Ab Initio Modeling Of Friction Reducing Agents Shows Quantum Mechanical Interactions Can Have Macroscopic Manifestation

TL;DR

This study uses quantum mechanical simulations to show how microscopic interactions of friction reducing agents influence their macroscopic friction properties in plastic sheet production.

Contribution

It demonstrates that quantum interactions determine the arrangement of erucamide and behenamide chains, explaining their differing friction coefficients.

Findings

Erucamide chains form closer π-π stacking interactions.

Behenamide chains are more spread out, allowing more solvent penetration.

The chain arrangement correlates with measured friction differences.

Abstract

Two of the most commonly encountered friction reducing agents used in plastic sheet production are the amides known as erucamide and behenamide, which despite being almost identical chemically, lead to markedly different values of the friction coefficient. To understand the origin of this contrasting behavior, in this work we model brushes made of these two types of linear chain molecules using quantum mechanical numerical simulations under the Density Functional Theory at the B97D/6-31G(d,p)level of theory. Four chains of erucamide and behenamide were linked to a 2X10 zigzag graphene sheet and optimized both in vacuum and in continuous solvent using the SMD implicit solvation model. We find that erucamide chains tend to remain closer together through {\pi}{\pi} stacking interactions arising from the double bonds located at C13 C14, a feature behenamide lacks and thus a more spread configuration is obtained with the latter. It is argued that this arrangement of the erucamide chains is responsible for the lower friction coefficient of erucamide brushes, compared with behenamide brushes, which is a macroscopic consequence of cooperative quantum mechanical interactions. While only quantum level interactions are modeled here, we show that behenamide chains are more spread out in the brush than erucamide chains as a consequence of those interactions. The spread out configuration allows more solvent particles to penetrate the brush, leading in turn to more friction, in agreement with macroscopic measurements and mesoscale simulations of the friction coefficient reported in the literature.