Transportation is currently the sector with the highest reliance on fossil fuels and accounts for more than a third of global CO 2 emissions. Despite increasing electrification of the transport fleet, the vast majority of vehicles still use fossil fuel-powered internal combustion engines (ICEs). It is therefore crucial to increase the efficiency of ICEs to ensure that fuel consumption and the subsequent CO 2 emissions are minimised. A major issue affecting the efficiency of modern ICEs are deposits that form on metal surfaces inside the engine, particularly those on the fuel injectors. These deposits have long been recognised as a problem in diesel-powered compression ignition ICEs, where recent attention has focused on internal injector deposits. Historically, injector deposits have been less of an issue for gasoline-powered spark ignition ICEs with port fuel injection. The majority of new spark ignition engines now use gasoline direct ignition technology, which can deliver higher power output and better fuel economy than the port fuel technology, but at the expense of increased particulate matter emissions. Another related problem with the widespread adoption of gasoline direct ignition technology is that it has led to an increase in deposit-related issues for gasoline-powered ICEs. It is well known that deposits can lead to a decrease in power and fuel economy, as well as an increase in CO 2 and pollutant emissions from ICEs. Recent studies have confirmed that polyaromatic hydrocarbons (PAHs) are major components of engine deposits formed in diesel and gasoline direct injection engines. PAHs are formed from the breakdown of fuel molecules through thermo-oxidation, which is followed by polymerization of the degradation products. The PAH molecules, acting as deposit precursors, grow up to ∼800 Da 10 and agglomerate in the fuel until they become insoluble and are deposited onto metal surfaces. Likewise, the degradation processes can be accelerated by these surfaces within the engine. It is worth noting that the size of the PAH molecules is similar to those found in soot (239-838 Da). Deposits contain a significant amount of oxygen when initially formed, which decreases with time while their aromatic content and porosity increases. The main mitigation strategy for engine deposits is to add surfactants to gasoline and diesel fuel formulations, which are known as detergents or deposit control additives (DCAs). DCAs act to prevent the agglomeration of PAHs to form insoluble deposits (keepclean mode) and remove those that have previously formed on the metal surface (clean-up mode). The effectiveness of DCAs depends on their ability to adsorb onto deposits and metal surfaces via their polar head-group. The non-polar tail-group provides solubility in the affine fuel chemistry, besides preventing the deposits aggregation and further deposition through steric repulsion effects. The predominant and most effective chemistry for ICEs detergency over the past few decades has been polyisobutylene succinimide (PIBSI) additives. PIBSI derivatives are also used as dispersant additives in engine lubricants to stabilise soot or other deposit-related particles. PIBSIs have proven to be effective to neutralise acidic fuel degradation products (such as hydroperoxides) given the basic nature of secondary amines, although many different polyamine head-groups have been proposed in the literature. Other DCA chemistries have also been employed, such as alkylpropoxylates and alkylbutoxylates, 32 polyhydroxystearic acid, 33 polyether amines, Mannich bases, and quaternary ammonium salts. Experimental studies have measured adsorption isotherms for DCAs on model deposits from several non-polar fluids. Gasoline, diesel, and lubricant surrogates, such as iso-octane, xylene, decalin, and n-dodecane have all been used as solvents. For reproducibility and cost reasons, these studies mostly used carbon black rather than real deposits, which is commonly employed as a surrogate for soot and engine deposits. Most of these studies observed adsorption isotherms that were consistent with Langmuir theory, which implies monolayer adsorption. Adsorption isotherms for some DCAs could not be fit with the standard Langmuir equation because a sharp increase in surface coverage was observed at high concentrations. This behaviour has been attributed to hemimicelle or multilayer formation on the surfaces. Molecular dynamics (MD) simulations have become an integral tool for the study of sur-factant adsorption and self-assembly at solid-liquid interfaces for a wide range of industriallyimportant systems. Prominent examples include formulated products such as paints, coatings, 45 fuels, and lubricants. When compared to the nanosecond timescales accessible to conventional MD simulations, surfactant adsorption and self-assembly are relatively slow processes. The bottleneck of MD simulations lies in that there are high-energy barriers separating different metastable conformations, so that transitions between them are rare events and the system is said to be quasi non-ergodic. In an attempt to extend MD to longer timescales, several enhanced sampling methods have been developed. Widely used techniques to improve the sampling efficiency within MD simulations rely on modifying the potential energy landscape by adding a bias potential to the Hamiltonian of the system. This approach underlies methods such as umbrella sampling and metadynamics. Methodologies framed on different theoretical principles have been devised too, such as the adaptive biasing force (ABF) technique that we adopt in this study. The ABF scheme involves the iterative modification of the average force felt by the system and, importantly, it does not require prior knowledge of the free energy landscape. Enhanced sampling methods have been applied to study surfactant adsorption at a wide range of aqueous interfaces, such as polymer-water, graphene-water, metal-water, metal oxide-water, 60 mineral-water, and membrane-water. Far fewer studies have used enhanced sampling to investigate surfactant adsorption within non-aqueous solvents, and those that have been performed have focused on metal-glycol or metal oxide-alkane interfaces. We are not aware of any previous MD simulations with enhanced sampling of surfactant adsorption at PAH-alkane interfaces, which are of relevance to DCAs. In this study, we develop a computational framework suitable for the virtual screening of DCAs in terms of their propensity to bind to deposits. We use MD simulations with the ABF method to compare the adsorption of non-ionic PIBSI and a zwitterionic surfactant on PAHs from alkane solvents representative of gasoline and diesel fuels. To understand the thermodynamic driving force for adsorption in these systems, we decompose the free energy into entropic and enthalpic contributions. Further insights are produced using density functional theory (DFT) calculations, which help to identify the relative importance of the different binding mechanisms as well as supporting MD results. We also check the PAH size dependency of the adsorption process and assess methodological considerations of relevance, such as the effect of an appropriate modelling of π-electrons on the adsorption free energy.