GC-FTICR mass spectrometry with dopant assisted atmospheric pressure photoionization: application to the characterization of plastic pyrolysis oil.

Pyrolysis is a promising way to convert plastic waste into valuable resources. However, for downstream upgrading processes, many undesirable species, such as conjugated diolefins or heteroatom-containing compounds, can be generated during this pyrolysis. In-depth chemical characterization is therefore required to improve conversion and valorization. Because of the high molecular diversity found in these samples, advanced analytical instrumentation is needed to provide accurate and complete characterization. Generally, direct infusion Fourier transform mass spectrometry is used to gather information at the molecular level, but it has the disadvantage of limited structural insights. To overcome this drawback, gas chromatography has been coupled to Fourier transform ion cyclotron resonance mass spectrometry. By taking advantage of soft atmospheric pressure photoionization, which preserves molecular information, and the use of different dopants (pyrrole, toluene, and benzene), selective ionization of different chemical families was achieved. Differences in the ionization energy of the dopants will only allow the ionization of the molecules of the pyrolysis oil which have lower ionization energy, or which are accessible via specific chemical ionization pathways. With a selective focus on hydrocarbon species and especially hydrocarbon species having a double bond equivalent (DBE) value of 2, pyrrole is prone to better ionize low-mass molecules with lower retention times compared to the dopant benzene, which allowed better ionization of high-mass molecules with higher retention times. The toluene dopant presented the advantage of ionizing both low and high mass molecules.

Contribution of LDI and MALDI for the Characterization of a Lignocellulosic-Based Pyrolysis Bio-Oil.

In recent years, various alternatives to fossil fuels have been developed. One of them involves the production of bio-oils from lignocellulosic-based biomass through pyrolysis. However, bio-oils present numerous heteroatoms and, in particular, oxygen atoms that need to be removed by an upgrading process. To optimize these processes, it is necessary to have good knowledge of the composition of the bio-oils at the molecular level. This work aims to establish the usefulness of laser desorption ionization (LDI) and matrix-assisted laser desorption/ionization (MALDI) techniques on lignocellulosic biomass-based bio-oils. Using a Fourier transform ion cyclotron mass spectrometer (FTICR MS), we showed that MALDI gives more information than LDI. The selectivity of a series of MALDI matrices was investigated, showing that some matrices are selective toward compound families and others ionize a wider range of compounds. In this study, nine proton-transfer matrices and three electron-transfer matrices were used and compared to results obtained in LDI. Dithranol, acetosyringone, and graphene oxide were the three promising matrices selected from all matrices, giving an overall characterization of oxygenated classes in a bio-oil. They allowed the ionization of many more species covering a wide range of polarity, aromaticity, and mass with a homogeneous relative intensity for all molecular classes such as lignin-derivative species, sugars, and lipid-derivative species.

PyC2MC: An Open-Source Software Solution for Visualization and Treatment of High-Resolution Mass Spectrometry Data.

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).

Prediction of Structures of Compounds Encountered in Complex Organic Matter with Highly Flexible Alkyl Chains Using Ion Mobility-Mass Spectrometry.

The chemical structure of an organic molecule has a direct influence on its three-dimensional conformation. One way to obtain information on this conformation is to use ion mobility spectrometry. This technique allows the separation of different isomers according to their collision cross section (CCS) with an inert gas. Smaller or more compact molecules will have lower collision cross section values than larger molecules. The CCS is an intrinsic ion parameter for a specific gas and is thus predictable. Today, calculations of rigid molecules are commonly performed to obtain additional structural information on an ion. However, calculations are more complex with very flexible molecules. In particular, molecules presenting long alkyl chains can yield a high number of conformers. Each conformer is then associated with a CCS value that is specific to it. We report, here, a methodology to predict CCS of flexible molecules. The used approach is based on automatic conformers research followed by geometry optimization and CCS calculations. Determination of theoretical and experimental CCS values for a rigid polycyclic aromatic hydrocarbons (PAHs) standard was used to calibrate the Mobcal software. Then, 13 standard molecules ranging from 4 to 19 carbon alkyl chains, including three long alkyl chain isomers of C22H38, were analyzed on a TWIMS-ToF and calculated using our methodology. CCS deviations between experimental and theoretical values were found to be less than 1.5% over the whole studied CCS range. This method was finally applied for structural analysis of petroleum compounds refractory to the hydro-denitrogenation process.

Visualization and identification of single meteoritic organic molecules by atomic force microscopy.

Using high-resolution atomic force microscopy (AFM) with CO-functionalized tips, we atomically resolved individual molecules from Murchison meteorite samples. We analyzed powdered Murchison meteorite material directly, as well as processed extracts that we prepared to facilitate characterization by AFM. From the untreated Murchison sample, we resolved very few molecules, as the sample contained mostly small molecules that could not be identified by AFM. By contrast, using a procedure based on several trituration and extraction steps with organic solvents, we isolated a fraction enriched in larger organic compounds. The treatment increased the fraction of molecules that could be resolved by AFM, allowing us to identify organic constituents and molecular moieties, such as polycyclic aromatic hydrocarbons and aliphatic chains. The AFM measurements are complemented by high-resolution mass spectrometry analysis of Murchison fractions. We provide a proof of principle that AFM can be used to image and identify individual organic molecules from meteorites and propose a method for extracting and preparing meteorite samples for their investigation by AFM. We discuss the challenges and prospects of this approach to study extraterrestrial samples based on single-molecule identification.

Structural analysis of petroporphyrins from asphaltene by trapped ion mobility coupled with Fourier transform ion cyclotron resonance mass spectrometry.

Molecular characterization of compounds present in highly complex mixtures such as petroleum is proving to be one of the main analytical challenges. Heavy fractions, such as asphaltenes, exhibit immense molecular and isomeric complexity. Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) with its unequalled resolving power, mass accuracy and dynamic range can address the isobaric complexity. Nevertheless, isomers remain largely inaccessible. Therefore, another dimension of separation is required. Recently, ion mobility mass spectrometry has revealed great potential for isomer description. In this study, the combination of trapped ion mobility and Fourier transform ion cyclotron resonance mass spectrometry (TIMS-FTICR) is used to obtain information on the structural features and isomeric diversity of vanadium petroporphyrins present in heavy petroleum fractions. The ion mobility spectra provided information on the isomeric diversity of the different classes of porphyrins. The determination of the collision cross section (CCS) from the peak apex allows us to hypothesize about the structural aspects of the petroleum molecules. In addition, the ion mobility signal full width at half maximum (FWHM) was used as a measure for isomeric diversity. Finally, theoretical CCS determinations were conducted first on core structures and then on alkylated petroporphyrins taking advantage of the linear correlation between the CCS and the alkylation level. This allowed the proposal of putative structures in agreement with the experimental results. The authors believe that the presented workflow will be useful for the structural prediction of real unknowns in highly complex mixtures.