Multiscale modeling of viscosity index improver (VII) polymers

Viscosity index improvers (VIIs) are compounds added to lubricants to help them maintain a uniform viscosity across a wide temperature range, allowing them to make important contributions to energy efficiency and wear protection. However, VIIs are typically high-molecular-weight polymers present at significant concentrations (~5 wt%), making them difficult to study using traditional particle-based simulation methods (e.g., all-atom or coarse-grained molecular dynamics) due to length and time scale limitations. To overcome this obstacle, we employ a workflow where small-scale, atomistic simulations are used to parameterize statistical field theory models, which can then be used to probe the behavior of VIIs of realistic sizes while maintaining a connection to the underlying chemistry. This multiscale computational approach has the potential to accelerate discovery of novel VIIs that have improved performance and are more environmentally friendly. We demonstrate the capability of this approach by predicting various thermodynamic properties, including critical micelle concentrations and phase transitions, of a model system consisting of acrylic copolymers in a model base oil.