[en] The martensitic transformation (MT), magnetic phases, and exchange bias (EB) effect in Mn₅₀Ni_{25 + x}In_25−x (x = 14.5∼18) Heusler alloys have been investigated. The MT and magnetic state can be tuned significantly by modifying the Ni/In ratio, while the Curie temperature (T_C) remains almost unchanged. With increase of the Ni/In ratio, the ferromagnetic components in the studied samples decrease continuously, while the antiferromagnetic components increase and it therefore enhances the exchange interaction as well. All of the samples exhibit negative horizontally shifted loops after field-cooled procedure. In addition, the samples with the compositional range of 15 ≤ x ≤ 16 also present the EB effect in zero field-cooled condition. To evaluate the causes of this scenario, EB field and coercive field as a function of temperature and cooling field have been investigated. The experimental results imply that the spin reconfiguration of superspin glass (SSG) clusters and the competition between antiferromagnetic and ferromagnetic interactions can account for the behavior of EB effect.

[en] Several models for end-point carbon prediction of BOF(Basic Oxygen Furnace) based on off-gas analysis were studied in this paper. The advantages and disadvantages of the integral model, the exponential decay model and the cubic fitting model were analyzed respectively. Based on analysis of the characteristics of the decarburization rate curve, a new exponential model was established by the introduction of a correction algorithm. The principle of the proposed model involves applying the decarburization rate curve and the descending gradient of the historical heats to obtain the average decarburization curve and reference decarburization efficiency coefficient using the regression fitting method. According to the deviation between the actual and the predicted decarburization curves, the decarburization efficiency coefficient was corrected to improve the prediction accuracy. Plant trials were carried out in a 210 t converter to compare the performance of the mentioned models. The results showed that the new model exhibited better adaptability and higher accuracy than the other ones. The hit ratio of the new model reached more than 90% for the prediction of end-point carbon content within a tolerance of ±0.02%. (paper)