摘要
This paper introduces the terahertz time- domain spectroscopy （THz-TDS） used for the quantitative detection of n-heptane volume ratios in 41 n-heptane and n-octane mixtures with the concentration range of 0-100% at the intervals of 2.5%. Among 41 samples, 33 were used for calibration and the remaining 8 tbr validation. Models of chemometrics methods, including partial least squares （PLS） and back propagation-artificial neural network （BP-ANN）, were built between the THz- TDS and the n-heptane percentage. To evaluate the quality of the built models, we calculated the correlation coefficient （R） and root-mean-square errors （RMSE） of calibration and validation models. R and RMSE of two methods were close to 1 and 0 within acceptable levels, respectively, demonstrating that the combination of THz- TDS and chemometrics methods is a potential and promising tool for further quantitative detection of n- alkanes.
This paper introduces the terahertz time- domain spectroscopy （THz-TDS） used for the quantitative detection of n-heptane volume ratios in 41 n-heptane and n-octane mixtures with the concentration range of 0-100% at the intervals of 2.5%. Among 41 samples, 33 were used for calibration and the remaining 8 tbr validation. Models of chemometrics methods, including partial least squares （PLS） and back propagation-artificial neural network （BP-ANN）, were built between the THz- TDS and the n-heptane percentage. To evaluate the quality of the built models, we calculated the correlation coefficient （R） and root-mean-square errors （RMSE） of calibration and validation models. R and RMSE of two methods were close to 1 and 0 within acceptable levels, respectively, demonstrating that the combination of THz- TDS and chemometrics methods is a potential and promising tool for further quantitative detection of n- alkanes.
