Using Fourier transform infrared (FT-IR) spectroscopy we investigated the water content of SAE 15W-40 diesel engine lubricating oil at various levels of contamination to establish instrument calibration standards for measuring water contamination in used or in-service engine oil by the standards of ASTM International. Since some known additives in consumer grade engine oil possess slightly hydrophilic properties, this experiment avoided changing the sample matrix with supplemental additives, such as adding surfactants, to achieve homogeneity of the original sample. The impact of sampling time after contamination on the spectral absorption signature was examined in an attempt to improve the accuracy of water contamination quantification and determine if water-soluble potassium bromide (KBr) windows were suitable for analyzing water in oil emulsions. Analysis of variance (ANOVA) modeling and limit of detection calculations were used to predict the ability to discriminate contamination levels over time. Our results revealed that the amount of water concentration in engine oil could be misinterpreted depending on the timing of the FT-IR measurement of the calibration standard after initial water contamination. Also, KBr windows are not sufficiently etched due to the limited window interaction with water molecules within micelles of emulsions to alter FT-IR spectral signatures.
Fourier Transform-Infrared (FT-IR) spectroscopy was used to analyze gasoline engine oil (SAE 5W20) samples that were exposed to seven different oxidation times (0 h, 24 h, 48 h, 72 h, 96 h, 120 h, and 144 h) to determine the best wavenumbers and wavenumber ranges for the discrimination of the oxidation times. The thermal oxidation process generated oil samples with varying total base number (TBN) levels. Each wavenumber (400–3900 cm−1) and wavenumber ranges identified from the literature and this study were statistically analyzed to determine which wavenumbers and wavenumber ranges could discriminate among all oxidation times. Linear regression was used with the best wavenumbers and wavenumber ranges to predict oxidation time.
Successful treatment of cancers requires detecting early signs of the disease. One promising way to approach this is to develop minimally invasive tests for the sensitive and specific detection of biomarkers in blood. Irrespective of the detection approach one uses, this remains a challenging task because biomarkers are typically present in low concentrations and there are signals that interfere strongly with prevailing compounds of human fluids. In this paper, we show that elemental encoded particle assay coupled with femtosecond laser-induced breakdown spectroscopy for simultaneous multi-elemental analysis can significantly improve biomarker detectability. An estimated near single molecule per particle efficiency of this method leads to sensitive detection of ovarian cancer biomarker CA125 in human blood plasma. This work opens new ways for earlier detection of cancers and for multiplex assay developments in various analytical applications from proteomics, genomics, and neurology fields.
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