Methanol and ethanol gasoline are two emerging clean energy sources with different characteristics. To achieve the qualitative identification and quantitative analysis of the alcohols present in methanol and ethanol gasoline, effective chemical information (ECI) models based on the characteristic spectral bands of the near-infrared (NIR) spectra of the methanol and ethanol molecules were developed using the partial least squares discriminant analysis (PLS-DA) and partial least squares (PLS) algorithms. The ECI model was further compared with models built from the full wavenumber (Full) spectra, variable importance in projection (VIP) spectra, and Monte Carlo uninformative variable elimination (MC-UVE) spectra to determine the predictive performance of ECI model. Among the various qualitative identification models, it was found that the ECI-PLS-DA model, which is built using the differences in molecular chemical information between methanol and ethanol, exhibited sensitivity, specificity and accuracy values of 100%. The ECI-PLS-DA model accurately identified methanol gasoline and ethanol gasoline with different contents. In the quantitative analysis model for methanol gasoline, the methanol gasoline and ethanol gasoline ECI-PLS models exhibited the smallest root mean squared error of predictions (RMSEP) of 0.18 and 0.21% (v/v), respectively, compared to the other models. Meanwhile, the F-test and T-test results revealed that the NIR method employing the ECI-PLS model showed no significant difference compared to the standard method. Compared with other spectral models examined herein, the ECI model demonstrated the highest recognition success and determination accuracy. This study therefore established a highly accurate and rapid determination model for the qualitative identification and quantitative analysis based on chemical structures. It is expected that this model could be extended to the NIR analysis of other physicochemical properties of fuel.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.talanta.2024.125961 | DOI Listing |
J Fluoresc
January 2025
Department of Physics, Jnana Bharathi Campus, Bangalore University, Bengaluru, 560056, India.
This investigation delves into the extraction of polyphenols from the flowers of Tabebuia rosea using a basic maceration approach with acetone, ethanol, and methanol as solvents. The spectroscopic analysis of the dye obtained confirms the existence of functional groups in the polyphenol extract. The study also explores optoelectronic, fluorescence, and photometric characteristics associated with polyphenols.
View Article and Find Full Text PDFJ Pharm Biomed Anal
January 2025
Sabanci University Nanotechnology Research and Application Center (SUNUM), Istanbul 34956, Turkey.
This study aimed to determine the chromatographic retention and dissociation/protonation constant (pK) values of lapatinib and tamoxifen, key drugs used in metastatic breast cancer treatment, at 37°C using both conventional and green high-performance liquid chromatography (HPLC) methods. Qualitative analysis was conducted on an XTerra C18 column (250 ×4.6 mm I.
View Article and Find Full Text PDFBMC Chem
January 2025
Department of Pharmaceutical Analytical Chemistry, Faculty of Pharmacy, University of Alexandria, Elmessalah, Alexandria, 21521, Egypt.
A simple, rapid, and reproducible high-performance liquid chromatography (HPLC) method has been developed and validated for the determination of β-sitosterol in the pharmaceutical dosage form of moist exposed burn ointment (MEBO). This method involved an effective sample procedure for extraction of β-sitosterol from MEBO using an alkali saponification agent composed of 0.8 N ethanolic NaOH and diethyl ether.
View Article and Find Full Text PDFEnviron Mol Mutagen
January 2025
Department of Pharmacology and Toxicology, Zydus Research Centre, Zydus Lifesciences Limited, Ahmedabad, Gujarat, India.
The bacterial reverse mutation test is essential for identifying the mutagenic potential of chemicals. The solubility of the test substance is vital for achieving the recommended assay concentration. Preferred solvents like dimethyl sulfoxide and water are chosen for their compatibility and historical data.
View Article and Find Full Text PDFHeliyon
January 2025
Department of Chemical Sciences, University of Johannesburg, PO Box 17011, Doornfontein, 2028, Johannesburg, South Africa.
Semiconductor metal oxide gas sensors are widely used to detect ethanol vapours, commonly used in industrial productions, road safety detection, and solvent production; however, they operate at extremely high temperatures. In this work, we present manganese dioxide nanorods (MnO NRs) prepared via hydrothermal synthetic route, carbon soot (CNPs) prepared via pyrolysis of lighthouse candle, and poly-4-vinylpyridine (P4VP) composite for the detection of ethanol vapour at room temperature. MnO, CNPs, P4VP, and MnO NRs-CNPs-P4VP composite were characterised using scanning electron microscopy, transmission electron microscopy, powder X-ray diffraction, Fourier transform infrared spectroscopy, and Raman spectroscopy.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!