As an important mechanical property, tensile behavior has been regarded as an indicator for the creep and thermal mechanical fatigue properties of Ni-based superalloys. The tensile property of Ni-based superalloys is closely related to the amount, size, and distribution of ${\gamma }^{\prime }$-phase and carbides. To further clarify the tensile deformation mechanism of the CM247LC alloy, this study investigated its solidification characteristics and directionally-solidified and heat-treated microstructure. The dependence of tensile properties on the varied temperature ranging between 650 and 950 °C is discussed in detail. It was found that the deformation mechanism at 650 °C is dominated by the shearing of dislocations into the ${\gamma }^{\prime }$-precipitates to form the superlattice stacking faults. At 800 °C, the K-W lock leads to the anomalous yield effects. At 950 °C, the deformation mechanism is dominated by the dislocations bypassing the ${\gamma }^{\prime }$-precipiates. The results provide a comprehensive understanding of the CM247LC alloy and are beneficial for the development of corrosion-resistant Ni-based superalloys.

In order to evaluate the increase in the flexural strength of a 3D braided C/SiC composite comprised with a thin pyrolytic carbon (PyC) interlayer (TI C/SiC) under a load of 60 MPa with an amplitude of ±20 MPa at an oxygen partial pressure of 8000 Pa, the effect of temperature, oxidation and stress value on the length change in the sample, fracture behavior, residual flexural strength and fracture morphology were studied up to 1500 °C. It was found that the gauge length change behaviors of the material are related to (i) the positive damage of the thin interlayer and (ii) to the negative damage of the C phase. The most serious damage of TI C/SiC under 60 ± 20 MPa occurs in an oxygen partial pressure of 17,000 Pa at 1300 °C. When the oxygen partial pressure and/or the temperature are reduced, the positive C phase damage is relieved. In the case that the oxygen partial pressure, temperature and stress increase, the negative C phase damage is facilitated. The oxidation mechanism of the C phase is controlled by the inward diffusion of oxygen from the sample surface to the center; however, a higher stress is considered to change the oxygen diffusion mechanism by increasing the reaction of the C phase, with oxygen causing a widening of microcracks.

The pre-sintered preform (PSP) is an advanced technology for repairing the Ni-based superalloy blade in a turbine. In general, boron is added to the Ni-based superalloys in small quantities (1.0 wt.%) on the microstructure evolution and mechanical properties in Ni-based superalloys for the PSP application is rarely studied. The variety, composition and evolution of the precipitates during solution heat treatment in the alloy with high B content were determined by EBSD, EPMA and SEM. The results indicate that Cr, W and Mo-rich M₅B₃ type borides precipitate from the matrix and its area fraction reaches up to about 8%. The area fraction of boride decreases with the prolonging of solution time and the increase of temperature higher than 1120 °C. The borides nearly disappear after solution treatment at 1160 °C for 2 h. The redissolution of boride and eutectic results in the formation of B-rich area with low incipient melting (about 1189 °C). It can bond metallurgically with the blade under the melting point of the blade, which decreases the precipitation of harmful phases of the blade after PSP repairing. The microhardness within the grain in the PSP work-blank first decreases (lower than 1160 °C) and then increases (higher than 1185 °C) with the increase of solution heat treatment temperature due to the dissolving and precipitation of borides. The tensile strength of the combination of PSP work-blank and Mar-M247 matrix at room temperature after solution treatment is related to the area fraction of boride, incipient melting and the cohesion between PSP work-blank and Mar-M247 matrix.

The multi-objective optimization of multicomponent superalloys has long been impeded by not only the complex interactions among multiple elements but also the low efficiency and high cost of traditional trial-and-error methods. To address this issue, this study proposed a thermodynamic calculation data-driven optimization framework that integrates machine learning (ML) and multi-objective screening based on domain knowledge. The core of this methodology involves introducing a commercial reference alloy and rapidly generating a large-scale thermodynamic dataset through ML models. After training, the ML models were verified to be more efficient at predicting phase transition temperatures and γ′ volume fractions than the CALPHAD methods. Focusing on the mechanical properties, critical strength indices, including solid solution strengthening, precipitation strengthening, and creep resistance based on the calculated γ/γ′ two-phase compositions, were compared with the reference alloy and set as the critical screen criteria. Optimal alloys were selected from the 388,000 candidates. Compared with the reference alloy, two new alloys were experimentally verified to have superior or comparable compressive yield strength and creep resistance at 900 °C at the expense of oxidation resistance and density, while maintaining comparable cost. This work demonstrates the significant potential of combining high-throughput thermodynamic data with intelligent multi-objective optimization to accelerate the development of new alloys with tailored property profiles.