Terahertz quantitatively distinguishing gasoline mixtures using multiparameter-combined analysis

Area of Science:

• Analytical Chemistry
• Spectroscopy
• Chemical Engineering

Background:

• Terahertz-absorption-coefficient spectra with dualistic linear regression fitting are used for refined oil mixture quantification.
• This method shows significant error (25%) when quantifying 90# and 97# gasoline mixtures due to component similarity.

Purpose of the Study:

• To develop a direct, simple, and accurate method for determining 97# gasoline content in gasoline mixtures.
• To improve upon existing terahertz spectroscopy methods for complex gasoline mixtures.

Main Methods:

• Utilizing terahertz time-domain pulses coupled with multiparameter-combined analysis.
• Analyzing time delay and amplitude of the first transmission dip and peak as key parameters.
• Developing four calibration models using least square fitting and combining them with cosine-optimal weighting.

Main Results:

• The new method determines 97# gasoline content with a low absolute error of 6%.
• This represents a substantial improvement in accuracy and precision over previous methods.
• The multiparameter analysis effectively distinguishes between similar gasoline components.

Conclusions:

• Terahertz time-domain pulse spectroscopy combined with multiparameter analysis offers a superior method for quantifying gasoline mixtures.
• The cosine-optimal weighting strategy enhances the reliability of the calibration models.
• This technique provides a precise and accurate solution for analyzing complex refined oil mixtures.