Abstract
Deposits can reduce engine performance and increase emissions, particularly in modern direct-injection engines. Surfactants known as deposit control additives (DCAs) ad- sorb and self-assemble on the surface of deposit precursors to keep them suspended in the fuel. Here, we show how molecular simulations can be used to virtually screen the ability of surfactants to bind to a major class of carbonaceous deposits, polyaromatic hydrocarbons. We use molecular dynamics with the adaptive biasing force method to generate the potential of mean force as a function of the distance between the surfactants and model deposits in gasoline and diesel fuel surrogates. We find that a zwitterionic surfactant outperforms non-ionic polyisobutylene succinimide for bind- ing to these aromatic species. The amine groups in the succinimide head-group only weakly adsorb on the polyaromatic deposit, while additional functional groups in the zwitterionic surfactant, particularly the ammonium ion, markedly enhance the binding strength. We decompose the adsorption free energies of the surfactants into entropic and enthalpic components, to find that the latter dominates the attraction from these non-aqueous solvents. The adsorption free energy of both surfactants is slightly weaker from n-hexadecane (diesel) than iso-octane (gasoline), which is due to the stronger molecular layering on the deposit of the former. Density functional theory calculations of the adsorption of DCA fragments validate the force field used in the molecular dy- namics simulations and provide further insights into the nature of the intermolecular interactions. The approach introduced here show considerable promise for accelerating the discovery of novel DCAs to facilitate more advanced fuel formulations to reduce emissions.
Supplementary materials
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Supporting Information
Description
COLVARS configuration file, PMF convergence studies, free energies profiles using standard OPLS-AA parametrisation, and further insights on DFT calculations
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Graphical Abstract
Description
Graphical abstract conveying the multiscale modelling approach proposed in this work, comprising enhanced-sampling MD and DFT simulations to unravel the atomistic mechanisms underpinning the adsorption of surfactants on deposit precursors consisting of polyaromatic hydrocarbons.
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