Elucidation of the macromolecular composition of fossil biopolymers using Py-GC×GC-TOFMS. (January 2021)

• Record Type: Journal Article
• Authors: Umamaheswaran, Raman; Dutta, Suryendu; Kumar, Sumit
• Is Part Of: Organic geochemistry. Volume 151(2021)
• Publication Date: 2021-01
• Subjects: Pyrolysis -- GC×GC-TOFMS -- Biopolymers -- G. prisca -- Tasmanites -- Resin; Organic geochemistry -- Periodicals; Biogeochemistry -- Periodicals; Géochimie organique -- Périodiques; 553.205
• DOI: 10.1016/j.orggeochem.2020.104139
• Languages: English
• ISSNs: 0146-6380

Abstract

Highlights: Efficacy of Py-GC×GC-TOFMS is demonstrated. Py-GC×GC-TOFMS detects compounds at enhanced resolution levels compared to Py-GC-MS. Complex mixtures of compounds clearly distinguished with less noisy mass spectra. UCMs formed on conventional Py-GC-MS able to be resolved by Py-GC×GC-TOFMS. Abstract: In recent times, the limits of traditional Py-GC-MS techniques in evaluating the macromolecular compositions of biopolymers have proved to be more apparent – particularly in those samples containing complex, structurally similar organic molecules, often producing large areas of unresolved complex mixtures (UCM). In this paper, we compare the use of pyrolysis comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (Py-GC×GC-TOFMS) with conventional Py-GC-MS analyses and attempt to showcase the full potential of this technique by analyzing different fossil organic materials – algal-derived Tasmanites, Ordovician microfossil Gloeocapsomorpha prisca and terrestrial plant-derived resin. With all three fossil samples, Py-GC×GC-TOFMS was able to offer a higher degree of compound separation and detection of more complex compounds. Sulphur and oxygen-bearing polar compounds were clearly separated into different homologous series. Thus, this method bypassed the problem created by the UCMs in traditional Py-GC-MS in the case of G. prisca and Tasmanites, while resolving several biomarkers in the case of the resin which aided chemotaxonomic classification. We find that Py-GC×GC-TOFMS provides a greater variety of compounds at enhanced resolution levels than conventional Py-GC-MS methods and is more suited to analyzing samples with larger variety of chemical structures and functional groups with greater confidence, particularly in unknown samples. It can thus provide the analytical capability to better characterize the chemistry of kerogens, which will help in assessments of hydrocarbon source properties and may provide new avenues to interpretation in paleobiological studies.