Improvement of carbon segregation in cast bloom and heredity in hot-rolled bar

In this study, the effect of mechanical soft reduction on carbon segregation in the continuous casting of 300 × 400 mm 42CrMo alloy structural steel blooms was comparatively investigated by adjusting the casting speed, which was systematically optimized through numerical simulation. When the casting speed is 0.60 m · min−1, during the soft reduction process, the central solidification structure of the bloom becomes dense, and carbon segregation is improved. Moreover, the distribution of carbon in the samples before and after rolling was analyzed. Combined with the soft reduction process, the uniformity of carbon across the cross section of the bloom /bar distinctly improved for casting speeds of 0.50 m · min−1, 0.55 m · min−1 and 0.60 m · min−1, this was predominantly reflected in the core areas. The effective segregation length proportion of the bloom and rolled bar is approximately 40%. This phenomenon fully verifies the heredity characteristics of the elements in the rolling process.

Method of Verification of Carbon Segregation Ratio Determined with Experimental Methods

The problem of macrosegregation of alloying elements occurring during cast strand solidification in the continuous casting process is still valid; it is the subject of numerous experiments and theoretical considerations. A large percentage of this research is dedicated to carbon segregation, which, for understandable reasons, is vital for the production of high-carbon steels. The background knowledge on the mechanism of segregation occurrence indicates that it is a very complex effect, and a broad range of factors influencing the continuous casting process need to be considered. Therefore, it is difficult to translate information (provided by complex models of metal flow through a diphase area at the solidification interface of a cast strand) into practical engineering recommendations to reduce the macrosegregation effect. The presented study shows the latest research related to the carbon macrosegregation effect for selected high-carbon steel grades cast with a continuous caster. Problems related to the recording of the effect concerned have been pointed out. The second part of the paper presents the influence of selected casting parameters on carbon macrosegregation intensity when casting 160 × 160 billets with a six-strand caster. In this case, the main subject of the research was the influence of the casting speed on macrosegregation intensity. In the following step, an attempt was made to find the relationship between the cast strand structure and the distribution of carbon content on its cross-section. The ultimate objective of the presented study was to find an answer to the question on the technological capabilities of restricting the segregation effect.

Prediction of Central Carbon Segregation in Continuous Casting Billet Using A Regularized Extreme Learning Machine Model

Central carbon segregation is a typical internal defect of continuous cast steel billets. Real-time and accurate carbon segregation prediction is of great significance for lean control of the production quality in continuous casting processes. In this paper, a data-driven regularized extreme learning machine (R-ELM) model is proposed for the prediction of carbon segregation index (CSI). To improve model performance, outliers in industrial data were eliminated by means of boxplot tool. Besides, Pearson correlation combined with grey relational analysis (GRA) was conducted to avoid multicollinearity and redundancy in input variables. The new model shows potential to evaluate online quality of steel billets. When predictive errors were within ±0.03 and ±0.025, the prediction accuracy of the R-ELM model was 94% and 89%, respectively, which was higher than that of the multiple linear regression (MLR) model and ELM model. Moreover, the effects of several key continuous casting process parameters on CSI were investigated based on the predictions of the R-ELM model via response surface analysis. The conclusions are consistent with the metallurgical mechanism, and the predictive values of the R-ELM model agree well with experimental values, which further verifies the correctness and generalization ability of the R-ELM model.

Microstructural Analysis of Ti/Ni Bilayer Ohmic Contacts on 4H-SiC Layers

The micro-structural analysis of Ti/Ni bilayer as Ohmic contacts to n-type 4H-SiC is reported. There was no carbon segregation at the interface between the NiSi layer and the 4H-SiC layer for Ti/Ni contacts, unlike pure Ni contacts. The diffraction pattern image shows the presence of the cubic NiSi film which grows on the SiC surface. The film interface with the SiC was uniform and more planar. An optimized contact in terms of contact morphology was achieved using a bilayer contact Ti/Ni (20/100nm) annealed at 1100 °C for 5 minutes in vacuum.