Molecular view of the plasticization process of poly(vinyl) alcohol.

The use of atomistic simulations is currently being used in addressing questions of mechanism in many materials, such as self-assembly phenomena in polymers, or host-guest binding applied for drug design, among others. When combining simulations with advance sampling methods that are able to bias the potential energy surface based on preset slow collective variables the simulation improves its efficiency, and this opens the possibility to treat more realistic complex systems. In this work, we will follow the analysis of the free energies governing the interactions of complex systems by employing the Artificial Neural Network sampling method developed by Hythem and Whitmer (JCP 2018). The discussion will highlight the configurational sampling using atomistic simulations of a polymer chain model, and its interaction with different small-weight molecules, representing with their interaction the plasticization process. In particular, we focus on conformational and hydrogen bond-structure changes induced in globules of a polymer chain by the plasticizer molecules, with the hypothesis that hydrogen bonding plays a role in the incorporation into polymer materials, and thus in the observed mechanical properties. The findings derived from this system showcase physical features relevant to the design of tailored materials, and the methods developed are intended to be part of a robust framework applicable to an assortment of experimental works useful for industrial proposes.