研究目的
To identify and quantify methanol in methanol gasoline using three-dimensional fluorescence spectroscopy combined with second-order chemometric methods.
研究成果
The SWATLD model combined with EEMF spectroscopy provides accurate and reliable detection of methanol in adulterated gasoline, with high recovery rates and low RMSEP values. This method is suitable for regulatory applications in the gasoline market to prevent fraud.
研究不足
The study is limited to methanol adulteration in gasoline and may not generalize to other adulterants. The methods require specific equipment and software, which could be costly. The number of factors in chemometric models can affect results, and the approach might not handle very complex mixtures with many fluorophores effectively.
1：Experimental Design and Method Selection:
The study used excitation-emission matrix fluorescence (EEMF) spectroscopy combined with chemometric methods (PARAFAC and SWATLD) to analyze adulterated gasoline samples. The rationale was to leverage the sensitivity and rapidity of fluorescence spectroscopy for detecting methanol adulteration.
2：Sample Selection and Data Sources:
Artificial samples were prepared by blending 95# gasoline and methanol in varying proportions within linear concentration ranges (0-42 μg/mL for gasoline, 0-32 μg/mL for methanol). Six artificial samples served as the validation set, and four real samples with known methanol content (5%, 10%, 15%, 20%) were purchased from a gas station. All samples were diluted with carbon tetrachloride to a concentration of 0.1 g/mL.
3：1 g/mL.
List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials: Equipment included an FS920 fluorescence spectrometer (Edinburgh Instruments) with a 450W Xe arc lamp, excitation and emission monochromators, and a photomultiplier tube (PMT). Materials were 95# gasoline, methanol, and carbon tetrachloride (purity >99%, from Shanghai Aladdin Biochemical Technology Co., Ltd.). Software used was F900 for data acquisition and Matlab R2015b for data processing.
4：Experimental Procedures and Operational Workflow:
Samples were illuminated with excitation wavelengths from 250 nm to 450 nm (10-nm band pass) and emission wavelengths from 300 nm to 500 nm (10-nm band pass). Slit width was set to 2 mm. EEM data were acquired, corrected for scattering by subtracting blank carbon tetrachloride solutions, and processed using PARAFAC and SWATLD models in Matlab. Core consistency diagnostic (CORCONDIA) was used to determine the number of factors.
5：Data Analysis Methods:
Data were analyzed using PARAFAC and SWATLD algorithms to decompose the three-dimensional EEM matrices. Recovery rate and root mean square error of prediction (RMSEP) were calculated to evaluate accuracy.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容
