Quantitative Molecular Representation and Sequential Optimization of Athabasca Asphaltenes

摘要: The chemical complexity and diversity of an Athabasca asphaltene sample was described using a series molecular representations. representations were created with Monte Carlo construction method that represented molecules aromatic aliphatic groups. After the groups randomly sampled for molecule, connection algorithm linked them together to form consisting connected by chains thioethers. A sequential nonlinear optimization used select small subset consistent elemental, weight, NMR spectroscopy (both 13C 1H) data. To accurately represent analytical data sample, minimum five needed. On basis results optimization, at least 50 in starting population required produce analytically representation.