Molecular Characterization of Volatiles and Petrochemical Base Oils by Photo-Ionization GC×GC-TOF-MS

The characterization of organic mixtures by comprehensive two-dimensional gas chromatography (GC×GC) coupled to electron impact (EI) ionization time-of-flight mass spectrometry (TOF-MS) allows the detection of thousands of compounds. However, owing to the exhaustive fragmentation following EI ionization, despite the use of mass spectral libraries, a majority of the compounds remains unidentified because of the lack of parent ion preservation. Thus, soft-ionization energies leading to organic compounds being ionized with limited or no fragmentation, retaining the molecular ion, has been of interest for many years. In this study, photoionization (PI) was evaluated as the ion source for GC×GC-TOF-MS measurements. First, capabilities and limitations of PI were tested using an authentic mixture of compounds of several chemical classes. Ionization energy exhibited by PI, equivalent to 10.8 eV, resulted in significant retention of molecular ion information; [M]^+• for alkanes, ketones, FAMEs, aromatics, [M–H]^+• for chloroalkanes, and [M–H₂O]^+• for alcohols. Second, considering the potential of PI for hydrocarbons, base oils, complex mixtures of saturated and unsaturated hydrocarbons blended for finished lubricant formulations, were extensively evaluated. Several chemical classes of hydrocarbons were positively identified including a large number of isomeric compounds, both aliphatics and cyclics. Interestingly, branched-alkanes were ionized with lower excess internal energy, not only retaining the molecular ions but also exhibiting unique fragmentation patterns. The results presented herein offer a unique perspective into the detailed molecular characterization of base oils. Such unprecedented identification power of PI coupled with GC×GC-TOF-MS is the first report covering volatiles to low-volatile organic mixtures

Illustration of the method used to measure regions of interest on an MR image.

<p>With use of computer software (developed in-house by the authors), two independent observers freely and easily selected a region of interest by clicking a mesh unit on the right hepatic lobe of an image while avoiding the large vessels, focal hepatic lesions, or artifacts. Seven regions of interest were chosen for liver parenchyma (1–5, total liver ROI area sampled, 500 mm²) and paraspinous muscles (6 and 7, total muscle ROI area sampled, 200 mm²) in the same slice section of each sequence.</p

Scatter plots of LMR and hepatic iron concentration (µmol/g dry liver) on T2-GRE (A), T2-EPI (B), DW-EPI-500 (C), and DW-EPI-1000 (D).

<p>Correlation between LMR and hepatic iron concentration for linear regression with spline models are shown as solid lines on each sequence. The linear regression model [y = 131.0−139.7×LMR+106.5×(LMR−0.73)₊+27.4×(LMR−1.24)₊] on T2-EPI was optimal.</p

Simple hepatic cyst in a 64-year-old woman.

<p>a) Abdominal CT scan shows a well-defined water attenuation lesion in the right hepatic lobe. (b) 3D-image showed a cyst capacity of 1800 ml. Note the Glisson’s pedicle in the base. (c) Laparoscopic aspiration and ethanol sclerosis using sand balloon catheter. (d) Wide unroofing in the right hepatic lobe.</p

Infectious liver cyst in a 71-year-old woman.

<p>(a) Abdominal CT scan showed enhanced cystic wall. (b) Laparotomy view. (c) Intraoperative photograph of post-central hepatectomy. (d) Surgical sample: note the presence of an abscess separated by a septum from the tumor area.</p