Prediction models for the yield strength of particle-reinforced unimodal pure magnesium (Mg) metal matrix nanocomposites (MMNCs)

Chang Soo Kim, Il Sohn, Marjan Nezafati, J. B. Ferguson, Benjamin F. Schultz, Zahra Bajestani-Gohari, Pradeep K. Rohatgi, Kyu Cho

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96 Citations (Scopus)

Abstract

Particle-reinforced metal matrix nanocomposites (MMNCs) have been lauded for their potentially superior mechanical properties such as modulus, yield strength, and ultimate tensile strength. Though these materials have been synthesized using several modern solid- or liquid-phase processes, the relationships between material types, contents, processing conditions, and the resultant mechanical properties are not well understood. In this paper, we examine the yield strength of particle-reinforced MMNCs by considering individual strengthening mechanism candidates and yield strength prediction models. We first introduce several strengthening mechanisms that can account for increase in the yield strength in MMNC materials, and address the features of currently available yield strength superposition methods. We then apply these prediction models to the existing dataset of magnesium MMNCs. Through a series of quantitative analyses, it is demonstrated that grain refinement plays a significant role in determining the overall yield strength of most of the MMNCs developed to date. Also, it is found that the incorporation of the coefficient of thermal expansion mismatch and modulus mismatch strengthening mechanisms will considerably overestimate the experimental yield strength. Finally, it is shown that work-hardening during post-processing of MMNCs employed by many researchers is in part responsible for improvement to the yield strength of these materials.

Original languageEnglish
Pages (from-to)4191-4204
Number of pages14
JournalJournal of Materials Science
Volume48
Issue number12
DOIs
Publication statusPublished - 2013 Jun 1

All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Mechanics of Materials
  • Mechanical Engineering

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    Kim, C. S., Sohn, I., Nezafati, M., Ferguson, J. B., Schultz, B. F., Bajestani-Gohari, Z., Rohatgi, P. K., & Cho, K. (2013). Prediction models for the yield strength of particle-reinforced unimodal pure magnesium (Mg) metal matrix nanocomposites (MMNCs). Journal of Materials Science, 48(12), 4191-4204. https://doi.org/10.1007/s10853-013-7232-x