Chemometric approaches to resolving base oil mixtures.

RATIONALE: In the lubrication industry, commercial base oils are commonly made up of blends of base oil stocks from different sources in different ratios to reduce production costs and modulate rheological properties. This practice introduces complexity in lubricant design because as the chemistry of the base oil becomes more complicated, it can become harder to formulate the base oil - particularly when the ratio of the original base oil stocks is unknown. METHODS: In this study, field ionisation mass spectrometry is used to collect chemical information on a range of base oil mixtures. The resultant data are processed within the Python workspace where molecular formulae are assigned to the components and statistical analyses are performed. A variety of regression techniques including regularised linear models and automated machine learning are evaluated on the data. RESULTS: The use of an automated machine learning pipeline yields insight into effective modelling strategies that could be applied to the data obtained. The best results were obtained using polynomial feature generation combined with ridge cross-validation regression. Overall, with this methodology it is possible to resolve the ratio of group 2 and group 3 base oil within a blended mixture to an accuracy of ±5%. CONCLUSIONS: The strategies outlined in this study show how modern data science and chemometrics can be applied successfully to resolve the ratio of a complex mixture.

Direct Analysis of Oil Additives by High-Field Asymmetric Waveform Ion Mobility Spectrometry-Mass Spectrometry Combined with Electrospray Ionization and Desorption Electrospray Ionization.

The analysis of corrosion inhibitors in the presence and absence of an oil matrix is reported using electrospray ionization (ESI) and desorption electrospray ionization (DESI), hyphenated with miniaturized high-field asymmetric waveform ion mobility spectrometry (FAIMS) and mass spectrometry (MS). The target analytes were successfully ionized in solution by ESI and directly from steel surfaces using DESI ambient ionization at levels ≥0.0004% w/w (4 ppm) in oil. Differences in the mass spectral profiles observed for the additive/oil mixture are attributed to differences between the ESI and DESI ionization processes. The use of FAIMS improved selectivity for ESI generated analyte ions through reduction in the chemical noise resulting from the oil matrix. DESI enabled the direct, rapid, native state interrogation of oil samples on steel surfaces without sample pretreatment, and the hyphenation of DESI with the miniaturized FAIMS enhanced the relative analyte responses of the surface-active corrosion inhibitors.

The quantitative surface analysis of an antioxidant additive in a lubricant oil matrix by desorption electrospray ionization mass spectrometry.

RATIONALE: Chemical additives are incorporated into commercial lubricant oils to modify the physical and chemical properties of the lubricant. The quantitative analysis of additives in oil-based lubricants deposited on a surface without extraction of the sample from the surface presents a challenge. The potential of desorption electrospray ionization mass spectrometry (DESI-MS) for the quantitative surface analysis of an oil additive in a complex oil lubricant matrix without sample extraction has been evaluated. METHODS: The quantitative surface analysis of the antioxidant additive octyl (4-hydroxy-3,5-di-tert-butylphenyl)propionate in an oil lubricant matrix was carried out by DESI-MS in the presence of 2-(pentyloxy)ethyl 3-(3,5-di-tert-butyl-4-hydroxyphenyl)propionate as an internal standard. A quadrupole/time-of-flight mass spectrometer fitted with an in-house modified ion source enabling non-proximal DESI-MS was used for the analyses. RESULTS: An eight-point calibration curve ranging from 1 to 80 µg/spot of octyl (4-hydroxy-3,5-di-tert-butylphenyl)propionate in an oil lubricant matrix and in the presence of the internal standard was used to determine the quantitative response of the DESI-MS method. The sensitivity and repeatability of the technique were assessed by conducting replicate analyses at each concentration. The limit of detection was determined to be 11 ng/mm(2) additive on spot with relative standard deviations in the range 3-14%. CONCLUSIONS: The application of DESI-MS to the direct, quantitative surface analysis of a commercial lubricant additive in a native oil lubricant matrix is demonstrated.

Cationic cyclocholamides; toroidal facial amphiphiles with potential for anion transport.

Cholic acid has been transformed into cyclotrimeric and cyclotetrameric toroidal amphiphiles with inward-directed ammonium substituents; the cyclotrimer effects the transport of chloride anions across vesicle bilayer membranes.