Morphology and Crystallography Analyses of HSLA Steels with Hardenability Enhanced by Tailored C–Ni Collocation

High hardenability is of great importance to ultra-heavy steel plates and can be achieved by tailoring the composition of steel. In this study, the continuous cooling transformation (CCT) curves of two high-strength low-alloy (HSLA) steels (0.16C-0.92Ni steel and 0.12C-1.86Ni steel) were elucidated to reveal the significance of C–Ni collocation on hardenability from the perspective of morphology and crystallography. At a low cooling rate (0.5 °C/s), the 0.12C-1.86Ni steel showed higher microhardness than 0.16C-0.92Ni steel. The microstructure in 0.16C-0.92Ni steel was mainly granular bainite with block-shaped martensite/austenite islands (M/A islands), while that in 0.12C-1.86Ni steel was typically lath bainite with film-shaped M/A islands, denoting that the 0.12C-1.86Ni steel is of higher hardenability. Moreover, the 0.12C-1.86Ni steel exhibited a higher density of block boundaries, especially V1/V2 boundaries. The higher density of block boundaries resulted from the weakened variant selection due to the larger transformation driving force and more self-accommodation of transformation strain induced by the reduced carbon and increased nickel content.

Effect of Welding Heat Input on Microstructure and Impact Toughness in the Simulated CGHAZ of Low Carbon Mo-V-Ti-N-B Steel

Welding thermal cycles with heat inputs ranging from 25 to 75 kJ/cm were performed on a Gleeble 3500. The impact energy improved significantly (from 10 to 112 J), whereas the simulated coarse-grain heat-affected zone (CGHAZ) microstructure changed from lath bainite ferrite (LBF) and granular bainite ferrite (GBF) + martensite/austenite (M/A) to acicular ferrite (AF) + polygonal ferrite (PF) + M/A as the heat input increased. Simultaneously, the mean coarse precipitate sizes and the degree of V(C,N) enrichment on the precipitate surface increased, which provided favorable conditions for intragranular ferrite nucleation. The Ar3 of CGHAZ increased from 593 °C to 793 °C with increasing heat inputs; the longer high-temperature residence time inhibited the bainite transformation and promoted the ferrite transformation. As a result, acicular ferrite increased and bainite decreased in the CGHAZ. The CGHAZ microstructure was refined for the acicular ferrite segmentation of the prior austenite, and the microstructure mean equivalent diameter (MED) in the CGHAZ decreased from 7.6 µm to 4.2 µm; the densities of grain boundaries higher than 15° increased from 20.3% to 45.5% and significantly increased the impact toughness. The correlation of heat input, microstructure, and impact toughness was investigated in detail. These results may provide new ideas for the development of high welding heat input multiphase steels.

A deep learning approach for complex microstructure inference

Automated, reliable, and objective microstructure inference from micrographs is essential for a comprehensive understanding of process-microstructure-property relations and tailored materials development. However, such inference, with the increasing complexity of microstructures, requires advanced segmentation methodologies. While deep learning offers new opportunities, an intuition about the required data quality/quantity and a methodological guideline for microstructure quantification is still missing. This, along with deep learning’s seemingly intransparent decision-making process, hampers its breakthrough in this field. We apply a multidisciplinary deep learning approach, devoting equal attention to specimen preparation and imaging, and train distinct U-Net architectures with 30–50 micrographs of different imaging modalities and electron backscatter diffraction-informed annotations. On the challenging task of lath-bainite segmentation in complex-phase steel, we achieve accuracies of 90% rivaling expert segmentations. Further, we discuss the impact of image context, pre-training with domain-extrinsic data, and data augmentation. Network visualization techniques demonstrate plausible model decisions based on grain boundary morphology.

