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Journal of Materials Science

, Volume 50, Issue 10, pp 3812–3824 | Cite as

Morphology and thermal degradation studies of melt-mixed poly(hydroxybutyrate-co-valerate) (PHBV)/poly(ε-caprolactone) (PCL) biodegradable polymer blend nanocomposites with TiO2 as filler

  • J. P. Mofokeng
  • A. S. Luyt
Original Paper

Abstract

The morphology, thermal stability and thermal degradation kinetics of melt-mixed poly(hydroxybutyrate-co-valerate) (PHBV)/poly(ε-caprolactone) (PCL) blends filled with small amounts of titanium(IV)oxide (TiO2) nanoparticles were investigated. The nanoparticles were mostly well dispersed in both phases of the PHBV/PCL blend, which showed a co-continuous morphology at a 50/50 w/w ratio, but some large agglomerates were also observed. The equal dispersion of the TiO2 nanoparticles in both polymers was attributed to the polymers having the same surface properties, polarities and viscosities. The thermal stability of PHBV was improved when blended with the more thermally stable PCL, but the PCL became less thermally stable when blended with PHBV. The introduction of only 1 wt% of TiO2 nanoparticles seems to have observably improved the thermal stabilities of both polymers in the blend, but the nanoparticles probably retarded the evolution of the degradation products through their interaction with these products. Further improvement in thermal stability at higher nanoparticle contents was insignificant because of the nanoparticles’ agglomeration which reduced their effectiveness. Changes in the activation energies of degradation, determined through the Flynn–Wall–Ozawa model from thermogravimetric analysis mass loss data, and differences between the Fourier-transform infrared spectra of the degradation volatiles obtained during the degradation process, to a large extent support the other observations.

Keywords

TiO2 Nanoparticles Scanning Transmission Electron Microscopy PHBV Thermal Degradation Kinetic Mass Loss Temperature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The authors would like to thank the National Research Foundation (NRF) for financial support.

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Center for Advanced MaterialsQatar UniversityDohaQatar
  2. 2.Department of ChemistryUniversity of the Free State (Qwaqwa campus)PhuthaditjhabaSouth Africa

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