The GH141 superalloy ring-rolled parts often face microstructural inhomogeneity during production. This work investigated the effect of post-dynamic recrystallization on the microstructural evolution of GH141 superalloy after gradient thermal deformation to solve the problem of microstructural inhomogeneity. Compression tests involving double cone (DC) samples were conducted at various temperatures to assess the effect of gradient strain on internal grain microstructure variation, which ranged from the rim to the center of the samples. The results demonstrate considerable microstructural inhomogeneity induced by gradient strain in the DC samples. The delay in heat preservation facilitated post-dynamic recrystallization (PDRX) and promoted extensive recrystallization in the DC samples experiencing large gradient strain, which resulted in a homogeneous grain microstructure throughout the samples. During compression at a relatively low temperature, dynamic recrystallization (DRX) was predominantly driven by continuous dynamic recrystallization (CDRX). As the deformation temperature increased, the DRX mechanism changed from CDRX-dominated to being dominated by discontinuous dynamic recrystallization (DDRX). During the delay of the heat preservation process, PDRX was dominated by a static recrystallization mechanism, along with the occurrence of meta-dynamic recrystallization (MDRX) mechanisms. In addition, the PDRX mechanism of twin-induced recrystallization nucleation was observed.

Laser additive manufacturing offers significant advantages for fabricating and repairing complex components. However, the complex solidification and remelting processes in nickel-based superalloys for additive manufacturing can introduce defects such as voids and cracks. Therefore, process parameters are crucial, as they significantly impact solidification and remelting, thereby affecting defect formation. In this study, laser-directed energy deposition was employed to evaluate the effects of our key process parameters on the formation of voids and cracks in a novel superalloy. The findings reveal that laser power and linear energy density significantly influence the void content and crack density. However, the influence of other process parameters on defect formation is relatively minimal. The optimal parameter space is characterized by a laser power range of 600~700 W, a linear energy density range of 60~90 J/mm and a powder feeding rate of 0.7~0.8 rpm. Moreover, the precipitation of fine MC-type carbides near the dendrites and grain-boundary misorientations within the range of 31~42° are associated with a higher propensity for crack formation. These insights provide a valuable reference for controlling the process parameters and understanding the cracking mechanisms in laser additive manufacturing of superalloys.

With the advancement in computational approaches and experimental, simulation, and modeling tools in recent decades, a trial-and-validation method is attracting more attention in the materials community. The development of powder metallurgy Ni-based superalloys is a vivid example that relies on simulation and experiments to produce desired microstructure and properties in a tightly controlled manner. In this research, we show an integrated approach to predicting the grain size of industrial forgings starting from lab-scale cylindrical compression by employing modeling and experimental validation. (a) Cylindrical compression tests to obtain accurate flow stress data and the hot working processing window; (b) double-cone tests of laboratory scale validation; (c) sub-scale forgings for further validation under production conditions; and (d) application and validation on full-scale industrial forgings. The procedure uses modeling and simulation to predict metal flow, strain, strain rate, temperature, and the resulting grain size as a function of thermo-mechanical processing conditions. The models are calibrated with experimental data until the accuracy of the modeling predictions is at an acceptable level, which is defined as the accuracy at which the results can be used to design and evaluate industrial forgings.

The Materials Genome Engineering (MGE) spurs the developments and applications of methods and tools in high-throughput experiments, integrated computation materials engineering and big data. Due to the unique importance and characteristics of structural alloys, there are great needs for MGE high throughput experimental methods and tools to enable efficient establishment of the complex alloy composition-microstructures-property relationships. To explore the alloy composition-phase relationships, several high-throughput experimental concepts are discussed. The diffusion-based high-throughput experimental concepts and approaches are highlighted from generating composition spread, automating characterization, and to illustrating systematic analysis. In particular, the evolution of diffusion multiple concepts and approaches demonstrated its efficiency, reliability and vitality to the high-throughput experimental methods and to the MGE at large.