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.

Role of Iron Speciation in Oxidation and Deposition at the Hexadecane-Iron Interface.

Interactions between iron surfaces and hydrocarbons are the basis for a wide range of materials synthesis processes and novel applications, including sensing. However, in diesel engines these interactions can lead to deposit formation that reduces performance, lowers efficiency, and increases emissions. Here, we present a global study to understand deposition at iron-hexadecane interfaces. We use a combination of spectroscopy, microscopy, and mass spectrometry to investigate surface reactions, bulk chemistry, and deposition processes. A dynamic equilibrium between the oxidation products, both at the surface and in solution, determines the deposition at the surface. Considering the solution and the surface in parallel, we find that the iron speciation affects the morphology, composition, and quantity of the deposit at the surface, as well as the oxidation of hexadecane. Fe(II) and Fe(III) both promote the decomposition of peroxides-intermediates in the oxidation of hexadecane-but through noncatalytic and catalytic mechanisms, respectively. In contrast, Fe(0) is proposed to initiate hexadecane autoxidation during its oxidation to Fe(III). We find that in all cases, the surfaces exclusively contain Fe(III) following heat treatment with hexadecane. Upon subsequent exposure at room temperature, Fe(III) species are found to promote oxidation; this finding is particularly concerning for hybrid vehicles where longer time periods are expected between engine operation. Our work provides a foundation for the development of strategies that disrupt the role of iron in the degradation of hexadecane to ultimately reduce oxidation and deposition in diesel engines.