Coarsening of SiO2 particles in copper and MnS inclusions in steel View Full Text


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Article Info

DATE

1982-12

AUTHORS

T. Fujii, D. R. Poirier, M. C. Flemings

ABSTRACT

A model to simulate the diffusion-controlled coarsening and dissolution kinetics of particles within a metallic matrix is formulated. With an arbitrary size distribution of particles, the model can be used to calculate the change in the size distribution of particles during coarsening or dissolution. Other system parameters, such as average radius of particles, volume fraction, average distance between particles, surface area, and matrix composition are also calculated. An important result is that kinetics do not generally obey the often-applied Lifshiftz-Slyozov-Wagner theory for diffusion controlled coarsening based upon concentration profiles around isolated spheres. In such a formulation, the direct effect of the surrounding particles is neglected. In our model, which is a modification of the coarsening kinetics described by Weins and Cahn, the effect of surrounding particles is incorporated because the system is taken to be a system of point potentials, each with a potential according to its radius of curvature. Calculations are on silica particles in a copper matrix and on manganese sulfide inclusions in iron, with emphasis on the latter, in order to predict their behavior during homogenization or soaking treatments. The effect of the composition of manganese, from 0.1 to 1.2 wt pct, on the coarsening of sulfides in a “high” sulfur (0.017 wt pct) steel and a “low” sulfur (0.003 wt pct) steel was investigated. As expected, the model predicts that manganese strongly reduces the rate of coarsening, particularly for times of ten hours or less in the temperature range of 1100 to 1400 °C. Calculated results also indicate that the rate of dissolution is very low at temperatures greater than the solvus for manganese sulfide inclusions in austenite. More... »

PAGES

2143-2153

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/bf02648384

DOI

http://dx.doi.org/10.1007/bf02648384

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1027023662


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