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In order to further improve the combination of strength and ductility for 30Si2MnCrMoVE ultra-high strength steel (UHSS), a thermomechanical treatment, named deformation direct quenching and partitioning (DQ&P), was carried out on it. The microstructure evolutions and mechanical properties of 30Si2MnCrMoVE UHSS treated by DQ&P were compared with those treated by conventional off-line quenching and tempering (Q&T) through various microscopic characterization methods and uniaxial tensile tests. Moreover, the effects of austempering temperature on the microstructure evolutions and mechanical properties of the studied steel after DQ&P process were also investigated. The results show that the DQ&P samples, although lower or slightly lower yield strength, possess significantly higher ultimate tensile strength due to higher work-hardening rate caused by high density dislocations and fine dispersed carbides. Moreover, DQ&P310 sample exhibit apparently higher uniform elongation than Q&T sample despite of comparable content of retained austenite due to more prone to transformation induced plasticity (TRIP) effect. The DQ&P process can increase the ultimate tensile strength by 267 MPã423 MPa and the uniform elongation by 78%∼85%, respectively, as compared to Q&T process, which indicates that DQ&P process may be a promising thermomechanical treatment method to improve the comprehensive mechanical properties of the studied steel. The strengths and elongations of DQ&P samples do not vary monotonously with the increase of austempering temperature, which are both closely related to the content of retained austenite.

The development of automated segmentation and quantitative characterization of microtextured regions (MTRs) from the complex heterogeneous microstructures is urgently needed, since MTRs have been proven to be the critical issue that dominates the dwell-fatigue performance of aerospace components. In addition, MTRs in Ti alloys have similarities to microstructures encountered in other materials, including minerals and biomaterials. Meanwhile, machine learning (ML) offers new opportunities. This paper addresses segmentation and quantitative characterization of MTRs, where an ML approach, the Gaussian mixture models (GMMs) coupled with density-based spatial clustering of applications with noise (DBSCAN) clustering algorithms, was employed in order to process the orientation data acquired via EBSD in the Matlab environment. Pixels with orientation information acquired through electron backscatter diffraction (EBSD) are divided and colored into several “classes” (MTRs) within the defined c-axis misorientations (i.e., 25°, 20°, 15°, 10°, and 5°), the precision and efficacy of which are verified by the morphology and pole figure of the segmented MTR. An appropriate range of c-axis misorientations for MTR segmentation was derived, i.e., 15~20°. The contribution of this innovative technique is compared with previous studies. At the same time, the MTRs were statistically characterized in the global region.

The formation of the irregular γ′ precipitates in the nickel-based superalloy Waspaloy was investigated during the continuous cooling, which is relevant to the cooling rates and interrupted temperature. The morphology of the γ′ precipitates was observed to change from a dispersed sphere to the flower-like one with the decreasing of the cooling rates. It was found that there are three modes of transportation of the solute atoms involved in relation to the γ′ precipitates: dissolution from the small γ′ precipitates to the γ matrix, diffusion to the large γ′ precipitates from the matrix, and the short distance among γ′ precipitates close to each other. Meanwhile, the slower cooling rates tend to result in the serrated grain boundaries, and the wavelength between successive peaks (λ) and the maximum amplitude (A) are larger with the decreasing of the cooling rates. The content of the low ΣCSL boundaries increases with the decreasing of the cooling rates, which is of great benefit in improving the creep property of the Waspaloy.