Metal–ligand coordination, as a non-covalent interaction, has been extensively applied in polymer matrices to enhance the mechanical toughness, tune viscoelasticity, and enable self-healing. In recent years, metal–ligand coordination has also been studied as a means of designing ionically conductive polymers. Silicone is a widely used elastomer due to its low cost, large strain to failure, and excellent chemical resistance. However, its poor ionic conductivity limits its application in many fields, including electrochemical devices, batteries, and fuel cells. In “Understanding How Metal–Ligand Coordination Enables Solvent Free Ionic Conductivity in PDMS“, we show that the incorporation of metal-ligand complexes into silicone can enhance its ionic conductivity without the need for a solvent and investigate the fundamental mechanisms governing this conductivity, using in-depth experimental studies with fully atomistic MD simulations. Our work provides insights into the strategic design of ionically conducting polymers that would benefit a range of applications. This effort was led jointly by MMD lab PhD graduate Xinyue Zhang and soon to be MS graduate Jinyue Dai, and in collaboration with Max Tepermeister, Prof Jingjie Yeo, and Yue Deng from the Archer lab.

Dynamic crosslinks and entanglements play a significant role in tuning mechanical properties of elastomers and gels. In our recent paper in the journal of Mechanics of Materials, we report a continuum modeling framework that considers these two mechanisms for adding toughness and strength to polymers – ionic bonding and entanglements. This theoretical study led by Zhongtong Wang investigates these mechanisms in the context of bulk polyelectrolyte mechanical properties. This work firstly establishes the constitutive model that couples entanglement evolution with the ionic crosslink effects and ionic bonds provide strength and dissipate energy without stiffness loss. This theoretical framework could direct the design of customized materials for various applications.