Analysis of solute distribution in dendrites of carbon steel with δ/γ transformation during solidification

Kinetics of the δ/γ interface in the massive-like transformation in Fe-0.3C-0.6Mn-0.3Si alloys

“…The thicknesses for carbon, manganese and silicon are 10 -8 m, 10 -10 m and 10 -10 m, respectively. Here, the diffusivities of carbon, manganese and silicon were 10 -9 , 10 -12 and 10 -11 m 2 /s [10]. Since the thicknesses for manganese and silicon is in the order of atomic distance, the two substitutional atoms are hardly partitioned at the δ/γ interface.…”

“…Since diffusivity in the δ phase is much larger than that in the γ phase [10], the solute profile at the δ/γ interface is essentially the same as that at the steady state solidification with planar interface [11]. Thickness of diffusion layer is given by 2D/V (D: diffusivity, V: velocity).…”

Mathematical Model for Prediction of Composition of Inclusions Formed during Solidification of Liquid Steel

“…Equilibrium partition coefficients (k) of solute elements between solid and liquid steel, and their diffusion coefficients (D) in d and g phases. 13,22,24) is evident from the plots that Brody-Flemings equation over-estimates back-diffusion. Consequently, the amount of segregation predicted by the same is less in comparison to Clyne-Kurz equation.…”

“…11,[23][24][25] Some of those correlations were examined critically and it was found that the most of them estimated the liquidus temperature of steel fairly well for all carbon ranges. However, none of the correlations gave reasonable estimate of the solidus temperature for all carbon contents.…”

Macrosegregation in Steel Ingots: The Applicability of Modelling and Characterisation Techniques

“…Instead, finite-difference approaches have often been used to better predict the onset and effects of the peritectic and other transitions. Ueshima et al 150) predicted the start of the peritectic using empirical relationships based on local solid concentrations, whilst Howe et al 151,152) introduced 'carbon equivalents' for alloying elements such that the effect of each partitioned species on the peritectic temperature was accounted for in a pseudo-binary model. More recently the use of thermodynamic databases in steel microsegregation models has become popular [153][154][155][156] and kinetic effects have also been incorporated into models .111,157-163) Nevertheless, adding such complexity into macrosegregation models often comes at great computational expense, and consequently there has been some development of rapid microsegregation models for incorporation into macromodels.…”