Algorithm-Assisted Molecular Dynamics Simulations Revealed the Microscopic Mechanism by Which TX-100 and Biosurfactants Regulate the Separation of Heavy Oils from Solids

To enhance quantitativeness and interpretability in identifying the mechanisms of complex oil–mineral–surfactant systems, this paper introduces an algorithmic molecular simulation analysis approach, transforming molecular dynamics trajectory data into comparable multidimensional molecular descriptors. Specifically, based on parameters such as radial distribution functions, mean square displacement, interface concentration distribution, adsorption energy attenuation, hydrogen bond statistics, and electrostatic interactions, an algorithm analysis framework was constructed covering “trajectory data acquisition—feature descriptor extraction—interface behavior recognition—separation mechanism classification.” This framework can identify differentiated regulatory patterns of different surfactants on SARA (saturates, aromatics, resins, asphaltenes) component migration, adsorption, and desorption behavior from a large amount of dynamic simulation data, thereby improving the structural expression and mechanism discrimination capabilities of molecular simulation results. In order to clarify the component-selective microscopic mechanisms of surfactants in the separation of heavy oil from oil sands, this work employs molecular dynamics simulations to study the interactions of the non-ionic surfactant TX-100 and the biosurfactants sophorolipid and rhamnolipid with the SARA fractions of heavy oil, both in the absence and presence of calcite mineral surfaces. The results show that all three surfactants act mainly through weak long-range interactions, but with distinct mechanisms: TX-100 preferentially screens small-molecule saturates through long-chain steric hindrance and hinders the diffusion of asphaltenes; sophorolipid promotes the preferential desorption of resins via hydrogen bonding; and rhamnolipid drives the desorption of aromatics at later stages through hydrophobic–electrostatic synergy. The C001 crystal surface exhibits the strongest adsorption affinity across all systems; the mineral surface overall prolongs the diffusion equilibrium time and amplifies the above kinetic differences. This study establishes three molecular-scale mechanisms—steric hindrance sieving, hydrogen-bond-promoted desorption, and electrostatically driven desorption—and reveals the universal adsorption platform effect of the C001 crystal surface, providing a theoretical basis for the molecular design of surfactants aimed at the selective separation of heavy oil components.