Impact of Molecular Structure on Properties of n-Hexadecane and Alkylbenzene Binary Mixtures.
Brian H MorrowSabina MaskeyMicah Z GustafsonDianne Jeanne Luning PrakJudith A HarrisonPublished in: The journal of physical chemistry. B (2018)
Because of the complexity of petroleum-based fuels, researchers typically use simplified mixtures, known as surrogates, to study combustion behavior and to attempt to identify how physical properties are related to combustion. The process of determining the surrogate composition to yield a desired set of thermophysical properties can be a complicated and time-consuming task. As a result, the use of computer simulations to narrow the number of possible surrogate compositions is beginning to be explored. Herein, molecular dynamics (MD) simulations are used to model binary mixtures of n-hexadecane with either benzene, toluene, n-ethylbenzene, n-propylbenzene, or n-butylbenzene. Calculated densities are in quantitative agreement with experimental values. With the exception of the mixtures containing benzene, simulated excess molar volumes are also in very good agreement with measured values. Isentropic bulk moduli are in qualitative agreement with experiment, and reproduce interesting trends observed in the experimental data. Specifically, minima in the bulk moduli at intermediate compositions of several of the alkylbenzenes are correctly reproduced. In addition, the structures of the fluids are also examined. For mixtures of n-hexadecane with alkylbenzenes with longer chains, the orientation of the aromatic rings is not substantially impacted by composition. In contrast, increasing n-hexadecane content increases the ratio of parallel to perpendicular arrangements of benzene and toluene molecules. In those mixtures, this change in orientation of the aromatic rings could be responsible for the minima observed in the bulk moduli data. These results show that MD simulations can assist in development of fuel surrogates, both by predicting thermophysical properties and by providing insight into how molecular structure and composition affect those properties.
Keyphrases
- molecular dynamics
- ionic liquid
- density functional theory
- particulate matter
- electronic health record
- physical activity
- high resolution
- mental health
- systematic review
- magnetic resonance
- magnetic resonance imaging
- deep learning
- big data
- mass spectrometry
- single molecule
- monte carlo
- artificial intelligence
- sewage sludge