Modeling and Simulations of Self-Assembly of Polymers

The realm of polymer self-assembly has emerged as a burgeoning domain within the sphere of materials science, presenting numerous potential applications in nanotechnology and nanobiotechnology. It is imperative to scrutinize the energy landscape governing the interactions among self-assembled polymers, as well as to elucidate the trajectory of these polymers and the strategies for achieving the ultimate morphology.

To comprehend the conformational changes in detail, one can employ molecular dynamics (MD) simulations along with umbrella sampling and the weighted histogram analysis method (WHAM) to construct free energy profiles. WHAM, a technique commonly utilized to unveil energy landscapes for tasks such as ligand-protein binding and conformational alterations in proteins, has recently been successfully adapted to explore polymer adsorption phenomena, like the absorption of ethylene/hexene copolymers onto graphene. This simulation methodology facilitates the estimation of energy barriers between transitional states and their implications for aggregation kinetics.

Another captivating facet in the realm of self-assembly pertains to transition pathways linking distinct states. The weighted ensemble (WE) method, a versatile and potent path sampling technique in MD simulations, enables the identification of transition paths and rates. This methodology holds the potential to uncover the underlying mechanisms governing a wide array of nano- and nanobio-systems.