Crude oil-derived fuels containing natural sulfur contaminants contribute significantly to the energy mix. Therefore, in addressing cleaner production sustainable goals, sulfur must be removed as these sulfur contaminants reduce the quality of the fuel. In this work, N-methyl-2-pyrrolidone (NMP) and sulfolane were investigated for their capability to remove thiophene from model fuels, such as n-octane and n-hexadecane. Ternary liquid–liquid equilibria (LLE) data were measured for four ternary systems, namely, n-octane/n-hexadecane + thiophene + NMP/sulfolane, at 308.15 K and 0.1 MPa. The NRTL model was used to correlate the experimental data. The maximum likelihood method was used to minimize the objective function. The regressed binary interaction parameters were consistent with measured data with an average root-mean-square deviation (RMSD) of 0.00024. The binary interaction parameters from the data regression were verified by assessing the topology of the model-predicted Gibbs energy of mixing for the studied mixtures. The systems generally exhibited the type 1 LLE behavior except for the system of n-hexadecane + thiophene + sulfolane, which exhibited type 2 behavior. Results indicate that sulfolane exhibits increased selectivity to thiophene from n-octane and n-hexadecane than NMP.

中文翻译：

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{正辛烷/正十六烷 + 噻吩 + NMP/环丁砜} 在 T = 308.15 K 和 P = 0.1 MPa 时的液-液平衡 (T–x–x) 数据

含有天然硫污染物的原油衍生燃料对能源结构做出了重大贡献。因此，在实现清洁生产可持续目标时，必须去除硫，因为这些硫污染物会降低燃料的质量。在这项工作中，研究了N-甲基-2-吡咯烷酮 (NMP) 和环丁砜从模型燃料（例如正辛烷和正十六烷）中去除噻吩的能力。在 308.15 K 和 0.1 MPa 下测量了四种三元体系（即正辛烷/正十六烷 + 噻吩 + NMP/环丁砜）的三元液-液平衡 (LLE) 数据。NRTL模型用于关联实验数据。使用最大似然法来最小化目标函数。回归的二元交互作用参数与测量数据一致，平均均方根偏差 (RMSD) 为 0.00024。通过评估所研究混合物的模型预测吉布斯混合能的拓扑，验证了数据回归中的二元相互作用参数。除正十六烷+噻吩+环丁砜体系表现出2型行为外，其他体系普遍表现出1型LLE行为。结果表明，与 NMP 相比，环丁砜对正辛烷和正十六烷对噻吩的选择性有所提高。