Nevertheless, capturing the adsorption and self-assembly processes from solution using realistic surfactant concentrations represents a considerable computational challenge. Until recently, a certain surface coverage of surfactant molecules molecules on the solid surfaces was usually assumed in MD simulations of OFMs. However, Chia et al. and Jaishankar et al. used MD simulations to study the adsorption of surfactants on iron oxide surfaces from hydrocarbon solvents. Chia et al. studied the competitive adsorption of the fuel additive 2-[(3-(dimethylamino)propyl)amino]methyl-4-dodecyl-6-methyl-phenol and ethanol from i-octane onto the α-Fe 2 O 3 (0001) surface at different temperatures. They showed that, while the free energy of adsorption of the additive was approximately two times larger than that for a single ethanol molecule, a single additive needs to displace up to five ethanol molecules to strongly adsorb onto the surface. Jaishankar et al. studied SA adsorption from n-heptane and n-hexadecane onto Fe 3 O 4 (111), Fe 3 O 4 (001), and hydroxylated Fe 3 O 4 (001) surfaces at room temperature. They found that adsorption was stronger on the hydroxylated surface and adsorption from n-hexadecane was much slower than from n-heptane due to stronger alignment of the molecules on the surface. They used a combined approach using MD and molecular thermodynamic theory (MTT) to calculate adsorption isotherms, which agreed well with experimental data obtained with QCM. The theoretical MTT model for the adsorption of non-ionic surfactants, originally developed by Nikas et al., was applied in combination with MD for the first time by Sresht et al. to study surface tensions at a water-air interface. Since then, it has been used to study adsorption in many systems, such as sodium dodecyl sulphate (SDS) on graphene from water, SDS on α-Al 2 O 3 nanoparticles from water, and organomolybdenum friction modifiers on borondoped diamond-like-carbon (DLC) from n-heptane. Chia et al. and Jaishankar et al. extracted the potential of mean force (PMF) along the reaction coordinate using umbrella sampling (US) and the weighted histogram analysis method (WHAM). Even using modern simulation software and high performance computing (HPC) architectures, this method requires hundreds of nanoseconds of simulation time to obtain converged PMFs. For example, Jaishankar et al. used an overall simulation time of more than 1 µs to obtain the PMF describing the adsorption of SA onto hematite from n-hexadecane. A potentially more efficient method to obtain the PMF for surfactants at solid-liquid interfaces is the adaptive biasing force (ABF) algorithm. The ABF method has been used to study adsorption at solid-liquid interfaces for a range of surfactants from water, such as SDS on graphene, 37 chlorogenic acid on polydimethylsiloxane, 44 lipoic acid on silver, peptides on gold, proteins on hydroxyapatite and graphene, ethylene glycols on calcite and hematite, and a wide range of organic molecules on carbon nanotubes, graphene, and graphene oxide. In this study, we compare the adsorption of different OFMs from hydrocarbon solvents onto iron oxide surfaces. More specifically, ABF-MD is used to study the adsorption of SA, GMS and GMO from n-hexadecane and hydrogenated 1-decene trimer onto the α-Fe 2 O 3 (010) surface. We show that the OFM headgroup and tailgroup structure, as well as the solvent, significantly affect the adsorption behaviour. Once the adsorption PMF is obtained, the hard-disk area occupied by the molecules on the surface due to steric effects is estimated using separate annealing MD simulations. Subsequently, the relation between the bulk concentration of the OFMs in the solvent and the surface coverage, i.e. the adsorption isotherm, is determined using the MTT model. Finally, the Jahanmir and Beltzer model, together with High Frequency Reciprocating Rig (HFRR) friction measurements, are used to experimentally validate the calculated adsorption energies.