HPC MSU

Publication Abstract

Characterization, Prediction, and Optimization of Flexural Properties of Vapor-Grown Carbon Nanofiber/Vinyl Ester Nanocomposites by Response Surface Modeling

Lee, J., Nouranian, S., Torres, G. W., Lacy, T., Toghiani, H., Pittman, C., & DuBien, J. L. (2013). Characterization, Prediction, and Optimization of Flexural Properties of Vapor-Grown Carbon Nanofiber/Vinyl Ester Nanocomposites by Response Surface Modeling. Journal of Applied Polymer Science. 130(3), 2087-2099. DOI:10.1002/app.39380.

Abstract

A design of experiments and response surface modeling were performed to investigate the effects of formulation and processing factors on the flexural moduli and strengths of vapor-grown carbon nanofiber (VGCNF)/vinyl ester (VE) nanocomposites. VGCNF type (pristine, surface-oxidized), use of a dispersing agent (no, yes), mixing method (ultrasonication, high-shear mixing, and a combination of both), and VGCNF weight fraction (0.00, 0.25, 0.50, 0.75, and 1.00 parts per hundred parts resin (phr)) were selected as independent factors. Response surface models were developed to predict flexural moduli and strengths as a continuous function of VGCNF weight fraction. The use of surface-oxidized nanofibers, a dispersing agent, and high-shear mixing at 0.48 phr of VGCNF led to an average increase of 19% in the predicted flexural modulus over that of the neat VE. High-shear mixing with 0.60 phr of VGCNF resulted in a remarkable 49% increase in nanocomposite flexural strength relative to that of the neat VE. This study underscores the advantages of statistical design of experiments and response surface modeling in characterizing and optimizing polymer nanocomposites for automotive structural applications. Moreover, response surface models may be used to tailor the mechanical properties of nanocomposites over a range of anticipated operating environments.