Process optimization of functionalized MWCNT/polyetherimide nanocomposites for aerospace application. (5th August 2017) - Pitchan, Mohan Kumar; Bhowmik, Shantanu; Balachandran, Meera; Abraham, M.
Abstract: Polyetherimide (PEI) is a high performance thermoplastic polymer that retains its properties at elevated and cryogenic temperatures. Nanofiller reinforced PEI used in aerospace structures will substantially reduce the payload. This study attempts to optimize nanofiller content and process parameter for melt compounding of PEI/acid (COOH) functionalized MWCNTs (Multi-walled Carbon Nanotube) nanocomposite using Response surface methodology (RSM). Face Centered Central Composite Design (FCCD) with two factors viz. MWCNT content and extrusion screw speed at three levels each is used to model and optimize nanocomposite properties relevant to aerospace applications. FTIR spectrum confirmed the functionalization of MWCNTs while morphological analysis confirmed the dispersion of MWCNTs. COOH-MWCNTs reinforced composite showed enhanced thermal and mechanical properties along with better retention of properties upon exposure to gamma irradiation and atomic oxygen. These properties were modeled with non-linear quadratic equations using regression analysis and verified by validation experiments. Optimization for performance of nanocomposites for aerospace application has been revealed by overlapping the contour plots within the practical constraints to recognize the combination of factor ranges. Graphical abstract: Highlights: Enhanced properties in high performance polyetherimide nanocomposite. Achieved better dispersion of acid treated Multi-walled carbon nanotubes in the polymer matrix using extrusion processing. Achieved better interfacial interaction between polymer and nanotubes evident from morphological and spectroscopic data. The nanocomposites possess better retention of mechanical properties even after exposure to space environment condition. Face centered composite design used to model and optimize the nanocomposite properties using regression analysis.