Quantification of the scratch-healing efficiency for novel zwitterionic polymers

In this work, we present a new strategy to engineer novel self-healing ionomers, namely, zwitterionic polymers, and a comprehensive analysis of their mechanical, viscoelastic, and scratch-healing properties. This new method enables reproducible damage of the polymer surfaces, calculation of the scratch volume through tactile profile scans, and quantification of the self-healing efficiency. Based on the results of the scratch tests and complementary rheology, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA) and hardness tests, new trends, and structure–property relationships can be identified. Polymers: Materials that pull themselves together A novel soft material that can heal itself has been engineered by researchers in Germany. Polymeric molecules are formed by long chains of atoms. Some polymers can reform when broken, giving them the intrinsic ability to repair scratches or tears. These self-healing properties are useful for applications in long-lasting biomedical implants, for example. Martin D. Hager and colleagues from the Friedrich Schiller University Jena synthesized and characterized a novel type of self-healing materials using a so-called zwitterionic polymer, a polymer which includes both positive and negative charges in the side-chains. Using a simple new method to create their material, the team investigated its hardness, its viscoelastic properties and quantified how efficiently it healed scratches of different sizes. This novel approach to scratch-healing tests, which utilizes the scratch volume, is both reproducible and quantifiable and could be extended to other materials. New self-healing zwitterionic polymer networks are prepared and the healing efficiency is quantified by 3D plotting, as well as volume calculation of the damaged surface after tactile profile scans. The results are complemented by comprehensive investigations of the mechanical, viscoelastic, and thermal properties in order to identify structure-property relationships.