ArticleJournal of molecular modeling2026
Functionalized carbon nanotubes as nanoinhibitors of asphaltene aggregation: a molecular dynamics approach for enhanced oil recovery.
Article in Journal of molecular modeling, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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3 authors.
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Abstract
contextAsphaltene aggregation and deposition pose major challenges in crude oil transport and processing. While extensive experimental studies have explored mitigation strategies, nanomaterials-particularly carbon nanotubes (CNTs)-have emerged as promising inhibitors due to their ability to adsorb asphaltenes and limit their clustering. However, experimental approaches provide limited insight into molecular-scale mechanisms. To address this, molecular dynamics (MD) simulations were performed to investigate interactions between model asphaltenes and CNTs in a toluene/heptane solvent. Five systems were studied: pristine CNTs and CNTs functionalized with carbamoyl (CONH
methodsGeometry optimizations and vibrational frequency calculations of toluene, heptane, the model asphaltene molecule, and the pristine carbon nanotube were performed using the Gaussian software package. These calculations were carried out within the framework of density functional theory (DFT) using the B3LYP functional and the 6-31G(d,p) basis set. The optimized structures obtained were subsequently used to construct the initial configurations for the molecular dynamics simulations and to derive Mulliken atomic charges for force-field parameterization. All-atom molecular dynamics simulations were performed using GROMACS 2023.3 and the OPLS-AA force field. After energy minimization using the steepest descent algorithm, the systems were equilibrated under NVT and NPT ensembles at 298.15 K and 1 bar. Production simulations were subsequently carried out for 150 ns using periodic boundary conditions and a 2 fs integration time step. Temperature and pressure were controlled using the velocity-rescaling thermostat and the Berendsen barostat, respectively. Long-range electrostatic interactions were treated using the Particle Mesh Ewald (PME) method, while bond constraints were maintained using the LINCS algorithm.
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