The Effect of Nickel Contents on the Microstructure Evolution and Toughness of 800 MPa Grade Low Carbon Bainite Deposited Metal

In this work, three deposited metals with different nickel (Ni) contents were produced by active gas metal arc welding (GMAW) in order to explore the influence of Ni on the microstructure evolution and toughness of 800 MPa grade low carbon bainite deposited metal. The results showed that microstructure of the deposited metals mainly consisted of lath bainite, lath martensite, coalesced bainite (CB), and retained austenite (RA), and that the toughness was closely related to two factors: CB and RA. RA in deposited metal could improve the toughness, while the CB would deteriorate the toughness of deposited metal. As the Ni content increased, a large amount of CB was generated in the deposited metals. The RA content increased from 1.5% to 5.7% with the content of Ni increasing from 5.5% to 6.5%. However, the RA content did not increase when the Ni content increased from 6.5% to 7.5%. Additionally, the smallest control unit of toughness in 800 MPa grade low carbon bainite deposited metals is the Bain Packet (BP) from the perspective of crystallography characteristics. This work provided a reference for the chemical composition design of 800 MPa grade steel welding consumables and showed that the toughness of the deposited metal could be improved effectively by increasing the RA content while suppressing the formation of CB.

A Deep Learning Approach for Complex Microstructure Inference

Automated, reliable, and objective microstructure inference from micrographs is an essential milestone towards a comprehensive understanding of process-microstructure-property relations and tailored materials development. However, such inference, with the increasing complexity of microstructures, requires advanced segmentation methodologies. While deep learning (DL), in principle, offers new opportunities for this task, an intuition about the required data quality and quantity and an extensive methodological DL guideline for microstructure quantification and classification are still missing. This, along with a lack of open-access data sets and the seemingly intransparent decision-making process of DL models, hampers its breakthrough in this field. We address all aforementioned obstacles by a multidisciplinary DL approach, devoting equal attention to specimen preparation, contrasting, and imaging. To this end, we train distinct U-Net architectures with 30–50 micrographs of different imaging modalities and corresponding EBSD-informed annotations. On the challenging task of lath-bainite segmentation in complex-phase steel, we achieve accuracies of 90% rivaling expert segmentations. Further, we discuss the impact of image context, pre-training with domain-extrinsic data, and data augmentation. Network visualization techniques demonstrate plausible model decisions based on grain boundary morphology and triple points. As a result, we resolve preconceptions about required data amounts and interpretability to pave the way for DL's day-to-day application for microstructure quantification.

Quantitative assessment of structural inhomogeneity in cold-resistant low-alloy steel sheets for interpretation of technological features of their manufacturing

Microstructural inhomogeneity comparative automated complex analysis of plate low-alloy cold-resistant steels for Arctic application with a thickness of 25, 50 and 70 mm, produced by thermomechanical processing technology with various temperaturedeformation parameters, has been performed. The inhomogeneity of the microstructure over the plates thickness was estimated by the volume fraction of coarse packet-block regions of lath bainite and regions of bainite that does not have a developed internal subgrain structure (conventionally called “non-granular” bainite), as well as anisotropy of the microstructure at different dimensional levels: short and long distance neighborhoods. The obtained results of microstructural heterogeneity quantitative assessment over the plates thickness were used for its detailed interpretation, taking into account the metallurgical inheritance of the slab and special features of two-stage thermomechanical processing with accelerated cooling.

Dynamic continuous cooling transformation, microstructure and mechanical properties of medium-carbon carbide-free bainitic steel

The effects of the cooling rate after hot deformation on phase transformation, the microstructure of the designed nonquenched and tempered medium-carbon carbide-free bainitic steel have been investigated during the dynamic continuous cooling process. The results show that with the increase of the cooling rate, the morphology of the carbide-free bainite of the experimental steel evolves from granular bainite to lath bainite. Meanwhile, the hardness increases, and the amount of the retained austenite decreases with the increase of the cooling rate. Besides, the morphology evolution of the retained austenite from block to film is revealed by EBSD. Moreover, 0.5°C/s is considered to be the favorable cooling rate to obtain the best strength–toughness matching. Furthermore, the semi-industrial experimental results proved that the tensile strength, yield strength and Charpy impact energy were 1,298 MPa, 847 MPa and 38 J, respectively.

