Insights from Nitrogen Compounds in Gas Oils Highlighted by High-Resolution Fourier Transform Mass Spectrometry

Guillemant, Julie; Albrieux, Florian; Oliveira, Luís Pereira de; Lacoue-Nègre, Marion; Duponchel, Ludovic; Joly, Jean‐François

doi:10.1021/acs.analchem.9b01702

Cited by 18 publications

(31 citation statements)

References 41 publications

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“…The macroscopic properties of these samples are shown in Table 1. The preparation and ionization conditions were optimized with a Design of Experiments (DoE) approach and detailed in a previous work 13 .…”

Section: Methodsmentioning

confidence: 99%

“…There is then a real need for molecular characterization of these different gas oils 2 . The detailed characterization of sulfur compounds in gas oils can be achieved through atmospheric pressure photo-ionization (APPI) coupled to ultra-high resolution mass spectrometry (Fourier Transform Ion Cyclotron Resonance Mass Spectrometry known as FT-ICR MS) analysis [8][9][10][11] while nitrogen compounds are described using the electrospray ionization (ESI) source in two different polarities (negative polarity for neutral nitrogen compounds and positive polarity for basic nitrogen compounds) 12,13 . As FT-ICR MS generates big datasets, multivariate analysis is more and more used to fully explore the resulting datasets [14][15][16] .…”

Section: Introductionmentioning

confidence: 99%

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Evaluating the Benefits of Data Fusion and PARAFAC for the Chemometric Analysis of FT-ICR MS Data Sets from Gas Oil Samples

et al. 2020

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Advanced characterization of the products of gas oils hydrotreatment is of high interest for the refiners and can be achieved by using ultra-high resolution mass spectrometry (FT-ICR MS). However, the analysis of gas oil samples by FT-ICR MS generates complex datasets with numerous variables whose exhaustive analysis requires the use of multivariate methods. Relevant information about nitrogen and sulfur compounds contained in several industrial gas oils are obtained by using three different ionization modes that are electrospray ionization (ESI) used in positive and negative polarities and atmospheric pressure photo-ionization (APPI) used in positive polarity. For datasets generated for a single ionization mode, classical multivariate methods such as Principal Component Analysis (PCA) are commonly used.When the key information is spread into several ionization modes and thus into several datasets, a data fusion approach is highly interesting to simultaneously explore these datasets and can be followed by Parallel Factor analysis (PARAFAC). Nevertheless, many more variables are simultaneously considered when data fusion is performed and the sensitivity of PARAFAC and its ability to extract the most relevant variables compared to classical multivariate methods has not been assessed yet in the framework of FT-ICR MS. In this paper, the comparison of the classical data analysis (PCA) approach and the data fusion combined with the PARAFAC analysis approach is presented. The results have shown that applying PARAFAC on fused datasets is highly sensitive and able to put forward features and variables that individually identified through the classical data analysis with greater ease of implementation and interpretation of results. As an example, dibenzothiophenes and carbazole families (DBE 9) have explained most of the variance between samples and remain the most refractory compounds in hydrotreated samples. A significant difference in alkylation between the different types of gas oils has also been spotted. This paper validates the power and efficiency of this approach to explore complex datasets simultaneously without any loss of significant information.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluating the Benefits of Data Fusion and PARAFAC for the Chemometric Analysis of FT-ICR MS Data Sets from Gas Oil Samples

et al. 2020

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“…70 scans with 4 µ-scans and their corresponding transients were recorded with an initial resolution set to 200,000 at m/z 300 before data processing. The ionization and ion transfer conditions for each ionization mode are described elsewhere [16]. The external mass calibration was performed using a sodium formiate clusters solution (sodium formiate provided from VWR, Fontenay-sous-Bois, France) from about 90 Da to 1000 Da.…”

Section: Ft-icr Ms Analysismentioning

confidence: 99%

“…The full data processing has been described elsewhere [16]. Phase absorption and phase correction were applied on a summed transient (sum of 70 recorded transients).…”

Section: Ft-icr Ms Analysismentioning

confidence: 99%

“…The hydrotreatment (HDT) process aims at removing impurities such as sulfur, nitrogen or metals from gas oils cuts so that they can respect the legal specifications. As these are getting more and more stringent, the hydrotreatment process needs to be more and more efficient and despite their relatively low amount among the gas oils, the nitrogen compounds are of high concern for refiners [13][14][15][16]. Neutral nitrogen compounds are refractory while the basic ones deactivate the catalysts used and compete with sulfur compounds for their removal [17,18].…”

Section: Introductionmentioning

confidence: 99%

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Towards a New Pseudo-quantitative Approach to Evaluate the Ionization Response of Nitrogen Compounds in Complex Matrices

Guillemant

Lacoue-Nègre

Berlioz‐Barbier

et al. 2021

Preprint

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Ultra high-resolution mass spectrometry (FT-ICR MS) coupled to electrospray ionization (ESI) provides unprecedented molecular characterization of complex matrices such as petroleum products. However, ESI faces major ionization competition phenomena that prevent the absolute quantification of the compounds of interest. On the other hand, comprehensive two-dimensional gas chromatography (GC × GC) coupled to specific detectors (HRMS or NCD) is able to quantify the main families identified in these complex matrices. In this paper, this innovative dual approach has been used to evaluate the ionization response of nitrogen compounds in gas oils as a case study. To this extent, a large gas oil dataset has been analyzed by GC × GC/HRMS, GC × GC-NCD and ESI(+/-)-FT-ICR MS. Then, the concentrations obtained from GC × GC-NCD have been compared to those obtained from FT-ICR MS hence proving that strong ionization competitions are taking place and also depending on the origin of the sample. Finally, multilinear regressions (MLR) have been used to quantitatively predict nitrogen families from FT-ICR MS measurements as well as start rationalizing the ionization competition phenomena taking place between them in different types of gas oils.

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Novel four-dimensional approach for the structural characterization of neutral nitrogen compounds in vacuum gas oils using UHPLC-IM-QqToF analysis

Guillemant

Berlioz‐Barbier

Oliveira

et al. 2021

Analytica Chimica Acta

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Insights from Nitrogen Compounds in Gas Oils Highlighted by High-Resolution Fourier Transform Mass Spectrometry

Cited by 18 publications

References 41 publications

Evaluating the Benefits of Data Fusion and PARAFAC for the Chemometric Analysis of FT-ICR MS Data Sets from Gas Oil Samples

Evaluating the Benefits of Data Fusion and PARAFAC for the Chemometric Analysis of FT-ICR MS Data Sets from Gas Oil Samples

Towards a New Pseudo-quantitative Approach to Evaluate the Ionization Response of Nitrogen Compounds in Complex Matrices

Novel four-dimensional approach for the structural characterization of neutral nitrogen compounds in vacuum gas oils using UHPLC-IM-QqToF analysis

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