Molecular-Level Insights into Coker/Straight-Run Gas Oil Hydrodenitrogenation by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

Nguyen, Minh-Hoang; Pirngruber, Gerhard D.; Chainet, Fabien; Albrieux, Florian; Tayakout‐Fayolle, Mélaz; Geantet, Christophe

doi:10.1021/acs.energyfuels.8b04432

Cited by 20 publications

(18 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Then, detailed knowledge of the exact chemical composition of VGO cuts is of premier importance, and we are highly interested in the molecular characterization of the nitrogen and sulfur compounds contained in these complex samples. Hydrotreatment processes rely on sulfide-based catalysts that are unfortunately poisoned by basic nitrogen compounds. − Moreover, some neutral nitrogen compounds are refractory to hydrotreatment and compete with sulfur compounds for the hydrotreatment of the latter. , Some sulfur compounds are also known to be refractory whereas the amount of total sulfur in converted products is lower than 10 ppm as it is strictly regulated. , As a consequence, the efficiency of hydrodenitrogenation (hydrotreatment of nitrogen compounds, often noted HDN) and hydrodesulfurization (hydrotreatment of sulfur compounds, often noted HDS) processes is very dependent on both nitrogen and sulfur compounds compositions.…”

mentioning

confidence: 99%

Low-Level Fusion of Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Data Sets for the Characterization of Nitrogen and Sulfur Compounds in Vacuum Gas Oils

et al. 2020

Self Cite

View full text Add to dashboard Cite

A total of 18 vacuum gas oils have been analyzed by Fourier transform ion cyclotron resonance mass spectrometry considering six replicates in three different ionization modes (electrospray ionization (ESI)(+), ESI(−), and atmospheric pressure photoionization (APPI)(+)) to characterize the nitrogen and sulfur compounds contained in these samples. Classical data analysis has been first performed on generated data sets using double bond equivalents (DBE) versus number of carbon atoms (#C) plots in order to observe similarities and differences within the nitrogen and sulfur-containing molecular classes from samples produced by different industrial processes. In a second step, three-way arrays have been generated for each ionization mode considering three dimensions: DBE related to aromaticity, number of carbon atoms related to alkylation, and sample. These threeway arrays have then be concatenated using low-level data fusion strategy to obtain a new tensor with three new modes: aromaticity, alkylation, and sample. The PARAFAC method has then been applied for the first time to this three-way data structure. A two components decomposition has allowed us to highlight unique samples with unexpected reactivity behaviors throughout hydrotreatment. The obtained loadings led to the identification of the variables responsible for this specific character. This original strategy has provided a fast visualization tool able to highlight simultaneously the impact of the three ionization modes in order to explain the differences between the samples and compare them.

show abstract

mentioning

confidence: 99%

Low-Level Fusion of Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Data Sets for the Characterization of Nitrogen and Sulfur Compounds in Vacuum Gas Oils

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…discussed in a previous work 17 . 6 principal components have been considered as significant and explain 96.7% of the total variance. The score plot obtained over PC1-PC2 is available in Figure S5 in Supporting Information.…”

Section: Sulfur Compounds the Results Obtained Considering Appi(+)-ft-icr/ms Data Have Been Exhaustivelymentioning

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

Self Cite

View full text Add to dashboard Cite

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.

show abstract

“…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%

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

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Molecular-Level Insights into Coker/Straight-Run Gas Oil Hydrodenitrogenation by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

Cited by 20 publications

References 64 publications

Low-Level Fusion of Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Data Sets for the Characterization of Nitrogen and Sulfur Compounds in Vacuum Gas Oils

Low-Level Fusion of Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Data Sets for the Characterization of Nitrogen and Sulfur Compounds in Vacuum Gas Oils

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

Contact Info

Product

Resources

About