ABSTRACT
Synthetic complex esters and polyol esters are incorporated as partially bio-based and biodegradable alternatives to petroleum base oils in lubricant formulations, to provide specific properties or performance and to help reducing their carbon footprint in certain cases. A sample can contain over 400 molecules of high chemical similarity including numerous isomers. To resolve such complexity, a separation technique with large peak capacity coupled to high-resolution mass spectrometry (HRMS) is essential. In this study, comprehensive off-line LCxSFC hyphenated with an Orbitrap analyzer was used for the structural elucidation of a synthetic bio-lubricant composed of a polyol reacted with fatty acids of varying length or with repetitive units of polyesters of ricinoleic acid. Retention in the LC first dimension was mostly due to the degree of oligomerization of ricinoleic acid within the polyester and to the chain length of the fatty acid. The SFC second dimension highlighted the esterification degree of the polyalcohol and the number and positions of fatty acids double bonds. The combination of both dimensions permitted the separation of isomers. The coupling of SFC with Orbitrap analyzer allowed an accurate assignment of molecular formulas. Finally, the fragmentation in the ionization source confirmed the attributed structures. By introducing a clear distribution of the chemical structures in the retention space, LCxSFC-HRMS provided a powerful analytical method for the comprehensive molecular characterization of the complex polyester polyols sample.
ABSTRACT
Complex molecular mixtures are encountered in almost all research disciplines, such as biomedical 'omics, petroleomics, and environmental sciences. State-of-the-art characterization of sample materials related to these fields, deploying high-end instrumentation, allows for gathering large quantities of molecular composition data. One established technological platform is ultrahigh-resolution mass spectrometry, e.g., Fourier-transform mass spectrometry (FT-MS). However, the huge amounts of data acquired in FT-MS often result in tedious data treatment and visualization. FT-MS analysis of complex matrices can easily lead to single mass spectra with more than 10,000 attributed unique molecular formulas. Sophisticated software solutions to conduct these treatment and visualization attempts from commercial and noncommercial origins exist. However, existing applications have distinct drawbacks, such as focusing on only one type of graphic representation, being unable to handle large data sets, or not being publicly available. In this respect, we developed a software, within the international complex matrices molecular characterization joint lab (IC2MC), named "python tools for complex matrices molecular characterization" (PyC2MC). This piece of software will be open-source and free to use. PyC2MC is written under python 3.9.7 and relies on well-known libraries such as pandas, NumPy, or SciPy. It is provided with a graphical user interface developed under PyQt5. The two options for execution, (1) a user-friendly route with a prepacked executable file or (2) running the main python script through a Python interpreter, ensure a high applicability but also an open characteristic for further development by the community. Both are available on the GitHub platform (https://github.com/iC2MC/PyC2MC_viewer).
ABSTRACT
Formulated lubricants correspond to high value products used for several applications in automotive, industrial, medicinal, and agro-food sectors. They correspond to complex matrices composed of approximately 80% of base oils (mineral or synthetic) and of about 20% of additives. Additives are generally low molecular weight polymeric molecules with a great diversity of elements. To characterize such complex compositions at the molecular level, ultrahigh resolution mass spectrometers are required. Two formulated lubricants and two additive packages were analyzed by Fourier transform ion cyclotron resonance mass spectrometry in direct infusion. Atmospheric pressure chemical ionization (APCI) and electrospray ionization (ESI) sources were used to have an exhaustive characterization of the samples. The Kendrick mass defects (KMD) plot is a widespread representation to characterize polymeric molecules. Here, the terms apparent mass defect and apparent Kendrick mass defects (aKMD) values were introduced to consider the uncertainty on nominal mass determination. Several additive families including alkyldiphenylamines, trisalkylphenylthiophosphoric acid, zinc dithiophosphates, bisuccinimide dispersants, and their derivatives were observed by APCI(+). ESI(-) also presented a use for the selective ionization of acidic compounds including sulfonates, phenates, and sulfur phenate molecules. The specific aKMD values and polydispersity of many additive families have been reported to create a database of additives. Overall, this study demonstrated the great utility of the aKMD approach and the use of the ESI/APCI combination for a simple and fast characterization of formulated lubricant and additive package samples.
