Investigations of polymer molecular design for high performance lubricant additives

Generally state-of-the-art viscosity modifiers (VM) or improvers (VI) are mono-functional, and aside from becoming more expensive with increasing performance, they offer opportunities for improvement. Our group is developing novel polymeric viscosity modifiers that incorporate improved shear resistance and a friction benefit to create a multipurpose additive. To that end, we are fine-tuning the molecular structure and polymer architecture of our compounds to enhance these desirable characteristics, with a focus on viscosity index improving (VII) properties. Several promising polymer classes are being investigated that range from hyperbranched polymers to comb-burst, hyperbranched analogs; modified polyethylene-based polymers; hybrid star polymers. Critical polymer parameters such as solubility, molecular weight, lipophilicity and hydrophobicity will be discussed, with an emphasis on how these relate to viscosity and friction. It is common practice to mitigate the inherent thinning tendency of base oils with increasing temperature by the addition of polymers of various topologies. These additives are known as viscosity index improvers (VII). It is widely accepted that the mechanism of action is an increase in free volume of the macromolecules at higher temperature, which results in a greater interaction with the oil and a reduction in the tendency toward lower viscosity. Linear and comb polymers have been extensively used for this purpose, as they provide the highest free volume or size change with applied heat as experienced in a running engine. However, these structures suffer degradation due to mechanical shear forces, thereby causing additive stability and lifetime issues for the oil. The general trend of polymer topology versus size, thermo-responsiveness, and shear stability is depicted in Figure 1. What the opposing trends indicate is that there is always a need to balance VII with shear stability and one can generally only maximize one parameter, but not the other.