Proton NMR Analysis of Octane Number for Motor Gasoline: Part III
Masatoshi Ichikawa, N. Nonaka, H. Amano, I. Takada, S. Ishimori, H. Andoh, K. Kumamoto
Abstract
Masatoshi Ichikawa, N. Nonaka, H. Amano, I. Takada, S. Ishimori, H. Andoh, K. Kumamoto
Abstract
A method to evaluate the octane number of automobile gasoline by proton magnetic resonance (PMR) spectrometry has been studied. Twelve samples of marketed winter gasoline, whose octane numbers and compositions were identified according to the ASTM standards, and high-olefin gasoline were used to supplement the insufficient coverage of a previous report with additional data. Then, a linear regression equation regarding the relationship between the octane number and PMR data was prepared from the PMR spectra of the 21 samples used for the previous report, whose octane numbers were known, and the 12 samples used this time. Further, the appropriateness of the regression equation was assessed. This report concerns the results of a study in which the scope of the previous study, lacking sufficient data, has been supplemented with additional data to improve the accuracy of the visual estimation of the octane number using the pattern recognition method. Also, a linear regression equation was obtained and found useful for octane number estimation.
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A method to evaluate the octane number of automobile gasoline by proton magnetic resonance (PMR) spectrometry has been studied. Twelve samples of marketed winter gasoline, whose octane numbers and compositions were identified according to the ASTM standards, and high-olefin gasoline were used to supplement the insufficient coverage of a previous report with additional data. Then, a linear regression equation regarding the relationship between the octane number and PMR data was prepared from the PMR spectra of the 21 samples used for the previous report, whose octane numbers were known, and the 12 samples used this time. Further, the appropriateness of the regression equation was assessed. This report concerns the results of a study in which the scope of the previous study, lacking sufficient data, has been supplemented with additional data to improve the accuracy of the visual estimation of the octane number using the pattern recognition method. Also, a linear regression equation was obtained and found useful for octane number estimation.
Key concepts: Octane, Octane rating, Gasoline, Linear regression, Proton magnetic resonance, Chemistry, Regression analysis, Proton NMR