Glassy state molecular mobility and its relationship to the physico-mechanical properties of plasticized...

Changes in tensile properties and the glass transition temperature (T_g) of plasticized polymer films are typically attributed to molecular mobility, often with no empirical data to support such an assertion. Herein solvent cast HPMC films containing varying amounts of PEG, as the plasticizer, were used to assess the dependence of tensile properties and the T_g on glassy state molecular mobility. Molecular mobility (molecular relaxation time and temperature) parameters were determined by Thermally Stimulated Current Spectroscopy (TSC). The tensile properties and T_g of the HPMC films were determined by texture analysis and DSC, respectively. Molecular mobilities detected by TSC were cooperative and occurred at temperatures (T_g') well below (113 to 127 °C) the bulk T_g. The relaxation times (τ) were 71 ± 1, 46 ± 1, 42 ± 1, 36 ± 1 and 29 ± 1 s for HPMC films containing 0, 6, 8, 11 and 17% (w/w) PEG, respectively. The T_g and glassy state molecular mobility were found to be intimately linked and demonstrated a linear dependence. While tensile strength was found to be linearly related to molecular relaxation time, tensile elongation and elastic modulus exhibited a non-linear dependence on molecular mobility. The data presented in this work demonstrates the complex nature of the relationship between plasticizer content, molecular mobility, T_g and tensile properties for plasticized polymeric films. It highlights the fact that the dependence of the bulk physico-mechanical properties on glassy state molecular mobility, differ greatly. Therefore, empirical characterization of molecular mobility is important to fully understand and predict the thermo-mechanical behavior of plasticized polymer films. This work demonstrates the unique capability of TSC to provide key information relating to molecular mobility and its influence on the bulk properties of materials. Data generated using TSC could prove useful for stability and performance ranking, in addition to the ability to predict materials behavior using data generated at or below typical storage conditions in the pharmaceutical, food, and polymer industries.