Microstructure Characterization of SAW and TIG Welded 25Cr2Ni2MoV Rotor Steel Metal

Low pressure turbine rotors are manufactured by welding thick sections of 25Cr2Ni2MoV rotor steel using tungsten inert gas (TIG) backing weld, and submerged arc welding (SAW) filling weld. In this study, the microstructure of columnar grain zones and reheated zones in weld metal was characterized meticulously by Optical Microscope (OM), Scanning Electron Microscope (SEM) and Electron Back-Scatter Diffraction (EBSD). The results showed that, compared with SAW weld metal microstructure, TIG weld metal microstructure was relatively fine and homogeneous, due to its lower heat input and faster cooling rate than SAW. The maximum effective grain size in TIG and SAW weld were 7.7 μm and 13.2 μm, respectively. TIG weld metal was composed of lath bainite (LB) and blocky ferrite (BF), while SAW weld metal was composed of acicular ferrite (AF), lath bainite (LB)and ferrite side plate (FSP). Tempered martensite (TM) was detected along columnar grain boundaries in both TIG and SAW weld metals, which was related to the segregation of solute elements during weld solidification. Electron Probe Micro-Analysis (EPMA) results showed that the contents of Ni and Mn at the dendritic boundaries were 50% higher than those at the dendritic core in TIG weld. Similarly, 30% of Ni and Mn segregation at dendritic boundaries was also found in SAW weld. In addition, the microhardness of the two welded joints was tested.

EBSD Study of the Effect of Hot Deformation on Low Carbon Bainitic Structure

The effect of deformation temperature (DT) and thickness reduction on the bainitic structure was investigated under various test conditions by using hot compression on a Gleeble-1500 thermo-mechanical simulation machine, and electron back scattering diffraction (EBSD) technique. In the case of the bainitic structure consisting of granular bainite (GB), lath bainite (LB) and a little ferrite (AF) under the given deformation conditions, DT and thickness reduction have remarkable effect on the transformation kinetics, starting temperature (B) of bainite fast transformation, and the type of bainitic structure. With the decreasing of DT from 810 °C to 730 °C, the starting temperature of transformation B increase from 585 °C to 595 °C. When the thickness reduction was 0 % and 20 %, the microstructure consists of GB, LB and a little AF, whereas as the thickness reduction increase to 40 %, large grain size of LB and GB disappear, and only AF and M/A remained. With the thickness reduction increases from 0 % to 40 %, the effective grain size decreases from 4 μm to 2 μm, and the fraction of HGB increases from 48 % to 57 %.

Effects of Final Cooling Temperature on Microstructure Transformation and Properties of Q550 Low Carbon Bainite Steel

The mechanical properties of low carbon bainite steel are closely related to the microstructure and proportion after phase transformation. The microstructure of the deformed austenite of low carbon bainite steel after isothermal transformation and continuous cooling transformation was studied by thermal simulation test. The metallographic structure was observed by optical microscopy (OM) and scanning electron microscopy (SEM). The metallographic and microhardness were used to judge the microstructure type, and the CCT (continuous cooling transformation) curve and TTT (time-temperature-transformation) curve of the test steel were drawn. It was found that at 700-430 °C isothermal, undergo a variety of medium-temperature microstructure transformations appeared for the test steels, such as ferrite, pearlite, granular bainite and lath bainite. The cooling rate and final cooling temperature have great influence on the type and performance of the final microstructure. The final cooling temperature was controlled at about 515°C. The mixed microstructures of granular bainite (GB) and fine martensite-austenite (M-A) island, a small amount of acicular ferrite and lath bainite were obtained. The yield and tensile strengths of this type of microstructure reached 639 MPa and 750 MPa respectively, the shrinkage rate reached 17%, and the better low-temperature impact performance was realized.