Synergistic Computational-Experimental Approach to Improve Ionene Polymer-Based Functional Hydrogels

The manifold applications of ionene‐based materials such as hydrogels in daily life, biomedical sciences, and industrial processes are a consequence of their unique physical and chemical properties, which are governed by a judicious balance between multiple non‐covalent interactions. However, one of the most critical aspects identified for a broader use of different polyelectrolytes is the need of raising their gelation efficiency. This work focuses on surfactant‐free ionene polymers 1−3 containing DABCO and N,N′‐(x‐phenylene)dibenzamide (x = ortho‐/meta‐/para‐) linkages as model systems to develop a combined computational‐experimental approach to improve the hydrogelation through a better understanding of the gelation mechanism. Molecular dynamics simulations of isomeric ionenes 1–3 with explicit water molecules point out remarkable differences in the assembly of the polymeric chains in each case. Interchain regions with high degree of hydration (i.e., polymer···water interactions) and zones dominated by polymer···polymer interactions are evident in the case of ortho‐ (1) and meta‐ (2) isomeric ionenes, whereas domains controlled by polymer···polymer interactions are practically inexistent in 3. In excellent agreement, ortho‐ionene 1 provides experimentally the best hydrogels with unique features such as thixotropic behavior and dispersion ability for single‐walles carbon nanotubes. A combined computational‐experimental approach identifies the topological constraints necessary to enhance gelation efficiency and achieve superior properties of hydrogels made from DABCO‐containing ionene polymers. The best performance of studied ionenes is established based on the critical gelation concentration, gelation kinetics, thermal and mechanical stability, optical properties, and dispersion ability for single‐walled carbon nanotubes.