온도 변화에 따른 스펙트럼 변별력 증대를 통한 라만 분광분석 정확도 향상

Abstract

A strategy to improve the spectral selectivity of Raman feature among complex hydrocarbon mixture samples, lube base oils (LBOs) in this study, has been demonstrated. It is based on the exploration of sample temperature that provides enhanced spectral discriminability among individual components and eventually improves accuracy of measurement. In Chapter I, the proposed strategy was evaluated under the sample temperature range from cryogenic to ambient condition. Raman spectra of LBO samples collected around -160 °C provided the most accurate determination of Kinematic Viscosity at 40 °C (KV@40). The contraction of hydrocarbon backbone occurred at a highly condensed (frozen) condition as expected. Different types of backbone contraction from individual molecules provided the improved spectral discriminability as well as accuracy for KV@40 determination. In Chapter II, the same strategy was also examined when the sample temperatures were changed above room temperature. Again, the distinct temperature-induced spectral variation among the samples occurred at 50 °C, thereby resulting in the improved accuracy for determination of KV@40. Characteristic C-C-C vibrations of LBO components at this temperature were mainly responsible for the enhanced spectral selectivity. Further, the strategy was successfully applied for the identification of soybean oil-adulterated olive oils by combing with linear discriminant analysis (LDA). In conclusion, the probing an optimal temperature maximizing the spectral discrimination among the mixture components is effective and simple to improve accuracy of quantitative analysis without extensive efforts. In addition, two-dimensional (2D) correlation analysis helps to provide an additional supportive rationale for the improved accuracy.