Molecular simulations of surfactant adsorption on Iron oxide from hydrocarbon solvents

The performance of organic friction modifiers (OFMs) depends on their ability to adsorb onto surfaces and form protective monolayers. Understanding the relationship between OFM concentration in the base oil and the resulting surface coverage is important for improving lubricant formulations. Here, we use molecular dynamics (MD) simulations to study the adsorption of three OFMs─stearic acid (SA), glycerol monoostearate (GMS), and glycerol monooleate (GMO)─onto a hematite surface from two hydrocarbon solvents─n-hexadecane and poly(α-olefin) (PAO). We calculate the potential of mean force of the adsorption process using the adaptive biasing force algorithm, and the adsorption strength increases in the order SA < GMS < GMO. We estimate the minimum area occupied by OFM molecules on the surface using annealing MD simulations and obtained a similar hard-disk area for GMS and GMO but a lower value for SA. Using the MD results, we determine the adsorption isotherms using the molecular thermodynamic theory (MTT), which agree well with one previous experimental data set for SA on hematite. For two other experimental data sets for SA, lateral interactions between surfactant molecules need to be accounted for within the MTT framework. SA forms monolayers with lower surface coverage than GMO and GMS at low concentrations but also has the highest plateau coverage. We validate the adsorption energies from the MD simulations using high-frequency reciprocating rig friction experiments with different concentrations of the OFMs in PAO. For OFMs with saturated tailgroups (SA and GMS), we obtain good agreement between the simulations and the experiments. The results deviate for OFMs containing Z-unsaturated tailgroups (GMO) due to the additional steric hindrance, which is not accounted for in the current simulation framework. This study demonstrates that MD simulations, alongside MTT, are an accurate and efficient tool to predict adsorption isotherms at solid–liquid interfaces.ll authors thank the Repsol Foundation and the Repsol Technology Lab for financial support. We acknowledge the Partnership for Advanced Computing in Europe (PRACE) scheme for awarding us access to the J ̈ulich Wizard for European Leadership Science (JUWELS) system, Gauss Centre for Supercomputing at the Forschungszentrum J ̈ulich (GCS@FZJ), Germany.103 J.P.E. was supported by the Royal Academy of Engineering under the Research Fellowship scheme.Peer ReviewedPostprint (author's final draft