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A model for volume fraction and/or particle size selection in metal matrix composites

► Face-centered cubic model for volume fraction and/or particle size selection. ► An alternative to the cubic model proposed by Tan and his successors. ► Uniform distribution criteria both for bi-modal and tri-modal composites. ► The new model is applicable to a wider range of reinforcement volume f...

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Bibliographic Details
Published in:Materials science & engineering. A, Structural materials : properties, microstructure and processing Structural materials : properties, microstructure and processing, 2011, Vol.530, p.574-579
Main Authors: Kai, X.Z., Li, Z.Q., Zhang, W.L., Fan, G.L., Jiang, L., Lu, W.J., Zhang, D.
Format: Article
Language:English
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Summary:► Face-centered cubic model for volume fraction and/or particle size selection. ► An alternative to the cubic model proposed by Tan and his successors. ► Uniform distribution criteria both for bi-modal and tri-modal composites. ► The new model is applicable to a wider range of reinforcement volume fraction. ► The new model is more accurate to predict the actual reinforcement distributions. In this study, a face-centered cubic (f.c.c) model for volume fraction and/or particle size selection in particle-reinforced metal matrix composites (PMMCs) via powder metallurgy (P/M) routes is presented to get a uniform distribution of reinforcements. The f.c.c model is an alternative to the cubic model proposed by Tan and Zhang [12] and its extension proposed by Reihanian et al. [14]. Uniform distribution criteria by the f.c.c model were proposed both for bi-modal and tri-modal composites obtained after different deformation processing, such as extrusion, rolling, high pressure torsion (HPT) and equal channel angular pressing (ECAP). Compared with the previous cubic models, the f.c.c model is applicable to a wider range of reinforcement volume fraction. Evaluation results both from some P/M PMMCs reported in literatures and the P/M B 4C/Al composites fabricated in the present study, showed that the f.c.c model is more accurate to simulate and predict the actual reinforcement distributions.
ISSN:0921-5093
1873-4936
DOI:10.1016/j.msea.2011.10.022