicted by the simulation approach.

The present study investigated the sensitivity of material constitutive models on thermomechanical responses in laser powder bed fusion additive manufacturing of Ti-6Al-4V. Uniform scan strategies with scan lengths of 0.5, 1, and 2 mm were applied so that wide ranges of thermal histories could be generated. The Johnson-Cook (JC) and Mechanical Threshold Stress (MTS) material plasticity models were chosen to capture the influence of strain, strain rate, and temperature. The JC model is a phenomenological model which is known for its easy implementation and excellent agreement with material testing results. On the other hand, the MTS model is a more complex physics-based internal state variable plasticity model that is expected to provide more accurate estimation, particularly for cases involving changes in strain rate and temperature. Numerical results revealed that both JC and MTS models provided a similar stress evolution, however, the plastic strain evolution was more realistic using the MTS model. Moreover, it was found that the maximum strain and the strain rate in the LPBF process are high compared to typical quasi-static testing, i.e., ~ 2% and ~ 4 s−1, respectively. Accordingly, the material models should be calibrated with data obtained under similar deformation conditions. The choice of scan length also strongly affects in-plane stress anisotropy. Ultimately, we show both qualitatively and quantitatively the dependency of mechanical behavior prediction in LPBF on the choice of material models.

A transient three-dimensional thermomechanical model was developed to examine the evolution of thermal and mechanical fields in the laser powder bed fusion of Ti-6Al-4V alloy, particularly with respect to the development of plastic strain. A primary focus was to evaluate the influence of material constitutive models on predicted mechanical behaviors. Johnson-Cook (JC) constitutive material models were chosen to account for the contribution of strain, strain rate, and temperature on material responses. Three different modifications of the JC models were applied to assess the sensitivity of rate hardening and temperature-dependent strain hardening on mechanical prediction. Numerical results revealed that predicted stress and strain fields were highly sensitive to the rate-dependent term but minimally affected by the temperature-dependent strain hardening. The maximum differences in average stresses and plastic strains were 23% and 13% when comparing results between the JC model and the JC model without strain rate hardening, respectively. Moreover, it was found that strain rate hardening mostly occurred at intermediate temperatures, ≈ 1000 — 1600 K, during the continuous cooling phase. Finally, the present study emphasizes the importance of material constitutive models on mechanical behavior in laser powder bed fusion as well as providing insight for further exploration of process parameter optimization.

During laser melting of metals, localized metal evaporation resulting in the formation of a keyhole shaped cavity can occur if processing conditions are chosen with high power density. An unstable keyhole can have deleterious effects in certain applications (e.g., laser powder bed fusion) as it increases the likelihood of producing defects such as porosity. In this work, we propose a pipeline that enables complete segmentation and extraction of various geometric features in keyholing conditions. In situ synchrotron high-speed X-ray visualization at the Advanced Photon Source provides large datasets of experimental images with a high spatio-temporal resolution across a range of laser parameters for Ti-6Al-4V. Computer vision image processing techniques were used to extract time-resolved quantitative geometric features (e.g., depth, width, front wall angle) throughout keyhole evolution which were subsequently analyzed to understand the relationship between the variation of local keyhole geometry and processing conditions. This analysis is the first to employ a data-driven approach to further our understanding of the keyholing process regime.

A brief overview of the state of texture and anisotropy is provided with the motive of inspiring younger readers to engage in this topic. The International Conference on Texture of Materials ICOTOM has been active since 1969 up through the recent 19th meeting in Japan in 2021. The series initially focused on the problem of reconstructing three-dimensional orientation distributions from diffraction data which typically provided two-dimensional projections in the form of pole figures following the pioneering work of Bunge [1] and Roe [2]. In recent years, the advent of automated orientation mapping in the scanning electron microscope [3] and 3D mapping via synchrotron x-rays [4][5] has provided vastly more detailed data on texture and, crucially, has connected texture more closely with microstructure. Alongside this has been the development of simulation tools to predict texture formation and the anisotropic properties of polycrystalline materials. This has mostly been a accomplished via a mix of mesoscale models, e.g. [6], and more detailed methods that include microstructure. The latter are predominantly based on the finite element method complemented by the spectral method [7].

Powder-entrapped gas, which can occur naturally in gas-atomized powder, can induce porosity in parts fabricated with powder-based metal additive manufacturing processes. This study utilized synchrotron-based x-ray computed tomography and an in situ high-speed imaging technique, dynamic x-ray radiography (DXR), to investigate the formation of powder-induced porosity using 17-4 PH stainless steel powders with a controlled size distribution and intentionally varied entrapped gas contents. While powder with a low entrapped gas content showed no net part porosity increase, the results showed a strong correlation between the porosity in the powder and the porosity in the builds made from powder with a high entrapped gas content relative to typical gas-atomized powder. A threshold value was developed to classify porosity induced by powder-entrapped gas based on pore morphology measured using computed tomography. Transfer and coalescence of pores during laser melting was observed directly with DXR.

The influence of thermomechanical processing (TMP) of a Ti-6Al-4V alloy on the transformation texture and intervariant boundary network were investigated by conventional EBSD mapping along with the five-parameter boundary analysis approach. The texture characteristics of Ti-6Al-4V subjected to deformation in the beta regime followed by the beta-+alpha martensitic transformation were examined using visco-plastic self-consistent simulation and forward calculation of the transformation texture. Comparison of the simulated and experimental texture characterisitcs revealed that the transformed alpha texture was dominated by the variant selection associated with substructure development in the beta parent phase and the occurrence of specific self-accommodating alpha variants in the microstructure, promoting the quadrilateral and/or V shape variant arrangement. This resulted in a progressive increase in the 63.26 degrees/[10553] intervariant boundaries with the strain increment, at the expense of 60 degrees/ [1 1 20]. Moreover, the grain boundary network for all conditions was dominated by the triple junctions (grain boundary network) terminating on 63.26 degrees/[10553] and 60 degrees/[1 1 20] intervariants. It is shown that the elastic interactions among the variants during the martensitic transformation is the dominant parameter affecting the grain boundary network, despite the presence of dislocation based variant selection.