Modeling and Simulations of Self-Assembly of Polymers

Polymer self-assembly has emerged as a rapidly growing field within materials science, offering numerous potential applications in nanotechnology and nanobiotechnology. It is crucial to investigate the energy landscape governing the interactions between self-assembled polymers, as well as to understand their trajectory and the strategies for achieving the desired morphology.

To study conformational changes in detail, molecular dynamics (MD) simulations, combined with umbrella sampling and the weighted histogram analysis method (WHAM), can be used to construct free energy profiles. WHAM, a technique widely used to explore energy landscapes in processes such as ligand-protein binding and conformational changes in proteins, has recently been adapted to investigate polymer adsorption phenomena, such as the absorption of ethylene/hexene copolymers onto graphene. This simulation approach helps estimate energy barriers between transitional states and their impact on aggregation kinetics.

Another interesting aspect of self-assembly involves transition pathways connecting distinct states. The weighted ensemble (WE) method, a powerful and versatile path sampling technique in MD simulations, enables the identification of transition paths and rates. This method has the potential to uncover the underlying mechanisms governing a wide range of nano- and nanobiological systems.