Topological Programmability of Isomerizable Polymers.

Topology isomerizable networks (TINs) can be programmed into numerous polymers exhibiting unique and spatially defined (thermo-) mechanical properties. However, capturing the dynamics in topological transformations and revealing the intrinsic mechanisms of mechanical property modulation at the microscopic level is a significant challenge. Here, we use a combination of coarse-grained molecular dynamics simulations and reaction kinetic theory to reveal the impact of dynamic bond exchange reactions on the topology of branched chains. We find that, the grafted units follow a geometric distribution with a converged uniformity, which depends solely on the average grafted units of branched chains. Furthermore, we demonstrate that the topological structure can lead to spontaneous modulation of mechanical properties. The theoretical framework provides a research paradigm for studying the topology and mechanical properties of TINs.

Designing Superselectivity in Linker-Mediated Multivalent Nanoparticle Adsorption.

Using a statistical mechanical model and numerical simulations, we provide the design principle for the bridging strength (ξ) and linker density (ρ) dependent superselectivity in linker-mediated multivalent nanoparticle adsorption. When the bridges are insufficient, the formation of multiple bridges leads to both ξ- and ρ-dependent superselectivity. When the bridges are excessive, the system becomes insensitive to bridging strength due to entropy-induced self-saturation and shows a superselective desorption with respect to the linker density. Counterintuitively, lower linker density or stronger bridging strength enhances the superselectivity. These findings help the understanding of relevant biological processes and open up opportunities for applications in biosensing, drug delivery, and programmable self-assembly.

A bond swap algorithm for simulating dynamically crosslinked polymers.

Materials incorporating covalent adaptive networks (CAN), e.g., vitrimers, have received significant scientific attention due to their distinctive attributes of self-healing and stimuli-responsive properties. Different from direct crosslinked systems, bivalent and multivalent systems require a bond swap algorithm that respects detailed balance, considering the multiple equilibria in the system. Here, we propose a simple and robust algorithm to handle bond swap in multivalent and multi-species CAN systems. By including a bias term in the acceptance of Monte Carlo moves, we eliminate the imbalance from the bond swap site selection and multivalency effects, ensuring the detailed balance for all species in the system.