For decades, the prediction of polymer material properties using macromolecular computational methods has faced significant challenges due to the requirement for extensive databases, inefficiencies in computation time, and limitations in predictive accuracy. Herein we discover that the calculated binding energy of supramolecular fragments correlates linearly with the mechanical properties of polyurethane elastomers. This finding suggests that small molecule calculations may offer a more efficient way to predict polymer performance. Experimental validation supports this insight, with the top-performing elastomer exhibiting a toughness of 1.1 GJ m-3, along with high mechanical strength, transparency, scalability, self-healing capability, and recyclability. Furthermore, this material presents a performance-to-cost ratio double that of commercially available high-performance elastomers, unlocking potential for broader applications where current materials may fall short.
Wang et al. (2025) studied this question.