Interpretation of thermal transitions and phase transformations in semi-crystalline PVDF/PEO/graphene nanocomposites characterized by modulated-temperature DSC

The glass transition temperature (T-g) and binodal phase transition (T-b) of poly(vinylidene fluoride)/ poly(ethylene oxide)/graphene (PVDF/PEO/graphene) nanocomposites were monitored across the complete composition range by modulated-temperature differential scanning calorimetry (MTDSC) due to better sensitivity and resolution over the conventional DSC. A single glass transition temperature at different temperature regions was observed for the nanocomposites. To have a better understanding of the level of homogeneity, the variation of composition-dependent T-g was modeled through Fox, Gordon-Taylor, and Kwei equations. Kwei equation was well-fitted over the experimental data by the introduction of self-concentration concept. Additionally, changes in the apparent heat capacity (C-p(ap)) signal at temperatures above the melting points were attributed to the phase separation. A lower critical solution temperature (LCST) phase diagram was proposed based on MTDSC which was further confirmed by scanning electron microscopy (SEM) observations and dynamic mechanical analysis (DMA). The melting and crystallization behavior of the nanocomposites were evaluated by DSC regarding the semi-crystalline nature of polymeric components and their relatively high degree of crystallinity. The findings revealed that the crystallization degree was the parameter that changed the most. The effect of graphene nanosheets and blend composition on thermal degradation was also investigated by thermogravimetric analysis (TGA). [GRAPHICS] .

Automated summary

The glass transition temperature and binodal phase transition of PVDF/PEO/graphene nanocomposites were monitored using MTDSC, with the composition-dependent T-g modeled through various equations. A LCST phase diagram was proposed, and the melting and crystallization behavior of the nanocomposites were evaluated, with crystallinity found to be the most affected parameter. The effect of graphene nanosheets and blend composition on thermal degradation was also investigated using TGA.