Jiao Long, Liu Huanhuan, Qu Le, Xue Zhiwei, Wang Yuan, Wang Yanzhao, Lei Bin, Zang Yunlei, Xu Rui, Zhang Zhen, Li Hua, Alyemeni Omar Abdulaziz Ahmed
College of Chemistry and Chemical Engineering, Xi'an Shiyou University, Xi'an 710065, P. R. China.
State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Chendu University of Technology, Chendu 610059, P. R. China.
ACS Omega. 2020 Feb 20;5(8):3878-3888. doi: 10.1021/acsomega.9b03139. eCollection 2020 Mar 3.
The quantitative structure-property relationship (QSPR) models for predicting the octane number (ON) of toluene primary reference fuel (TPRF; blends of -heptane, isooctane, and toluene) was investigated. The electrotopological state (E-state) index of TPRF components was computed and weight-summed to generate the quantitative descriptor of TPRF samples. The partial least squares (PLS) technique was used to build up the regression model between the ON and weight-summed E-state index of the investigated samples. The QSPR models for the research octane number (RON) and motor octane number (MON) of TPRF were built. The prediction performance of the obtained PLS models was assessed by the external test set validation and leave-one-out cross-validation. The validation results demonstrate that the proposed PLS models are feasible for predicting the ON, both RON and MON, of TPRF. In addition, several other QSPR models for the ON of TPRF were developed by employing the stepwise regression and Scheffé polynomials methods, and the prediction performance of these models were compared with that of the PLS models. The comparison result shows that the proposed PLS models are slightly better than multiple linear regression models and Scheffé models. It is demonstrated that the combination of the E-state index and PLS is an easy-to-use and promising method for studying and forecasting the ON of TPRF.
研究了用于预测甲苯一级参考燃料(TPRF,由正庚烷、异辛烷和甲苯混合而成)辛烷值(ON)的定量结构-性质关系(QSPR)模型。计算了TPRF组分的电拓扑状态(E-state)指数并进行加权求和,以生成TPRF样品的定量描述符。使用偏最小二乘法(PLS)技术建立所研究样品的ON与加权求和E-state指数之间的回归模型。构建了TPRF研究法辛烷值(RON)和马达法辛烷值(MON) 的QSPR模型。通过外部测试集验证和留一法交叉验证对所得PLS模型的预测性能进行评估。验证结果表明,所提出的PLS模型对于预测TPRF的ON、RON和MON是可行的。此外,采用逐步回归和谢费多项式方法开发了其他几个用于TPRF的ON的QSPR模型,并将这些模型的预测性能与PLS模型进行了比较。比较结果表明,所提出的PLS模型略优于多元线性回归模型和谢费模型。结果表明,E-state指数与PLS的结合是一种用于研究和预测TPRF的ON的易于使用且有前景的方法。