Enclose Biobased Content into Polyurethane Elastomers: A Summary of Synthetic Routes and an Inverse Prediction of...

Biobased polyurethane elastomers (BPUEs) got vigorous exploration in recent decade, clarifying how biobased content affect their mechanical and thermal properties becomes critical. Here, a comprehensive BPUE dataset with 506 splines associated with a brief summary for the transformation of biobased content into polyurethane are presented. Distributions for typical mechanical and thermal properties including Young's modulus, tensile strength, elongation at break, and glass transition temperature (T_g) are clarified. A linear relationship T_g ^DMA = 0.98*T_g + 19.43K is found for T_g's measured by differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA). Then, a binary classification model with an accuracy of 0.80 to distinguish PUEs with and without biobased content, and a regression model with the coefficient of determination of 0.89 to predict the mass percentage of biobased content (BBC%) are constructed. Based on these predictive models, important correlations are observed, including the strong dependence of Tg and tanδ on BBC%, and the weak preference to use longer spline in tensile test, lower heating rates in DSC and DMA measurements for BPUEs with higher BBC%. These inverse predictive models provide a cost-effective way to quantify the biobased content in PUE products, without prior knowledge of their exact composition and formulas.