Acta Chim. Sinica ›› 2016, Vol. 74 ›› Issue (2): 172-178.DOI: 10.6023/A15100664 Previous Articles     Next Articles



祁丽华, 蔡文生, 邵学广   

  1. 南开大学化学学院分析科学研究中心 天津市生物传感与分子识别重点实验室 药物化学生物学国家重点实验室天津化学化工协同创新中心 天津 300071
  • 投稿日期:2015-10-17 发布日期:2015-12-23
  • 通讯作者: 邵学广
  • 基金资助:


Effect of Temperature on Near-infrared Spectra of n-Alkanes

Qi Lihua, Cai Wensheng, Shao Xueguang   

  1. Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300071, China
  • Received:2015-10-17 Published:2015-12-23
  • Supported by:

    Project supported by the National Natural Science Foundation of China (No. 21475068) and MOE Innovation Team (IRT13022).

Effect of temperature on near-infrared (NIR) spectra has been studied and applied to structural and quantitative analyses. To investigate the effect of temperature on NIR spectra of alkyl organic system, n-alkanes were studied in this work. NIR spectra of pure n-alkanes (hexane to decane), binary (hexane and octane) and ternary (octane, nonane and decane) mixtures were measured. In the experiments, temperature was controlled to change from 60 to 20℃ with a step of ca. 5℃. Comparing the spectra at different temperatures, only a little difference in peak intensity of some bands can be found. Therefore, alternating trilinear decomposition (ATLD) algorithm was adopted to analyze the three-order data matrix. The results show that two spectral loadings are obtained because the influence of temperature on the spectra of terminal ethyl (C2H5) groups differs from that of mid-chain methylene (CH2) groups. Furthermore, the temperature scores of CH2 and C2H5 groups decrease linearly with temperature, implying that the temperature effect can be quantitatively described by a quantitative spectra-temperature relationship (QSTR) model. The QSTR model provides an efficient way to predict the temperature of n-alkane solutions. Good linearity also exists between sample scores and carbon number or the relative content of CH2 and C2H5 groups in the molecules of the n-alkanes. Linear models between the two scores and the relative content of CH2 and C2H5 groups are obtained, respectively, using the least square fitting of the score and the relative contents. The model can be used for prediction of the relative content of CH2 and C2H5 groups in mixtures, which can further be used to estimate the composition of the mixtures. Furthermore, the relationship between the scores and the carbon atom numbers is modeled using multivariate linear regression (MLR). The composition of n-alkane mixtures can also be estimated through the predicted carbon number using the MLR model. These models are validated by binary and ternary mixtures of the n-alkanes. It was indicated that the relative contents of CH2 and C2H5 groups or the carbon atom number can be predicted using the models. Therefore, a new way for quantitative estimation of the composition in n-alkane mixtures was developed using the temperature effect of the near-infrared spectra.

Key words: near-infrared spectra, temperature effect, n-alkane, alternating trilinear decomposition, quantitative spectratemperature relationship